{"id":383,"date":"2023-05-14T17:17:56","date_gmt":"2023-05-14T15:17:56","guid":{"rendered":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/?page_id=383"},"modified":"2023-05-16T18:23:46","modified_gmt":"2023-05-16T16:23:46","slug":"dr-ing-tobias-gergs","status":"publish","type":"page","link":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/dr-ing-tobias-gergs\/","title":{"rendered":"Dr.-Ing. Tobias Gergs"},"content":{"rendered":"

Senior Researcher<\/p>\n\n\n\n

\n
\n

Address<\/strong>
Ruhr-Uni\u00adver\u00adsi\u00adt\u00e4t Bo\u00adchum
Fakult\u00e4t f\u00fcr Elektrotechnik und Informationstechnik
Angewandte Elektrodynamik und Plasmatechnik
Uni\u00adver\u00adsi\u00adt\u00e4ts\u00adstra\u00ad\u00dfe 150
D-44801 Bo\u00adchum, Germany<\/p>\n\n\n\n

Room<\/strong>
ID 1\/253<\/p>\n\n\n\n

Phone<\/strong>
+49 234 32 19743<\/p>\n\n\n\n

Email<\/strong>
gergs(at)aept.rub.de<\/p>\n<\/div>\n\n\n\n

\n
\"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n
\n\n\n\n

Publications<\/strong><\/p>\n\n\n

\n\n\t\t2825793<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\tGergs<\/span>\n\t\t<\/span>\n <\/span>\n\t\t1<\/span>\n\t\tapa<\/span>\n\t\t50<\/span>\n\t\tdate<\/span>\n\t\tdesc<\/span>\n\t\tyear<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t1<\/span>\n\t\t<\/span>\n\t\t<\/span>\n\t\t<\/span>\n Gergs<\/span>\n 383<\/span>\n\t\thttps:\/\/aept.blogs.ruhr-uni-bochum.de\/wp-content\/plugins\/zotpress\/<\/span>\n\n\t\t
\n\t\t\t
\n\t\t\t\t%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%223XDCN58E%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Adejube%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-29%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAdejube%2C%20B.%2C%20Gronenberg%2C%20O.%2C%20Steel%2C%20J.%2C%20Mallinson%2C%20J.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Protsak%2C%20M.%2C%20Tjardts%2C%20T.%2C%20Hemke%2C%20T.%2C%20Nikitin%2C%20D.%2C%20Veziroglu%2C%20S.%2C%20Sch%26%23xFC%3Brmann%2C%20U.%2C%20Strunskus%2C%20T.%2C%20Choukourov%2C%20A.%2C%20Mussenbrock%2C%20T.%2C%20Trieschmann%2C%20J.%2C%20Kienle%2C%20L.%2C%20Faupel%2C%20F.%2C%20Brown%2C%20S.%20A.%2C%20%26amp%3B%20Vahl%2C%20A.%20%282025%29.%20Silver-Based%20Self-Organized%20Resistive%20Switching%20Nanoparticle%20Networks%20with%20Neural-Like%20Spiking%20Behavior%3A%20Implications%20for%20Neuromorphic%20Computing.%20%26lt%3Bi%26gt%3BACS%20Applied%20Nano%20Materials%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B%2834%29%2C%2016680%26%23x2013%3B16693.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1021%5C%2Facsanm.5c02520%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1021%5C%2Facsanm.5c02520%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3D3XDCN58E%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Silver-Based%20Self-Organized%20Resistive%20Switching%20Nanoparticle%20Networks%20with%20Neural-Like%20Spiking%20Behavior%3A%20Implications%20for%20Neuromorphic%20Computing%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Blessing%22%2C%22lastName%22%3A%22Adejube%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ole%22%2C%22lastName%22%3A%22Gronenberg%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Steel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joshua%22%2C%22lastName%22%3A%22Mallinson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mariia%22%2C%22lastName%22%3A%22Protsak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tim%22%2C%22lastName%22%3A%22Tjardts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Torben%22%2C%22lastName%22%3A%22Hemke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Daniil%22%2C%22lastName%22%3A%22Nikitin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Salih%22%2C%22lastName%22%3A%22Veziroglu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Sch%5Cu00fcrmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Strunskus%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrei%22%2C%22lastName%22%3A%22Choukourov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lorenz%22%2C%22lastName%22%3A%22Kienle%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Franz%22%2C%22lastName%22%3A%22Faupel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Simon%20Anthony%22%2C%22lastName%22%3A%22Brown%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Vahl%22%7D%5D%2C%22abstractNote%22%3A%22Brain-inspired%20computational%20systems%20with%20complex%2C%20dynamic%20behaviors%20are%20under%20active%20development.%20Self-organized%20networks%20of%20interacting%20nano-objects%20exhibit%20rich%2C%20neural-like%20spiking%20behaviors%20driven%20by%20resistive%20switching.%20The%20collective%20switching%20dynamics%20in%20nanoparticle%20networks%20%28NPNs%29%20position%20them%20as%20promising%20candidates%20for%20neuromorphic%20computing.%20However%2C%20the%20individual%20switching%20behavior%20and%20structural%20factors%20that%20govern%20spiking%20behavior%20in%20these%20networks%20remain%20to%20be%20fully%20understood.%20In%20this%20study%2C%20the%20relation%20between%20switching%20behavior%20and%20network%20composition%20and%20morphology%20is%20explored%20by%20the%20example%20of%20three%20types%20of%20silver-based%2C%20self-organized%20percolating%20NPNs%3A%20a%20monometallic%20silver%20%28Ag%29%20NPN%2C%20an%20alloy%20silver%5Cu2212gold%20%28AgAu%29%20NPN%2C%20and%20a%20composite%20silver%5Cu2212%20zirconium%20nitride%20%28Ag%5C%2FZrN%29%20NPN.%20These%20are%20compared%20with%20respect%20to%20the%20time%20scales%20of%20switching%20events%20%28SEs%29.%20The%20SEs%20comprise%20a%20switch-on%20and%20a%20relaxation%20process.%20Transmission%20electron%20microscopy%20%28TEM%29%20offers%20valuable%20insights%20into%20the%20morphological%20characteristics%20of%20the%20NPNs.%20Molecular%20dynamics%20simulations%20provide%20insights%20into%20the%20filamentary%20processes%20occurring%20between%20Ag%20nanoparticles%20%28NPs%29%2C%20exploring%20the%20dynamics%20involved%20in%20an%20SE.%20The%20distinct%20differences%20observed%20in%20switching%20time%20and%20kinetics%20suggest%20that%20the%20composition%2C%20morphology%2C%20and%20local%20environment%20of%20the%20NPs%20play%20a%20critical%20role%20in%20modulating%20resistive%20switching%20behavior%2C%20including%20filament%20formation%20and%20dissolution%20processes.%20This%20materialsbased%20approach%20enables%20modification%20of%20switch-on%20and%20relaxation%20time%20scales%20and%20patterns%20in%20self-organized%20networks.%20Such%20tunability%20is%20advantageous%20for%20applications%20where%20these%20networks%20function%20as%20physical%20reservoirs%20for%20signal%20processing%20and%20classification%20%28e.g.%2C%20speech%20recognition%29%20and%20in%20reservoir%20computing%20%28RC%29%2C%20potentially%20enhancing%20adaptive%20learning%20capabilities%20and%20computational%20performance.%22%2C%22date%22%3A%222025-08-29%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1021%5C%2Facsanm.5c02520%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fpubs.acs.org%5C%2Fdoi%5C%2F10.1021%5C%2Facsanm.5c02520%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222574-0970%2C%202574-0970%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222025-08-30T07%3A35%3A09Z%22%7D%7D%2C%7B%22key%22%3A%22YKNGNU4J%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Yarragolla%20et%20al.%22%2C%22parsedDate%22%3A%222024-12-30%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BYarragolla%2C%20S.