Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Priya Paulachan"'
Publikováno v:
Communications Engineering, Vol 3, Iss 1, Pp 1-12 (2024)
Abstract More than Moore technology is driving semiconductor devices towards higher complexity and further miniaturization. Device miniaturization strongly impacts failure analysis (FA), since it triggers the need for non-destructive approaches with
Externí odkaz:
https://doaj.org/article/2fe7168ed86644a8af660c49d4b1a749
Autor:
Charlotte Cui, Fereshteh Falah Chamasemani, Priya Paulachan, Rahulkumar Sinojiya, Jördis Rosc, Michael Reisinger, Peter Imrich, Walter Hartner, Roland Brunner
Publikováno v:
npj Materials Degradation, Vol 8, Iss 1, Pp 1-12 (2024)
Abstract Reliable connections of electrical components embody a crucial topic in the microelectronics and power semiconductor industry. This study utilises 3D non-destructive X-ray tomography and specifically developed machine learning (ML-) algorith
Externí odkaz:
https://doaj.org/article/d5d5581f26b646b68a52982df8d22ab3
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract The advancement in the field of 3D integration circuit technology leads to new challenges for quality assessment of interconnects such as through silicon vias (TSVs) in terms of automated and time-efficient analysis. In this paper, we develo
Externí odkaz:
https://doaj.org/article/fbe27382c2d7408eaff2c0088f98ed64
Autor:
Rahulkumar Jagdishbhai Sinojiya, Priya Paulachan, Fereshteh Falah Chamasemani, Rishi Bodlos, René Hammer, Jakub Zálešák, Michael Reisinger, Daniel Scheiber, Jozef Keckes, Lorenz Romaner, Roland Brunner
Publikováno v:
Communications Materials, Vol 4, Iss 1, Pp 1-12 (2023)
Nanocrystalline thin films fabricated by deposition often have high residual stresses, making them susceptible to defects. Here, stress distribution in tungsten-titanium nanocrystalline films are probed by experimental and simulation techniques, reve
Externí odkaz:
https://doaj.org/article/777038996dfc45748cfc7f3c2bdad25e
Autor:
Rahulkumar Sinojiya, Priya Paulachan, Fereshteh Chamasemani, Rishi Bodlos, Rene Hammer, Jakub Zalesak, Michael Reisinger, Daniel Scheiber, Jozef Keckes, Lorenz Romaner, Roland Brunner
Nanocrystalline metallic alloy thin films provide a variety of interesting properties. A disadvantage concerns their inherent instability and generation of residual stresses. Here, we present a unique framework incorporating machine learning assisted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::690e181702ccaf713b9b32b7ef695d7b
https://doi.org/10.21203/rs.3.rs-1622061/v1
https://doi.org/10.21203/rs.3.rs-1622061/v1
