Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Bryan Sundahl"'
Autor:
Yang Ban, Bryan Sundahl, Jawad Ahmed, Crystal Barrera, S.V. Sreenivasan, Roger Bonnecaze, Meghali C. Chopra
Publikováno v:
Metrology, Inspection, and Process Control XXXVI.
Publikováno v:
Metrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV.
Semiconductor process engineers currently spend almost 10% of their time extracting critical dimensions from microscope images. Images are analyzed one by one, which is tedious, prone to human bias, time-consuming and expensive. Accurate, automated d
Publikováno v:
Advanced Etch Technology and Process Integration for Nanopatterning X.
A method for automated creation and optimization of multistep etch recipes is presented. Here we demonstrate how an automated model-based process optimization approach can cut the cost and time of recipe creation by 75% or more as compared with tradi
Publikováno v:
Advanced Etch Technology for Nanopatterning IX.
We present a model-based experimental design methodology for accelerating 3D etch optimization with demonstration on 3D NAND structures. The design and optimization of etch recipes for such 3D structures face significant challenges requiring costly a
Publikováno v:
The Journal of chemical physics. 151(23)
We report the first fully numerical approach for relativistic quantum chemical calculations applicable to molecules. The approach uses an adaptive basis of multiwavelet functions to solve the full four-component Dirac-Coulomb equation to a user-speci
Autor:
Bryan Sundahl, Robert W. Harrison, Joel Anderson, Hideo Sekino, George I. Fann, Irina Sagert, Stig Rune Jensen, Gregory Beylkin
Publikováno v:
Journal of Computational Physics: X, Vol 4, Iss, Pp-(2019)
We construct high-order derivative operators for smooth functions represented via discontinuous multiwavelet bases. The need for such operators arises in order to avoid artifacts when computing functionals involving high-order derivatives of solution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d356fd94145ed27b2571bdbeddb76e8f
https://hdl.handle.net/10037/17033
https://hdl.handle.net/10037/17033
Autor:
Zhuo-Qun Li, Haiqing Liu, Robert W. Harrison, Jinkyu Han, Gordon T. Taylor, Stanislaus S. Wong, Joerg Appenzeller, Ruiping Zhou, Lei Wang, Cherno Jaye, Bryan Sundahl, Daniel A. Fischer, Scott Thornton, Yuqi Zhu
Publikováno v:
Nanoscale. 8:15553-15570
As a model system to probe ligand-dependent charge transfer in complex composite heterostructures, we fabricated double-walled carbon nanotube (DWNT)-CdSe quantum dot (QD) composites. Whereas the average diameter of the QDs probed was kept fixed at
Publikováno v:
Computational and Theoretical Chemistry. 1175:112711
We present for the first time real-space, arbitrarily-accurate representations of the operators required for up to second-order Douglas-Kroll-Hess (DKH), a model for constructing quasi-relativistic electronic Hamiltonians. The approach can be extende
Autor:
Nicholas Vence, Takeshi Yanai, Jakob S. Kottmann, Jun Jia, M-J. Yvonne Ou, Nichols A. Romero, Álvaro Vázquez-Mayagoitia, Diego Galindo, Robert W. Harrison, Gregory Beylkin, Edward F. Valeev, George I. Fann, Junchen Pei, Yukina Yokoi, Bryan Sundahl, Justus A. Calvin, Jeff R. Hammond, Hideo Sekino, Judith Hill, Matthew G. Reuter, Jacob Fosso-Tande, Laura E. Ratcliff, William A. Shelton, Florian A. Bischoff, W. Scott Thornton, Rebecca Hartman-Baker, Adam Richie-Halford
Publikováno v:
SIAM Journal on Scientific Computing, vol 38, iss 5
Harrison, RJ; Beylkin, G; Bischoff, FA; Calvin, JA; Fann, GI; Fosso-Tande, J; et al.(2016). MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation. SIAM Journal on Scientific Computing, 38(5), S123-S142. doi: 10.1137/15M1026171. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/9hz8w8tw
Harrison, RJ; Beylkin, G; Bischoff, FA; Calvin, JA; Fann, GI; Fosso-Tande, J; et al.(2016). MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation. SIAM Journal on Scientific Computing, 38(5), S123-S142. doi: 10.1137/15M1026171. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/9hz8w8tw
MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a29778dc31f827cc21e4f8ce6b088fc0