%2C%20Hemke%2C%20T.%2C%20Jalled%2C%20F.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Trieschmann%2C%20J.%2C%20Arul%2C%20T.%2C%20%26amp%3B%20Mussenbrock%2C%20T.%20%282024%29.%20Identifying%20and%20understanding%20the%20nonlinear%20behavior%20of%20memristive%20devices.%20%26lt%3Bi%26gt%3BScientific%20Reports%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B14%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%2031633.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-024-80568-y%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-024-80568-y%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DYKNGNU4J%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Identifying%20and%20understanding%20the%20nonlinear%20behavior%20of%20memristive%20devices%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sahitya%22%2C%22lastName%22%3A%22Yarragolla%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Torben%22%2C%22lastName%22%3A%22Hemke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fares%22%2C%22lastName%22%3A%22Jalled%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tolga%22%2C%22lastName%22%3A%22Arul%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Nonlinearity%20is%20a%20crucial%20characteristic%20for%20implementing%20hardware%20security%20primitives%20or%20neuromorphic%20computing%20systems.%20The%20main%20feature%20of%20all%20memristive%20devices%20is%20this%20nonlinear%20behavior%20observed%20in%20their%20current-voltage%20characteristics.%20To%20comprehend%20the%20nonlinear%20behavior%2C%20we%20have%20to%20understand%20the%20coexistence%20of%20resistive%2C%20capacitive%2C%20and%20inertia%20%28virtual%20inductive%29%20effects%20in%20these%20devices.%20These%20effects%20originate%20from%20corresponding%20physical%20and%20chemical%20processes%20in%20memristive%20devices.%20A%20physics-inspired%20compact%20model%20is%20employed%20to%20model%20and%20simulate%20interface-type%20RRAMs%20such%20as%20Au%5C%2FBiFeO%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%24%24_%7B3%7D%24%24%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5C%2FPt%5C%2FTi%2C%20Au%5C%2FNb%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%24%24_%7B%5C%5Ctextrm%7Bx%7D%7D%24%24%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20O%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%24%24_%7B%5C%5Ctextrm%7By%7D%7D%24%24%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5C%2FAl%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%24%24_%7B2%7D%24%24%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20O%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%24%24_%7B3%7D%24%24%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5C%2FNb%2C%20while%20accounting%20for%20the%20modeling%20of%20capacitive%20and%20inertia%20effects.%20The%20simulated%20current-voltage%20characteristics%20align%20well%20with%20experimental%20data%20and%20accurately%20capture%20the%20non-zero%20crossing%20hysteresis%20generated%20by%20capacitive%20and%20inductive%20effects.%20This%20study%20examines%20the%20response%20of%20two%20devices%20to%20increasing%20frequencies%2C%20revealing%20a%20shift%20in%20their%20nonlinear%20behavior%20characterized%20by%20a%20reduced%20hysteresis%20range%20Fourier%20series%20analysis%20utilizing%20a%20sinusoidal%20input%20voltage%20of%20varying%20amplitudes%20and%20frequencies%20indicates%20harmonics%20or%20frequency%20components%20that%20considerably%20influence%20the%20functioning%20of%20RRAMs.%20Moreover%2C%20we%20propose%20and%20demonstrate%20the%20use%20of%20the%20frequency%20spectra%20as%20one%20of%20the%20fingerprints%20for%20memristive%20devices.%22%2C%22date%22%3A%222024-12-30%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs41598-024-80568-y%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs41598-024-80568-y%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222045-2322%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222025-01-02T17%3A33%3A21Z%22%7D%7D%2C%7B%22key%22%3A%22ZZFPFSC6%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Trieschmann%20et%20al.%22%2C%22parsedDate%22%3A%222023-12-28%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTrieschmann%2C%20J.%2C%20Vialetto%2C%20L.%2C%20%26amp%3B%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%20%282023%29.%20Review%3A%20Machine%20learning%20for%20advancing%20low-temperature%20plasma%20modeling%20and%20simulation.%20%26lt%3Bi%26gt%3BJournal%20of%20Micro%5C%2FNanopatterning%2C%20Materials%2C%20and%20Metrology%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B22%26lt%3B%5C%2Fi%26gt%3B%2804%29.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1117%5C%2F1.JMM.22.4.041504%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1117%5C%2F1.JMM.22.4.041504%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DZZFPFSC6%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Review%3A%20Machine%20learning%20for%20advancing%20low-temperature%20plasma%20modeling%20and%20simulation%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Luca%22%2C%22lastName%22%3A%22Vialetto%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-12-28%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1117%5C%2F1.JMM.22.4.041504%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.spiedigitallibrary.org%5C%2Fjournals%5C%2Fjournal-of-micro-nanopatterning-materials-and-metrology%5C%2Fvolume-22%5C%2Fissue-04%5C%2F041504%5C%2FReview--Machine-learning-for-advancing-low-temperature-plasma-modeling%5C%2F10.1117%5C%2F1.JMM.22.4.041504.full%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222708-8340%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222024-01-05T10%3A16%3A23Z%22%7D%7D%2C%7B%22key%22%3A%22EAQAJM94%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22De%20Los%20Arcos%20et%20al.%22%2C%22parsedDate%22%3A%222023-11-27%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDe%20Los%20Arcos%2C%20T.%2C%20Awakowicz%2C%20P.%2C%20B%26%23xF6%3Bke%2C%20M.%2C%20Boysen%2C%20N.%2C%20Brinkmann%2C%20R.%20P.%2C%20Dahlmann%2C%20R.%2C%20Devi%2C%20A.%2C%20Eremin%2C%20D.%2C%20Franke%2C%20J.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Jenderny%2C%20J.%2C%20Kemaneci%2C%20E.%2C%20K%26%23xFC%3Bhne%2C%20T.%20D.%2C%20Kusmierz%2C%20S.%2C%20Mussenbrock%2C%20T.%2C%20Rubner%2C%20J.%2C%20Trieschmann%2C%20J.%2C%20Wessling%2C%20M.%2C%20Xie%2C%20X.%2C%20%26%23x2026%3B%20Grundmeier%2C%20G.%20%282023%29.%20PECVD%20and%20PEALD%20on%20polymer%20substrates%20%28part%20II%29%3A%20Understanding%20and%20tuning%20of%20barrier%20and%20membrane%20properties%20of%20thin%20films.%20%26lt%3Bi%26gt%3BPlasma%20Processes%20and%20Polymers%26lt%3B%5C%2Fi%26gt%3B%2C%20e2300186.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202300186%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202300186%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DEAQAJM94%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22PECVD%20and%20PEALD%20on%20polymer%20substrates%20%28part%20II%29%3A%20Understanding%20and%20tuning%20of%20barrier%20and%20membrane%20properties%20of%20thin%20films%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Teresa%22%2C%22lastName%22%3A%22De%20Los%20Arcos%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Peter%22%2C%22lastName%22%3A%22Awakowicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%22%2C%22lastName%22%3A%22B%5Cu00f6ke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nils%22%2C%22lastName%22%3A%22Boysen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ralf%20Peter%22%2C%22lastName%22%3A%22Brinkmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rainer%22%2C%22lastName%22%3A%22Dahlmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anjana%22%2C%22lastName%22%3A%22Devi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Denis%22%2C%22lastName%22%3A%22Eremin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jonas%22%2C%22lastName%22%3A%22Franke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jonathan%22%2C%22lastName%22%3A%22Jenderny%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Efe%22%2C%22lastName%22%3A%22Kemaneci%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%20D.