Results 231 to 240 of about 1,580,709 (290)

Effects of parasitic capacitance on switching transients and thermal performance in a single-phase SiC power MOSFET inverter. [PDF]

Sci Rep
Cheng HC, Jhu WY, Liu YC, Yu CF, Chiu PK, Chang TC.   +5 more
europepmc   +1 more source

InGaP/GaAs/InGaAs Multijunction Flexible Photovoltaics With Chemical Robustness and Radiation Hardness for Unassisted Electrocatalysis and Space Applications

Advanced Energy Materials, EarlyView.
A flexible InGaP/GaAs/InGaAs triple‐junction platform encapsulated with ultrathin glass enables unassisted electrocatalysis and space applications by providing robust protection against chemically aggressive and radiation‐rich environments. This work establishes a unified III–V multijunction photovoltaic platform that bridges space photovoltaics and ...
Sukkyu Hong, Seungwan Woo, Hoki Son, Hyun‐Beom Shin, Eungbeom Yeon, Jeongeun Mo, Daehwan Jung, Ho Won Jang, Ho Kwan Kang, Sung‐Min Lee, Won Jun Choi   +10 more
wiley   +1 more source

Dielectric stacking-engineered scalable reconfigurable transistor platform for adaptive logic circuits. [PDF]

Nat Commun
Zhu P, Zhang C, Yang J, Guo YW, Huo S, Wu E, Wang F, Lin CY, Chen JH, Chu H, Liu Z, Zhao S, Li J, Li M, Lin YF, Zhang J.   +15 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

A CNTFET based process variation resilient SRAM design for stable low power and half select free operation. [PDF]

Sci Rep
Haq SU, Aminzadeh A, Darabi A, Abbasian E, Shah OA, Sreenivasulu VB.   +5 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Machine learning-assisted design of carbon nanotube edge computing circuits for monolithic epidermal systems. [PDF]

Nat Commun
Luo Z, Xiang L, Zou X, Liu J, Wang H, Ye H, Yuan Y, Zhang H, Yu X, Hu Y, Pan A.   +10 more
europepmc   +1 more source

Competing Charge Separation Pathways Govern Charge Generation in Organic Photovoltaic Blends: Insights From Transient Electron Spin Resonance

Advanced Energy Materials, EarlyView.
Transient electron spin resonance distinguishes interfacial charge‐transfer states from separated charges, revealing competing charge separation pathways in organic photovoltaic blends. The relative contributions of fast charge separation and a pathway mediated by spin‐polarized charge‐transfer states vary across different blends, with high‐efficiency ...
Jack M. S. Palmer, Claudia E. Tait
wiley   +1 more source

Research on temperature prediction method for rail transit train inverters based on spatial and timing improving Transformer. [PDF]

Sci Rep
Feng Y, Zhai Y, Wang F, Yu X, Li J, Chen X.   +5 more
europepmc   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source