Results 211 to 220 of about 9,610 (304)

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

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

Enhanced Performance of Optoelectronic Devices Using Metal Chalcogenide Complex Ligands‐Capped InAs/ZnSe Quantum Dots as Electron Transport Layers

Advanced Energy Materials, EarlyView.
Thin‐shell InAs/ZnSe quantum dots functionalized with metal chalcogenide ligands were employed as electron transport layers in organic optoelectronic devices, yielding optimized conduction band alignment and film morphology. Consequently, the devices achieved enhanced charge transport, a detectivity of ∼1013 Jones, and a power conversion efficiency of ...
Yonghoon Choi, Seyeong Song, Dain Choi, Jinho Shin, Yeonjeong Lee, Jaehyeong Kim, Jeongmin Son, Jin Young Kim, Jongnam Park   +8 more
wiley   +1 more source

Cost-effective single-source 25-level inverter achieving twelvefold voltage gain with redundant switching and hybrid modulation. [PDF]

Sci Rep
Hosseinpour M, Mansourizadeh H, Seifi A.
europepmc   +1 more source

A Kinetic–Energetic Bottleneck of Charge‐Transfer Injection Governs Energy Loss in Organic Solar Cells

Advanced Energy Materials, EarlyView.
Kinetic–energetic projection of time‐resolved photoluminescence reveals that charge‐transfer injection acts as a universal bottleneck in organic solar cells. A physics‐constrained Bayesian framework identifies an emergent effective CT injection rate governing the trade‐off between charge generation and nonradiative energy loss.
Rong Wang, Tobias Osterrieder, Atul Shukla, Christos L. Chochos, Vasilis G. Gregoriou, Yakun He, Hua Tang, Julian Matthias Haffner‐Schirmer, Karen Forberich, Ning Li, Thomas Heumueller, Frédéric Laquai, Jens Hauch, Safa Shoaee, Dieter Neher, Larry Lüer, Christoph J. Brabec   +16 more
wiley   +1 more source

First Demonstration of Hysteresis-Free IGZO/SnO-Based Complementary Circuits and SRAM with Long-Term Reliability Using SU-8 Passivation. [PDF]

Nano Converg
Han C, Park H, Choi Y, Choi M, Lim J, Shin H, Moon S, Shin C.   +7 more
europepmc   +1 more source

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Generic logic block based on bias-gated 2D MoS₂ transistors. [PDF]

Nat Commun
Wei X, Chen Z, Chen K, Shang J, Gao L, Jiang H, Yu H, Hong M, Zhang X, Zhang Z, Zhang Y.   +10 more
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Hybrid fuzzy logic-PI control with metaheuristic optimization for enhanced performance of high-penetration grid-connected PV systems. [PDF]

Sci Rep
Mohamed MAE, Ward SA, El-Gohary MF, Mohamed MA.   +3 more
europepmc   +1 more source