%22%2C%22lastName%22%3A%22K%5Cu00fchne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Simon%22%2C%22lastName%22%3A%22Kusmierz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jens%22%2C%22lastName%22%3A%22Rubner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthias%22%2C%22lastName%22%3A%22Wessling%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Xiaofan%22%2C%22lastName%22%3A%22Xie%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Zanders%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frederik%22%2C%22lastName%22%3A%22Zysk%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guido%22%2C%22lastName%22%3A%22Grundmeier%22%7D%5D%2C%22abstractNote%22%3A%22This%20feature%20article%20presents%20insights%20concerning%20the%20correlation%20of%20plasmaenhanced%20chemical%20vapor%20deposition%20and%20plasma%5Cu2010enhanced%20atomic%20layer%20deposition%20thin%20film%20structures%20with%20their%20barrier%20or%20membrane%20properties.%20While%20in%20principle%20similar%20precursor%20gases%20and%20processes%20can%20be%20applied%2C%20the%20adjustment%20of%20deposition%20parameters%20for%20different%20polymer%20substrates%20can%20lead%20to%20either%20an%20effective%20diffusion%20barrier%20or%20selective%20permeabilities.%20In%20both%20cases%2C%20the%20understanding%20of%20the%20film%20growth%20and%20the%20analysis%20of%20the%20pore%20size%20distribution%20and%20the%20pore%20surface%20chemistry%20is%20of%20utmost%20importance%20for%20the%20understanding%20of%20the%20related%20transport%20properties%20of%20small%20molecules.%20In%20this%20regard%2C%20the%20article%20presents%20both%20concepts%20of%20thin%20film%20engineering%20and%20analytical%20as%20well%20as%20theoretical%20approaches%20leading%20to%20a%20comprehensive%20description%20of%20the%20state%20of%20the%20art%20in%20this%20field.%20Perspectives%20of%20future%20relevant%20research%20in%20this%20area%2C%20exploiting%20the%20presented%20correlation%20of%20film%20structure%20and%20molecular%20transport%20properties%2C%20are%20presented.%22%2C%22date%22%3A%222023-11-27%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Fppap.202300186%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Fppap.202300186%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221612-8850%2C%201612-8869%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222023-11-29T07%3A49%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22VECGDG7K%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22De%20Los%20Arcos%20et%20al.%22%2C%22parsedDate%22%3A%222023-10-30%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDe%20Los%20Arcos%2C%20T.%2C%20Awakowicz%2C%20P.%2C%20Benedikt%2C%20J.%2C%20Biskup%2C%20B.%2C%20B%26%23xF6%3Bke%2C%20M.%2C%20Boysen%2C%20N.%2C%20Buschhaus%2C%20R.%2C%20Dahlmann%2C%20R.%2C%20Devi%2C%20A.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Jenderny%2C%20J.%2C%20Von%20Keudell%2C%20A.%2C%20K%26%23xFC%3Bhne%2C%20T.%20D.%2C%20Kusmierz%2C%20S.%2C%20M%26%23xFC%3Bller%2C%20H.%2C%20Mussenbrock%2C%20T.%2C%20Trieschmann%2C%20J.%2C%20Zanders%2C%20D.%2C%20Zysk%2C%20F.%2C%20%26amp%3B%20Grundmeier%2C%20G.%20%282023%29.%20PECVD%20and%20PEALD%20on%20polymer%20substrates%20%28part%20I%29%3A%20Fundamentals%20and%20analysis%20of%20plasma%20activation%20and%20thin%20film%20growth.%20%26lt%3Bi%26gt%3BPlasma%20Processes%20and%20Polymers%26lt%3B%5C%2Fi%26gt%3B%2C%20e2300150.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202300150%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202300150%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DVECGDG7K%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22PECVD%20and%20PEALD%20on%20polymer%20substrates%20%28part%20I%29%3A%20Fundamentals%20and%20analysis%20of%20plasma%20activation%20and%20thin%20film%20growth%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Teresa%22%2C%22lastName%22%3A%22De%20Los%20Arcos%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Peter%22%2C%22lastName%22%3A%22Awakowicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Benedikt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Beatrix%22%2C%22lastName%22%3A%22Biskup%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marc%22%2C%22lastName%22%3A%22B%5Cu00f6ke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nils%22%2C%22lastName%22%3A%22Boysen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rahel%22%2C%22lastName%22%3A%22Buschhaus%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rainer%22%2C%22lastName%22%3A%22Dahlmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anjana%22%2C%22lastName%22%3A%22Devi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jonathan%22%2C%22lastName%22%3A%22Jenderny%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Achim%22%2C%22lastName%22%3A%22Von%20Keudell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%20D.%22%2C%22lastName%22%3A%22K%5Cu00fchne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Simon%22%2C%22lastName%22%3A%22Kusmierz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hendrik%22%2C%22lastName%22%3A%22M%5Cu00fcller%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Zanders%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frederik%22%2C%22lastName%22%3A%22Zysk%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guido%22%2C%22lastName%22%3A%22Grundmeier%22%7D%5D%2C%22abstractNote%22%3A%22This%20feature%20article%20presents%20recent%20results%20on%20the%20analysis%20of%20plasma%5C%2Fpolymer%20interactions%20and%20the%20nucleation%20of%20ultra%5Cu2010thin%20plasma%20films%20on%20polymeric%20substrates.%20Because%20of%20their%20high%20importance%20for%20the%20understanding%20of%20such%20processes%2C%20in%20situ%20analytical%20approaches%20of%20the%20plasma%20volume%20as%20well%20as%20the%20plasma%5C%2Fsubstrate%20interfaces%20are%20introduced%20before%20the%20findings%20on%20plasma%20surface%20chemistry.%20The%20plasma%20activation%20of%20polymeric%20substrates%20is%20divided%20into%20the%20understanding%20of%20fundamental%20processes%20on%20model%20substrates%20and%20the%20relevance%20of%20polymer%20surface%20complexity.%20Concerning%20thin%20film%20nucleation%20and%20growth%2C%20both%20plasma%5Cu2010enhanced%20chemical%20vapor%20deposition%20and%20plasma%5Cu2010enhanced%20atomic%20layer%20deposition%20processes%20as%20well%20as%20the%20combination%20of%20both%20processes%20are%20considered%20both%20for%20model%20substrates%20and%20technical%20polymers.%20Based%20on%20the%20comprehensive%20presentation%20of%20recent%20results%2C%20selective%20perspectives%20of%20this%20research%20field%20are%20discussed.