Article
Engineering, Aerospace
Zilong Li, Ping He
Summary: Unsteady computational fluid dynamics (CFD) simulations are essential in aerospace engineering. Reduced-order modeling (ROM) is an efficient approach to simulate unsteady flow by decomposing the flow solutions into spatial modes and temporal coefficients. Existing ROM studies mostly focus on parametric problems, but our proposed predictive ROM approach can accelerate individual unsteady aerodynamic simulations without the need for massive offline samples.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Chemistry, Physical
Akash Shah, Amit H. Munshi, Anthony P. Nicholson, Aanand Thiyagarajan, Umberto M. Pozzoni, Walajabad S. Sampath
Summary: Atomistic modeling based on Density Functional Theory coupled with surface Green's function was used to investigate energy band alignment in cadmium selenium telluride (CdSeTe) surfaces. Results showed differences in surface geometry and band alignment features between CdSeTe and CdTe surfaces, which may help explain the lower performance of CdSeTe-only solar cells compared to CdTe-only devices.
APPLIED SURFACE SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Xi Ding, Ming Tao, Junhua Li, Mingyuan Li, Mengchao Shi, Jiashu Chen, Zhen Tang, Francis Benistant, Jie Liu
Summary: This paper proposes an efficient method using deep neural networks to model atomistic dopant migration, showing high accuracy and speed compared to traditional DFT-based methods through NEB simulations.
MATERIALS SCIENCE IN SEMICONDUCTOR PROCESSING
(2022)
Article
Chemistry, Physical
A. Arun, K. K. Minu, P. S. Sreelakshmi, Jobymol Jacob
Summary: A highly accurate analytical model for Tunnel Field Effect Transistor is proposed in this study, utilizing numerical integration to tackle the challenge of calculating tunneling generation rate. The new model shows excellent agreement with device simulations across the entire operational region.
Article
Multidisciplinary Sciences
Ju Young Kim, Juho Park, Gregory R. Holdman, Jacob T. Heiden, Shinho Kim, Victor W. Brar, Min Seok Jang
Summary: This paper presents an electrically tunable metasurface design strategy that achieves an unprecedented upper limit of 4 pi range of dynamic phase modulation by utilizing two coupled resonances, with no significant variations in optical amplitude. The proposed concept is analytically justified and numerically verified using quasi-bound states in the continuum and graphene plasmon resonances, showing a 3 pi phase modulation capacity with a uniform reflection amplitude of approximately 0.65.
NATURE COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Chen Luo, Tao Xu, Zhihao Yu, Xinran Wang, Litao Sun, Junhao Chu, Xing Wu
Summary: Layered materials offer potential solutions for insulators in 2-D electronics, but their sub-nanometer thickness and complex interface states present challenges for their study. Transmission electron microscopy is a powerful tool for analyzing their morphology, chemical composition, crystal structure, and electronic structure.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Article
Optics
Shu-Feng Lin, Philippe Gentet, Di Wang, Seung-Hyun Lee, Eun-Soo Kim, Qiong-Hua Wang
Summary: The proposed full-color holographic three-dimensional display system utilizes an angular-compensating holographic optical element to achieve a simple structure for full-color display. This system eliminates the need for additional optical elements for synthesizing full-color reconstruction, leading to enhanced system integration and miniaturization.
OPTICS AND LASERS IN ENGINEERING
(2021)
Article
Chemistry, Physical
Qiyu Zeng, Bo Chen, Shen Zhang, Dongdong Kang, Han Wang, Xiaoxiang Yu, Jiayu Dai
Summary: The coupling of excited states and ionic dynamics is crucial for materials response under extreme conditions. In this study, a method combining an electron-temperature-dependent deep neural-network potential energy surface with a hybrid atomistic-continuum approach is used to simulate the laser-driven microscopic dynamics from solid to liquid. The nonthermal effects introduced by hot electrons are found to dominate the lattice dynamics, thermodynamic pathway, and structural transformation.