%22%2C%22date%22%3A%222023-10-30%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Fppap.202300150%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Fppap.202300150%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221612-8850%2C%201612-8869%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222023-11-02T11%3A26%3A49Z%22%7D%7D%2C%7B%22key%22%3A%22CK78LLZ9%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222023-05-11%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Mussenbrock%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282023%29.%20Physics-separating%20artificial%20neural%20networks%20for%20predicting%20sputtering%20and%20thin%20film%20deposition%20of%20AlN%20in%20Ar%5C%2FN%20%26lt%3Bsub%26gt%3B2%26lt%3B%5C%2Fsub%26gt%3B%20discharges%20on%20experimental%20timescales.%20%26lt%3Bi%26gt%3BJournal%20of%20Physics%20D%3A%20Applied%20Physics%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B56%26lt%3B%5C%2Fi%26gt%3B%2819%29%2C%20194001.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6463%5C%2Facc07e%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6463%5C%2Facc07e%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DCK78LLZ9%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Physics-separating%20artificial%20neural%20networks%20for%20predicting%20sputtering%20and%20thin%20film%20deposition%20of%20AlN%20in%20Ar%5C%2FN%20%3Csub%3E2%3C%5C%2Fsub%3E%20discharges%20on%20experimental%20timescales%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22Understanding%20and%20modeling%20plasma%5Cu2013surface%20interactions%20frame%20a%20multi-scale%20as%20well%20as%20multi-physics%20problem.%20Scale-bridging%20machine%20learning%20surface%20surrogate%20models%20have%20been%20demonstrated%20to%20perceive%20the%20fundamental%20atomic%20fidelity%20for%20the%20physical%20vapor%20deposition%20of%20pure%20metals.%20However%2C%20the%20immense%20computational%20cost%20of%20the%20data-generating%20simulations%20render%20a%20practical%20application%20with%20predictions%20on%20relevant%20timescales%20impracticable.%20This%20issue%20is%20resolved%20in%20this%20work%20for%20the%20sputter%20deposition%20of%20AlN%20in%20Ar%5C%2FN2%20discharges%20by%20developing%20a%20scheme%20that%20populates%20the%20parameter%20spaces%20effectively.%20Hybrid%20reactive%20molecular%20dynamics%5C%2F%20time-stamped%20force-bias%20Monte%20Carlo%20simulations%20of%20randomized%20plasma-surface%20interactions%5C%2F%20diffusion%20processes%20are%20used%20to%20setup%20a%20physics-separating%20artificial%20neural%20network.%20The%20application%20of%20this%20generic%20machine%20learning%20model%20to%20a%20specific%20experimental%20reference%20case%20study%20enables%20the%20systematic%20analysis%20of%20the%20particle%20flux%20emission%20as%20well%20as%20underlying%20system%20state%20%28e.g.%20composition%2C%20density%2C%20point%20defect%20structure%29%20evolution%20within%20process%20times%20of%20up%20to%2045%20min.%22%2C%22date%22%3A%222023-05-11%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1088%5C%2F1361-6463%5C%2Facc07e%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fiopscience.iop.org%5C%2Farticle%5C%2F10.1088%5C%2F1361-6463%5C%2Facc07e%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220022-3727%2C%201361-6463%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222023-07-28T16%3A31%3A03Z%22%7D%7D%2C%7B%22key%22%3A%22A8JTEXFM%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222023-02-23%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Mussenbrock%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282023%29.%20Physics-separating%20artificial%20neural%20networks%20for%20predicting%20initial%20stages%20of%20Al%20sputtering%20and%20thin%20film%20deposition%20in%20Ar%20plasma%20discharges.%20%26lt%3Bi%26gt%3BJournal%20of%20Physics%20D%3A%20Applied%20Physics%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B56%26lt%3B%5C%2Fi%26gt%3B%288%29%2C%20084003.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6463%5C%2Facb6a4%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6463%5C%2Facb6a4%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DA8JTEXFM%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Physics-separating%20artificial%20neural%20networks%20for%20predicting%20initial%20stages%20of%20Al%20sputtering%20and%20thin%20film%20deposition%20in%20Ar%20plasma%20discharges%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22Simulations%20of%20Al%20thin%20film%20sputter%20depositions%20rely%20on%20accurate%20plasma%20and%20surface%20interaction%20models.%20Establishing%20the%20latter%20commonly%20requires%20a%20higher%20level%20of%20abstraction%20and%20means%20to%20dismiss%20the%20fundamental%20atomic%20fidelity.%20Previous%20works%20on%20sputtering%20processes%20addressed%20this%20issue%20by%20establishing%20machine%20learning%20surrogate%20models%2C%20which%20include%20a%20basic%20surface%20state%20%28i.e.%20stoichiometry%29%20as%20static%20input.%20In%20this%20work%2C%20an%20evolving%20surface%20state%20and%20defect%20structure%20are%20introduced%20to%20jointly%20describe%20sputtering%20and%20growth%20with%20physics-separating%20artificial%20neural%20networks.%20The%20data%20describing%20the%20plasma%5Cu2013surface%20interactions%20%28PSIs%29%20stem%20from%20hybrid%20reactive%20molecular%20dynamics%5C%2Ftime-stamped%20force%20bias%20Monte%20Carlo%20simulations%20of%20Al%20neutrals%20and%20Ar%2B%20ions%20impinging%20onto%20Al%28001%29%20surfaces.%20It%20is%20demonstrated%20that%20the%20fundamental%20processes%20are%20comprehensively%20described%20by%20taking%20the%20surface%20state%20as%20well%20as%20defect%20structure%20into%20account.%20Hence%2C%20a%20machine%20learning%20PSI%20surrogate%20model%20is%20established%20that%20resolves%20the%20inherent%20kinetics%20with%20high%20physical%20fidelity.%20The%20resulting%20model%20is%20not%20restricted%20to%20input%20from%20modeling%20and%20simulation%2C%20but%20may%20similarly%20be%20applied%20to%20experimental%20input%20data.%22%2C%22date%22%3A%222023-02-23%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1088%5C%2F1361-6463%5C%2Facb6a4%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fiopscience.iop.org%5C%2Farticle%5C%2F10.1088%5C%2F1361-6463%5C%2Facb6a4%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220022-3727%2C%201361-6463%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222023-02-10T09%3A13%3A56Z%22%7D%7D%2C%7B%22key%22%3A%22EAVHWGGG%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222023%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Mussenbrock%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282023%29.%20Charge-optimized%20many-body%20interaction%20potential%20for%20AlN%20revisited%20to%20explore%20plasma%26%23x2013%3Bsurface%20interactions.%20%26lt%3Bi%26gt%3BScientific%20Reports%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B13%26lt%3B%5C%2Fi%26gt%3B%2C%205287.%20https%3A%5C%2F%5C%2Fdoi.org%5C%2F%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-023-31862-8%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-023-31862-8%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DEAVHWGGG%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Charge-optimized%20many-body%20interaction%20potential%20for%20AlN%20revisited%20to%20explore%20plasma%5Cu2013surface%20interactions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-023-31862-8%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-023-31862-8%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222023-03-31T16%3A16%3A38Z%22%7D%7D%2C%7B%22key%22%3A%227BKNP85P%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222022-08-14%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Mussenbrock%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282022%29.%20Molecular%20dynamics%20study%20on%20the%20role%20of%20Ar%20ions%20in%20the%20sputter%20deposition%20of%20Al%20thin%20films.%20%26lt%3Bi%26gt%3BJournal%20of%20Applied%20Physics%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B132%26lt%3B%5C%2Fi%26gt%3B%286%29%2C%20063302.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F5.0098040%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F5.0098040%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3D7BKNP85P%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Molecular%20dynamics%20study%20on%20the%20role%20of%20Ar%20ions%20in%20the%20sputter%20deposition%20of%20Al%20thin%20films%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22Compressive%20stresses%20in%20sputter%20deposited%20thin%20films%20are%20generally%20assumed%20to%20be%20caused%20by%20forward%20sputtered%20%28peened%29%20built-in%20particles%20and%20entrapped%20working%20gas%20atoms.%20While%20the%20former%20are%20assumed%20to%20be%20predominant%2C%20the%20effect%20of%20the%20latter%20on%20interaction%20dynamics%20and%20thin%20film%20properties%20is%20scarcely%20clarified%20%28concurrent%20or%20causative%29.%20The%20overlay%20of%20the%20ion%20bombardment%20induced%20processes%20renders%20an%20isolation%20of%20their%20contribution%20impracticable.%20This%20issue%20is%20addressed%20by%20two%20molecular%20dynamics%20case%20studies%20considering%20the%20sputter%20deposition%20of%20Al%20thin%20films%20in%20Ar%20working%20gas.%20First%2C%20Ar%20atoms%20are%20fully%20retained.%20Second%2C%20they%20are%20artificially%20neglected%2C%20as%20implanted%20Ar%20atoms%20are%20assumed%20to%20outgas%20anyhow%20and%20not%20alter%20the%20ongoing%20dynamics%20significantly.%20Both%20case%20studies%20share%20common%20particle%20dose%20impinging%20Al%28001%29%20surfaces.%20Ion%20energies%20from%203%20to%20300%20eV%20and%20Al%3DAr%5Cu00fe%20flux%20ratios%20from%200%20to%201%20are%20considered.%20The%20surface%20interactions%20are%20simulated%20by%20hybrid%20reactive%20molecular%20dynamics%5C%2Fforce-biased%20Monte%20Carlo%20simulations%20and%20characterized%20in%20terms%20of%20mass%20density%2C%20Ar%20concentration%2C%20biaxial%20stress%2C%20shear%20stress%2C%20ring%20statistical%20connectivity%20profile%2C%20Ar%20gas%20porosity%2C%20Al%20vacancy%20density%2C%20and%20root-mean-squared%20roughness.%20Implanted%20Ar%20atoms%20are%20found%20to%20form%20subnanometer%20sized%20eventually%20outgassing%20clusters%20for%20ion%20energies%20exceeding%20100%20eV.%20They%20fundamentally%20govern%20a%20variety%20of%20surface%20processes%20%28e.g.%2C%20forward%20sputtering%5C%2Fpeening%29%20and%20surface%20properties%20%28e.g.%2C%20compressive%20stresses%29%20in%20the%20considered%20operating%20regime.%22%2C%22date%22%3A%222022-08-14%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1063%5C%2F5.0098040%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Faip.scitation.org%5C%2Fdoi%5C%2F10.1063%5C%2F5.0098040%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220021-8979%2C%201089-7550%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222022-08-09T16%3A01%3A13Z%22%7D%7D%2C%7B%22key%22%3A%22NTT4YX5U%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222022%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Monti%2C%20C.%2C%20Gaiser%2C%20S.%2C%20Amberg%2C%20M.%2C%20Sch%26%23xFC%3Btz%2C%20U.%2C%20Mussenbrock%2C%20T.%2C%20Trieschmann%2C%20J.%2C%20Heuberger%2C%20M.%2C%20%26amp%3B%20Hegemann%2C%20D.%20%282022%29.%20Nanoporous%20SiOx%20plasma%20polymer%20films%20as%20carrier%20for%20liquid%26%23x2010%3Binfused%20surfaces.%20%26lt%3Bi%26gt%3BPlasma%20Processes%20and%20Polymers%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B19%26lt%3B%5C%2Fi%26gt%3B%288%29%2C%202200049.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202200049%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fppap.202200049%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DNTT4YX5U%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Nanoporous%20SiOx%20plasma%20polymer%20films%20as%20carrier%20for%20liquid%5Cu2010infused%20surfaces%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Chiara%22%2C%22lastName%22%3A%22Monti%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sandra%22%2C%22lastName%22%3A%22Gaiser%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Martin%22%2C%22lastName%22%3A%22Amberg%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Urs%22%2C%22lastName%22%3A%22Sch%5Cu00fctz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Manfred%22%2C%22lastName%22%3A%22Heuberger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dirk%22%2C%22lastName%22%3A%22Hegemann%22%7D%5D%2C%22abstractNote%22%3A%22Liquid%5Cu2010infused%20surfaces%20are%20based%20upon%20the%20infusion%20of%20a%20liquid%20phase%20into%20a%20porous%20solid%20material%20to%20induce%20slippery%20and%20repellent%20character.%20In%20this%20context%2C%20porous%20SiOx%20plasma%20polymer%20films%20represent%20a%20relevant%20candidate%20for%20a%20robust%20nanoporous%20carrier%20layer.%20Intermittent%20low%5Cu2010pressure%20plasma%20etching%20of%20O2%5C%2Fhexamethyldisiloxane%5Cu2010derived%20coatings%20is%20investigated%20to%20enhance%20the%20intrinsic%20porosity%20inherent%20to%20residual%20hydrocarbons%20in%20the%20silica%20matrix.%20Simulations%20of%20the%20resulting%20Si%5Cu2013O%20ring%20network%20structure%20using%20reactive%20molecular%20dynamics%20indicate%20formation%20of%20interconnected%20voids%20with%20Si%5Cu2013OH%20functionalized%20pore%20walls%20allowing%20water%20penetration%20with%20almost%20Fickian%20diffusive%20behavior.%20The%20corresponding%20porosity%20of%20up%20to%2018%25%2C%20well%20agreeing%20with%20simulations%2C%20Fourier%5Cu2010transform%20infrared%20spectroscopy%2C%20and%20ellipsometry%20measurements%2C%20was%20found%20to%20be%20suitable%20for%20the%20liquid%20infusion%20of%20polyethylene%20glycol%20molecules%20into%20about%2080%20nm%20thick%20SiOx%20films%20providing%20ongoing%20lubricating%20properties%2C%20thus%20revealing%20their%20suitability%20as%20liquid%5Cu2010infused%20surfaces.%22%2C%22date%22%3A%2208%5C%2F2022%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Fppap.202200049%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Fppap.202200049%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221612-8850%2C%201612-8869%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222022-08-04T15%3A45%3A45Z%22%7D%7D%2C%7B%22key%22%3A%22W3UZFKRG%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222022%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Borislavov%2C%20B.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282022%29.%20Efficient%20plasma-surface%20interaction%20surrogate%20model%20for%20sputtering%20processes%20based%20on%20autoencoder%20neural%20networks.%20%26lt%3Bi%26gt%3BJournal%20of%20Vacuum%20Science%20%26amp%3B%20Technology%20B%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B40%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%20012802.