NPJ COMPUTATIONAL MATERIALS
(2023)
Article
Physics, Applied
Giuseppe Lovarelli, Gaetano Calogero, Gianluca Fiori, Giuseppe Iannaccone
Summary: This article proposes a computationally effective and physically sound method for modeling electron transport in 2D van der Waals heterostructures, and applies it to two practical electronic devices.
PHYSICAL REVIEW APPLIED
(2022)
Article
Engineering, Electrical & Electronic
Paul R. Genssler, Hamza E. Barkam, Karthik Pandaram, Mohsen Imani, Hussam Amrouch
Summary: The reliability of circuit design is a major concern due to transistor aging, which is influenced by operating voltage and workload. The challenge lies in estimating close-to-the-edge guardbands for aging effects, as foundries do not disclose their confidential physics-based models. We propose a machine learning model that replicates the physics-based model without revealing confidential parameters, providing circuit designers with an accessible and efficient aging model. Our approach incorporates full switching activity to consider recovery effects, achieving a mean relative error as low as 1.7% and a speedup of up to 20 x. This work bridges the gap between foundries and circuit designers, offering a promising solution.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Polymer Science
Wesley Michaels, Yan Zhao, Jian Qin
Summary: Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is a crucial conductive polymer complex in electronic devices. Density functional theory (DFT) and molecular dynamics (MD) studies have been used to investigate nanoscale details of this system, with different density functionals (DFs) showing varying accuracy in predicting properties of the system. Studies find that reducing Hartree-Fock exchange in DFs may lead to improved predictions of certain properties of the PEDOT:PSS system.
Article
Chemistry, Physical
Chaofeng Hou, Aiqi Zhu, Mingcan Zhao, Shuai Zhang, Yanhao Ye, Yufeng Huang, Ji Xu, Wei Ge
Summary: A highly efficient atomistic simulation framework is established for studying the thermal and mechanical behaviors of microprocessor chips, which is crucial for the performance and reliability of high-end microprocessor circuits. This method can treat nanoscale factors and bridges the simulation gap between macroscopic continuous methods and microscopic quantum mechanics methods.
CHEMICAL PHYSICS LETTERS
(2022)
Article
Materials Science, Multidisciplinary
I. Chesser, R. K. Koju, A. Vellore, Y. Mishin
Summary: Atomistic computer simulations are used to investigate the atomic structure, thermal stability, and diffusion processes at the Al-Si interphase boundaries in composite materials. It is found that some stable orientation relationships observed in epitaxy experiments also exist at these interfaces. An interface-induced recrystallization mechanism can transform non-equilibrium interfaces into more stable states. Diffusion of Al and Si atoms in stable Al-Si interfaces is slower compared to diffusion in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation for the sluggish interphase boundary diffusion is proposed, involving correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.
Article
Statistics & Probability
Torsten Hothorn, Achim Zeileis
Summary: This article discusses regression models for supervised learning problems with continuous response, suggesting a more general understanding of regression models as models for conditional distributions. Quantile regression forests are highlighted among algorithms estimating conditional distributions. A novel approach based on a parametric family of distributions characterized by their transformation function is proposed, along with a dedicated transformation tree algorithm for detecting distributional changes. Prediction intervals and inference procedures are provided by the resulting predictive distributions, making them fully parametric yet very general.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2021)
Article
Mechanics
Markus J. Buehler
Summary: Dynamic fracture is a significant area of materials analysis, and a machine learning model derived from atomistic simulations can effectively describe the dynamics and key aspects of fracture. The model, trained on a small dataset, offers a rapid assessment of dynamic fracture mechanisms for complex geometries and performs well on various validation cases.
JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME
(2022)
Article
Engineering, Electrical & Electronic
Fan Chen, Hesameddin Ilatikhameneh, Yaohua Tan, Gerhard Klimeck, Rajib Rahman
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2018)
Article
Engineering, Electrical & Electronic
Hesameddin Ilatikhameneh, Tarek A. Ameen, ChinYi Chen, Gerhard Klimeck, Rajib Rahman
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2018)
Article
Chemistry, Multidisciplinary
Peng Wu, Tarek Ameen, Huairuo Zhang, Leonid A. Bendersky, Hesameddin Ilatikhameneh, Gerhard Klimeck, Rajib Rahman, Albert V. Davydov, Joerg Appenzeller
Article
Engineering, Electrical & Electronic
Tarek A. Ameen, Hesameddin Ilatikhameneh, Patrick Fay, Alan Seabaugh, Rajib Rahman, Gerhard Klimeck
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2019)
Article
Physics, Applied
Timothy B. Boykin, Prasad Sarangapani, Gerhard Klimeck
JOURNAL OF APPLIED PHYSICS
(2019)
Article
Nanoscience & Nanotechnology
Tingting Shen, Daniel Valencia, Qingxiao Wang, Kuang-Chung Wang, Michael Povolotskyi, Moon J. Kim, Gerhard Klimeck, Zhihong Chen, Joerg Appenzeller
ACS APPLIED MATERIALS & INTERFACES
(2019)
Article
Engineering, Electrical & Electronic
Yuanchen Chu, Shang-Chun Lu, Nadim Chowdhury, Michael Povolotskyi, Gerhard Klimeck, Mohamed Mohamed, Tomas Palacios
IEEE ELECTRON DEVICE LETTERS
(2019)
Article
Physics, Applied
Jana M. Meyer, Jan Scharnetzky, Matthias Berl, Werner Wegscheider, Maik Hauser, Werner Dietsche, Kuang-Chun Wang, Gerhard Klimeck, Lars Tiemann, Robert H. Blick
JOURNAL OF APPLIED PHYSICS
(2019)
Article
Chemistry, Multidisciplinary
Chin-Sheng Pang, Chin-Yi Chen, Tarek Ameen, Shengjiao Zhang, Hesameddin Ilatikhameneh, Rajib Rahman, Gerhard Klimeck, Zhihong Chen
Article
Physics, Applied
Prasad Sarangapani, Yuanchen Chu, James Charles, Gerhard Klimeck, Tillmann Kubis
PHYSICAL REVIEW APPLIED
(2019)
Article
Physics, Applied
Yuanchen Chu, Jingjing Shi, Kai Miao, Yang Zhong, Prasad Sarangapani, Timothy S. Fisher, Gerhard Klimeck, Xiulin Ruan, Tillmann Kubis
APPLIED PHYSICS LETTERS
(2019)
Article
Engineering, Electrical & Electronic
Chin-Yi Chen, Hesameddin Ilatikhameneh, Jun Z. Huang, Gerhard Klimeck, Michael Povolotskyi
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2020)
Article
Engineering, Electrical & Electronic
Chin-Yi Chen, Hsin-Ying Tseng, Hesameddin Ilatikhameneh, Tarek A. Ameen, Gerhard Klimeck, Mark J. Rodwell, Michael Povolotskyi
Summary: The design of THJ-TFETs addresses the low ON-current challenge of TFETs, but faces limitations due to fabrication challenges with respect to device dimensions and material interfaces. The performance of the original THJ-TFET design is improved by engineering the doping profile to boost resonant tunneling efficiency, resulting in better SS and ON-current. Quantum transport simulations are employed to optimize THJ-TFET design in this study, considering the complexity of devices with multiple quantum wells and material interfaces in the tunneling junction.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2021)
Article
Nanoscience & Nanotechnology
Wan Sik Hwang, Pei Zhao, Sung Geun Kim, Rusen Yan, Gerhard Klimeck, Alan Seabaugh, Susan K. Fullerton-Shirey, Huili Grace Xing, Debdeep Jena
NPJ 2D MATERIALS AND APPLICATIONS
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Gerhard Klimeck
2019 8TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO)
(2019)