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1116%5C%2F6.0001485%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1116%5C%2F6.0001485%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DW3UZFKRG%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Efficient%20plasma-surface%20interaction%20surrogate%20model%20for%20sputtering%20processes%20based%20on%20autoencoder%20neural%20networks%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Borislav%22%2C%22lastName%22%3A%22Borislavov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22Simulations%20of%20thin%20film%20sputter%20deposition%20require%20the%20separation%20of%20the%20plasma%20and%20material%20transport%20in%20the%20gas%20phase%20from%20the%20growth%5C%2Fsputtering%20processes%20at%20the%20bounding%20surfaces%20%28e.g.%2C%20substrate%20and%20target%29.%20Interface%20models%20based%20on%20analytic%20expressions%20or%20look-up%20tables%20inherently%20restrict%20this%20complex%20interaction%20to%20a%20bare%20minimum.%20A%20machine%20learning%20model%20has%20recently%20been%20shown%20to%20overcome%20this%20remedy%20for%20Ar%20ions%20bombarding%20a%20Ti-Al%20composite%20target.%20However%2C%20the%20chosen%20network%20structure%20%28i.e.%2C%20a%20multilayer%20perceptron%2C%20MLP%29%20provides%20approximately%204%5Cu00c2106%20degrees%20of%20freedom%2C%20which%20bears%20the%20risk%20of%20overfitting%20the%20relevant%20dynamics%20and%20complicating%20the%20model%20to%20an%20unreliable%20extent.%20This%20work%20proposes%20a%20conceptually%20more%20sophisticated%20but%20parameterwise%20simplified%20regression%20artificial%20neural%20network%20for%20an%20extended%20scenario%2C%20considering%20a%20variable%20instead%20of%20a%20single%20fixed%20Ti-Al%20stoichiometry.%20A%20convolutional%20%5Cu03b2-variational%20autoencoder%20is%20trained%20to%20reduce%20the%20high-dimensional%20energy-angular%20distribution%20of%20sputtered%20particles%20to%20a%20low-dimensional%20latent%20representation%20with%20only%20two%20components.%20In%20addition%20to%20a%20primary%20decoder%20that%20is%20trained%20to%20reconstruct%20the%20input%20energy-angular%20distribution%2C%20a%20secondary%20decoder%20is%20employed%20to%20reconstruct%20the%20mean%20energy%20of%20incident%20Ar%20ions%20as%20well%20as%20the%20present%20Ti-Al%20composition.%20The%20mutual%20latent%20space%20is%20hence%20conditioned%20on%20these%20quantities.%20The%20trained%20primary%20decoder%20of%20the%20variational%20autoencoder%20network%20is%20subsequently%20transferred%20to%20a%20regression%20network%2C%20for%20which%20only%20the%20mapping%20to%20the%20particular%20low-dimensional%20space%20has%20to%20be%20learned.%20While%20obtaining%20a%20competitive%20performance%2C%20the%20number%20of%20degrees%20of%20freedom%20is%20drastically%20reduced%20to%2015%20111%20%280.378%25%20of%20the%20MLP%29%20and%20486%20%280.012%25%20of%20the%20MLP%29%20parameters%20for%20the%20primary%20decoder%20and%20the%20remaining%20regression%20network%2C%20respectively.%20The%20underlying%20methodology%20is%20very%20general%20and%20can%20easily%20be%20extended%20to%20more%20complex%20physical%20descriptions%20%28e.g.%2C%20taking%20into%20account%20dynamical%20surface%20properties%29%20with%20a%20minimal%20amount%20of%20data%20required.%22%2C%22date%22%3A%2201%5C%2F2022%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1116%5C%2F6.0001485%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Favs.scitation.org%5C%2Fdoi%5C%2F10.1116%5C%2F6.0001485%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222166-2746%2C%202166-2754%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222021-12-23T14%3A35%3A15Z%22%7D%7D%2C%7B%22key%22%3A%222AA5GUY3%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222021-11-09%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Schmidt%2C%20F.%2C%20Mussenbrock%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282021%29.%20Generalized%20Method%20for%20Charge-Transfer%20Equilibration%20in%20Reactive%20Molecular%20Dynamics.%20%26lt%3Bi%26gt%3BJournal%20of%20Chemical%20Theory%20and%20Computation%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B17%26lt%3B%5C%2Fi%26gt%3B%2811%29%2C%206691%26%23x2013%3B6704.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1021%5C%2Facs.jctc.1c00382%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1021%5C%2Facs.jctc.1c00382%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3D2AA5GUY3%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Generalized%20Method%20for%20Charge-Transfer%20Equilibration%20in%20Reactive%20Molecular%20Dynamics%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frederik%22%2C%22lastName%22%3A%22Schmidt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22Variable%20charge%20models%20%28e.g.%2C%20electronegativity%20equalization%20method%20%28EEM%29%2C%20charge%20equilibration%20%28QEq%29%2C%20electrostatic%20plus%20%28ES%2B%29%29%20used%20in%20reactive%20molecular%20dynamics%20simulations%20often%20inherently%20impose%20a%20global%20charge%20transfer%20between%20atoms%20%28approximating%20each%20system%20as%20an%20ideal%20metal%29.%20Consequently%2C%20most%20surface%20processes%20%28e.g.%2C%20adsorption%2C%20desorption%2C%20deposition%2C%20sputtering%29%20are%20a%5Cufb00ected%2C%20potentially%20causing%20dubious%20dynamics.%20This%20issue%20has%20been%20addressed%20by%20certain%20split%20charge%20variants%20%28i.e.%2C%20split%20charge%20equilibration%20%28SQE%29%2C%20redoxSQE%29%20through%20a%20distance-dependent%20bond%20hardness%2C%20by%20the%20atomic%20charge%20ACKS2%20and%20QTPIE%20models%2C%20which%20are%20based%20on%20the%20Kohn%5Cu2212Sham%20density%20functional%20theory%2C%20as%20well%20as%20by%20an%20electronegativity%20screening%20extension%20to%20the%20QEq%20model%20%28approximating%20each%20system%20as%20an%20ideal%20insulator%29.%20In%20a%20brief%20review%20of%20the%20QEq%20and%20the%20QTPIE%20model%2C%20their%20applicability%20for%20studying%20surface%20interactions%20is%20assessed%20in%20this%20work.%20Following%20this%20evaluation%2C%20a%20revised%20generalization%20of%20the%20QEq%20and%20QTPIE%20models%20is%20proposed%20and%20formulated%2C%20called%20the%20charge-transfer%20equilibration%20model%20or%20in%20short%20the%20QTE%20model.%20This%20method%20is%20based%20on%20the%20equilibration%20of%20charge-transfer%20variables%2C%20which%20locally%20constrain%20the%20split%20charge%20transfer%20per%20unit%20time%20%28i.e.%2C%20due%20to%20overlapping%20orbitals%29%20without%20any%20kind%20of%20bond%20hardness%20speci%5Cufb01cation.%20Furthermore%2C%20a%20formalism%20relying%20solely%20on%20atomic%20charges%20is%20obtained%20by%20a%20respective%20transformation%2C%20employing%20an%20extended%20Lagrangian%20method.%20We%20moreover%20propose%20a%20mirror%20boundary%20condition%20and%20its%20implementation%20to%20accelerate%20surface%20investigations.%20The%20models%20proposed%20in%20this%20work%20facilitate%20reactive%20molecular%20dynamics%20simulations%2C%20which%20describe%20various%20materials%20and%20surface%20phenomena%20appropriately.%22%2C%22date%22%3A%222021-11-09%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1021%5C%2Facs.jctc.1c00382%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fpubs.acs.org%5C%2Fdoi%5C%2F10.1021%5C%2Facs.jctc.1c00382%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221549-9618%2C%201549-9626%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222021-11-18T16%3A32%3A10Z%22%7D%7D%2C%7B%22key%22%3A%22IT2TA5DU%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Schmidt%20et%20al.%22%2C%22parsedDate%22%3A%222019-05-07%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BSchmidt%2C%20F.%2C%20Trieschmann%2C%20J.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20%26amp%3B%20Mussenbrock%2C%20T.%20%282019%29.%20A%20generic%20method%20for%20equipping%20arbitrary%20rf%20discharge%20simulation%20frameworks%20with%20external%20lumped%20element%20circuits.%20%26lt%3Bi%26gt%3BJournal%20of%20Applied%20Physics%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B125%26lt%3B%5C%2Fi%26gt%3B%2817%29%2C%20173106.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F1.5091965%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F1.5091965%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DIT2TA5DU%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22A%20generic%20method%20for%20equipping%20arbitrary%20rf%20discharge%20simulation%20frameworks%20with%20external%20lumped%20element%20circuits%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frederik%22%2C%22lastName%22%3A%22Schmidt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%5D%2C%22abstractNote%22%3A%22External%20electric%20circuits%20attached%20to%20radio-frequency%20plasma%20discharges%20are%20essential%20for%20the%20power%20transfer%20into%20the%20discharge%20and%20are%2C%20therefore%2C%20a%20key%20element%20for%20plasma%20operation.%20Many%20plasma%20simulations%2C%20however%2C%20simplify%20or%20even%20neglect%20the%20external%20network.%20This%20is%20because%20a%20solution%20of%20the%20circuit%5Cu2019s%20auxiliary%20di%5Cufb00erential%20equations%20following%20Kirchho%5Cufb00%5Cu2019s%20laws%20is%20required%2C%20which%20can%20become%20a%20tedious%20task%20especially%20for%20large%20circuits.%20This%20work%20proposes%20a%20method%20which%20allows%20one%20to%20include%20electric%20circuits%20in%20any%20desired%20radio-frequency%20plasma%20simulation.%20Conceptually%2C%20arbitrarily%20complex%20external%20networks%20may%20be%20incorporated%20in%20the%20form%20of%20a%20simple%20netlist.%20The%20suggested%20approach%20is%20based%20on%20the%20harmonic%20balance%20concept%2C%20which%20splits%20the%20whole%20system%20into%20the%20nonlinear%20plasma%20and%20the%20linear%20circuit%20contribution.%20A%20mathematical%20formulation%20of%20the%20in%5Cufb02uence%20of%20the%20applied%20voltage%20on%20the%20current%20for%20each%20speci%5Cufb01c%20harmonic%20is%20required%20and%20proposed.%20It%20is%20demonstrated%20that%20this%20method%20is%20applicable%20for%20both%20simple%20global%20plasma%20models%20and%20more%20complex%20spatially%20resolved%20Particle-in-Cell%20simulations.%22%2C%22date%22%3A%222019-05-07%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1063%5C%2F1.5091965%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Faip.scitation.org%5C%2Fdoi%5C%2F10.1063%5C%2F1.5091965%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220021-8979%2C%201089-7550%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222021-07-18T04%3A47%3A02Z%22%7D%7D%2C%7B%22key%22%3A%22B8BUWL8H%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kr%5Cu00fcger%20et%20al.%22%2C%22parsedDate%22%3A%222019-03-08%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BKr%26%23xFC%3Bger%2C%20F.%2C%20%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20%26amp%3B%20Trieschmann%2C%20J.%20%282019%29.%20Machine%20learning%20plasma-surface%20interface%20for%20coupling%20sputtering%20and%20gas-phase%20transport%20simulations.%20%26lt%3Bi%26gt%3BPlasma%20Sources%20Science%20and%20Technology%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B28%26lt%3B%5C%2Fi%26gt%3B%283%29%2C%20035002.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6595%5C%2Fab0246%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1088%5C%2F1361-6595%5C%2Fab0246%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DB8BUWL8H%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Machine%20learning%20plasma-surface%20interface%20for%20coupling%20sputtering%20and%20gas-phase%20transport%20simulations%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Florian%22%2C%22lastName%22%3A%22Kr%5Cu00fcger%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%22%2C%22lastName%22%3A%22Trieschmann%22%7D%5D%2C%22abstractNote%22%3A%22A%20uni%5Cufb01ed%20model%20of%20thin%20%5Cufb01lm%20deposition%20by%20means%20of%20sputter%20deposition%20requires%20a%20description%20which%20bridges%20the%20intrinsic%20time%20and%20length%20scales%20of%20both%20the%20solid%20and%20the%20gas-phase.%20As%20a%20proof%20of%20concept%2C%20in%20this%20work%20such%20a%20description%20is%20established%20based%20on%20machine%20learning%20techniques%20using%20arti%5Cufb01cial%20neural%20networks.%20Initially%2C%20sputtered%20particle%20distributions%20are%20obtained%20from%20transport%20of%20ions%20in%20matter%20based%20simulations%20for%20Ar%20projectiles%20bombarding%20a%20Ti%5Cu2013Al%20composite%20for%20a%20number%20of%20representative%20incident%20particle%20energy%20distribution%20functions.%20Subsequently%2C%20a%20multilayer%20perceptron%20network%20is%20trained%20and%20veri%5Cufb01ed%20with%20this%20set%20of%20incident%5C%2Foutgoing%20distributions.%20An%20error%20analysis%20is%20carried%20out%20for%20the%20obtained%20training%20results%20and%20their%20quality%20is%20compared%20and%20discussed%20for%20two%20sets%20of%20hyperparameters.%20Therewith%2C%20it%20is%20demonstrated%20that%20the%20trained%20network%20is%20able%20to%20predict%20the%20sputtered%20particle%20distributions%20for%20unknown%2C%20arbitrarily%20shaped%20incident%20ion%20energy%20distributions.%20It%20is%20consequently%20argued%20that%20the%20trained%20network%20may%20be%20readily%20used%20as%20a%20machine%20learning%20based%20model%20interface%2C%20which%20is%20suf%5Cufb01ciently%20accurate%20also%20in%20scenarios%20which%20have%20not%20been%20previously%20trained.%22%2C%22date%22%3A%222019-03-08%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1088%5C%2F1361-6595%5C%2Fab0246%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fiopscience.iop.org%5C%2Farticle%5C%2F10.1088%5C%2F1361-6595%5C%2Fab0246%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221361-6595%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222021-07-18T05%3A33%3A55Z%22%7D%7D%2C%7B%22key%22%3A%22U3JRKI4V%22%2C%22library%22%3A%7B%22id%22%3A2825793%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gergs%20et%20al.%22%2C%22parsedDate%22%3A%222018-06-28%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bstrong%26gt%3BGergs%26lt%3B%5C%2Fstrong%26gt%3B%2C%20T.%2C%20Dirkmann%2C%20S.%2C%20%26amp%3B%20Mussenbrock%2C%20T.%20%282018%29.%20Integration%20of%20external%20electric%20fields%20in%20molecular%20dynamics%20simulation%20models%20for%20resistive%20switching%20devices.%20%26lt%3Bi%26gt%3BJournal%20of%20Applied%20Physics%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B123%26lt%3B%5C%2Fi%26gt%3B%2824%29%2C%20245301.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F1.5029877%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1063%5C%2F1.5029877%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3Ba%20title%3D%26%23039%3BCite%20in%20RIS%20Format%26%23039%3B%20class%3D%26%23039%3Bzp-CiteRIS%26%23039%3B%20data-zp-cite%3D%26%23039%3Bapi_user_id%3D2825793%26amp%3Bitem_key%3DU3JRKI4V%26%23039%3B%20href%3D%26%23039%3Bjavascript%3Avoid%280%29%3B%26%23039%3B%26gt%3BCite%26lt%3B%5C%2Fa%26gt%3B%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Integration%20of%20external%20electric%20fields%20in%20molecular%20dynamics%20simulation%20models%20for%20resistive%20switching%20devices%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22T.%22%2C%22lastName%22%3A%22Gergs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22S.%22%2C%22lastName%22%3A%22Dirkmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22T.%22%2C%22lastName%22%3A%22Mussenbrock%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222018-06-28%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1063%5C%2F1.5029877%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Faip.scitation.org%5C%2Fdoi%5C%2F10.1063%5C%2F1.5029877%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220021-8979%2C%201089-7550%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222021-07-18T04%3A45%3A46Z%22%7D%7D%5D%7D<\/span>\n\n\t\t\t\t
\n
\n
Adejube, B., Gronenberg, O., Steel, J., Mallinson, J., Gergs<\/strong>, T., Protsak, M., Tjardts, T., Hemke, T., Nikitin, D., Veziroglu, S., Sch\u00fcrmann, U., Strunskus, T., Choukourov, A., Mussenbrock, T., Trieschmann, J., Kienle, L., Faupel, F., Brown, S. A., & Vahl, A. (2025). Silver-Based Self-Organized Resistive Switching Nanoparticle Networks with Neural-Like Spiking Behavior: Implications for Neuromorphic Computing. ACS Applied Nano Materials<\/i>, 8<\/i>(34), 16680\u201316693. https:\/\/doi.org\/10.1021\/acsanm.5c02520<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Yarragolla, S., Hemke, T., Jalled, F., Gergs<\/strong>, T., Trieschmann, J., Arul, T., & Mussenbrock, T. (2024). Identifying and understanding the nonlinear behavior of memristive devices. Scientific Reports<\/i>, 14<\/i>(1), 31633. https:\/\/doi.org\/10.1038\/s41598-024-80568-y<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Trieschmann, J., Vialetto, L., & Gergs<\/strong>, T. (2023). Review: Machine learning for advancing low-temperature plasma modeling and simulation. Journal of Micro\/Nanopatterning, Materials, and Metrology<\/i>, 22<\/i>(04). https:\/\/doi.org\/10.1117\/1.JMM.22.4.041504<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
De Los Arcos, T., Awakowicz, P., B\u00f6ke, M., Boysen, N., Brinkmann, R. P., Dahlmann, R., Devi, A., Eremin, D., Franke, J., Gergs<\/strong>, T., Jenderny, J., Kemaneci, E., K\u00fchne, T. D., Kusmierz, S., Mussenbrock, T., Rubner, J., Trieschmann, J., Wessling, M., Xie, X., \u2026 Grundmeier, G. (2023). PECVD and PEALD on polymer substrates (part II): Understanding and tuning of barrier and membrane properties of thin films. Plasma Processes and Polymers<\/i>, e2300186. https:\/\/doi.org\/10.1002\/ppap.202300186<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
De Los Arcos, T., Awakowicz, P., Benedikt, J., Biskup, B., B\u00f6ke, M., Boysen, N., Buschhaus, R., Dahlmann, R., Devi, A., Gergs<\/strong>, T., Jenderny, J., Von Keudell, A., K\u00fchne, T. D., Kusmierz, S., M\u00fcller, H., Mussenbrock, T., Trieschmann, J., Zanders, D., Zysk, F., & Grundmeier, G. (2023). PECVD and PEALD on polymer substrates (part I): Fundamentals and analysis of plasma activation and thin film growth. Plasma Processes and Polymers<\/i>, e2300150. https:\/\/doi.org\/10.1002\/ppap.202300150<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Mussenbrock, T., & Trieschmann, J. (2023). Physics-separating artificial neural networks for predicting sputtering and thin film deposition of AlN in Ar\/N 2<\/sub> discharges on experimental timescales. Journal of Physics D: Applied Physics<\/i>, 56<\/i>(19), 194001. https:\/\/doi.org\/10.1088\/1361-6463\/acc07e<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Mussenbrock, T., & Trieschmann, J. (2023). Physics-separating artificial neural networks for predicting initial stages of Al sputtering and thin film deposition in Ar plasma discharges. Journal of Physics D: Applied Physics<\/i>, 56<\/i>(8), 084003. https:\/\/doi.org\/10.1088\/1361-6463\/acb6a4<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Mussenbrock, T., & Trieschmann, J. (2023). Charge-optimized many-body interaction potential for AlN revisited to explore plasma\u2013surface interactions. Scientific Reports<\/i>, 13<\/i>, 5287. https:\/\/doi.org\/https:\/\/doi.org\/10.1038\/s41598-023-31862-8<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Mussenbrock, T., & Trieschmann, J. (2022). Molecular dynamics study on the role of Ar ions in the sputter deposition of Al thin films. Journal of Applied Physics<\/i>, 132<\/i>(6), 063302. https:\/\/doi.org\/10.1063\/5.0098040<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Monti, C., Gaiser, S., Amberg, M., Sch\u00fctz, U., Mussenbrock, T., Trieschmann, J., Heuberger, M., & Hegemann, D. (2022). Nanoporous SiOx plasma polymer films as carrier for liquid\u2010infused surfaces. Plasma Processes and Polymers<\/i>, 19<\/i>(8), 2200049. https:\/\/doi.org\/10.1002\/ppap.202200049<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Borislavov, B., & Trieschmann, J. (2022). Efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks. Journal of Vacuum Science & Technology B<\/i>, 40<\/i>(1), 012802. https:\/\/doi.org\/10.1116\/6.0001485<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Schmidt, F., Mussenbrock, T., & Trieschmann, J. (2021). Generalized Method for Charge-Transfer Equilibration in Reactive Molecular Dynamics. Journal of Chemical Theory and Computation<\/i>, 17<\/i>(11), 6691\u20136704. https:\/\/doi.org\/10.1021\/acs.jctc.1c00382<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Schmidt, F., Trieschmann, J., Gergs<\/strong>, T., & Mussenbrock, T. (2019). A generic method for equipping arbitrary rf discharge simulation frameworks with external lumped element circuits. Journal of Applied Physics<\/i>, 125<\/i>(17), 173106. https:\/\/doi.org\/10.1063\/1.5091965<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Kr\u00fcger, F., Gergs<\/strong>, T., & Trieschmann, J. (2019). Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations. Plasma Sources Science and Technology<\/i>, 28<\/i>(3), 035002. https:\/\/doi.org\/10.1088\/1361-6595\/ab0246<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\t\t\t\t
\n
\n
Gergs<\/strong>, T., Dirkmann, S., & Mussenbrock, T. (2018). Integration of external electric fields in molecular dynamics simulation models for resistive switching devices. Journal of Applied Physics<\/i>, 123<\/i>(24), 245301. https:\/\/doi.org\/10.1063\/1.5029877<\/a> Cite<\/a> <\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>","protected":false},"excerpt":{"rendered":"

Senior Researcher AddressRuhr-Uni\u00adver\u00adsi\u00adt\u00e4t Bo\u00adchumFakult\u00e4t f\u00fcr Elektrotechnik und InformationstechnikAngewandte Elektrodynamik und PlasmatechnikUni\u00adver\u00adsi\u00adt\u00e4ts\u00adstra\u00ad\u00dfe 150D-44801 Bo\u00adchum, Germany RoomID 1\/253 Phone+49 234 32 19743 Emailgergs(at)aept.rub.de Publications<\/p>","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-383","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/pages\/383","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/comments?post=383"}],"version-history":[{"count":2,"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/pages\/383\/revisions"}],"predecessor-version":[{"id":525,"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/pages\/383\/revisions\/525"}],"wp:attachment":[{"href":"https:\/\/aept.blogs.ruhr-uni-bochum.de\/de\/wp-json\/wp\/v2\/media?parent=383"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}