Results 111 to 120 of about 8,709 (260)

Design and Optimization of Specular Reflecting RIS-Aided VLCP System With Low SNR

IEEE Photonics Journal
This paper investigates the optimization of the integrated visible light communication and positioning (VLCP) system performance with the aid of specular reflecting reconfigurable intelligent surface (RIS) when the received signal is subject to low ...
Qi Wu, Jian Zhang, Rui-jie Duan, Yan-yu Zhang, Gang Xin, Dun Li   +5 more
doaj   +1 more source

Degradation Mechanism of Phosphate‐Based Li‐NASICON Conductors in Alkaline Environment

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
The presence of water in the cathode of a Li‐air battery shifts reactions to produce LiOH, creating a corrosive, alkaline environment. This study investigates the alkaline stability of the common Li‐NASICON solid‐state conductor chemistries through a systematic experimental study combined with computational modeling to understand the degradation ...
Benjamin X. Lam, Zhuohan Li, Tara P. Mishra, Gerbrand Ceder   +3 more
wiley   +1 more source

Convex Optimization for Spacecraft Attitude Alignment of Laser Link Acquisition Under Uncertainties

Aerospace
This paper addresses the critical multiple-uncertainty challenge in laser link acquisition for space gravitational wave detection missions—a key bottleneck where spacecraft attitude alignment for laser link establishment is perturbed by inherent random ...
Mengyi Guo, Peng Huang, Hongwei Yang
doaj   +1 more source

NOISY MATRIX COMPLETION: UNDERSTANDING STATISTICAL GUARANTEES FOR CONVEX RELAXATION VIA NONCONVEX OPTIMIZATION. [PDF]

SIAM J Optim, 2020
Chen Y, Chi Y, Fan J, Ma C, Yan Y.
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

Modeling the separation of water‐in‐oil emulsions in continuously fed gravity settlers using millifluidic experiments

AIChE Journal, EarlyView.
Abstract Emulsion separation remains a persistent challenge in chemical and process industries due to the metastable nature of dispersed droplets. In gravity separators, the overall separation rate is governed by the formation of a densely packed zone (DPZ) of deforming and coalescing droplets that mediates between the dispersed and continuous phases ...
Andrei Zlobin, José Esteban Andino‐Enriquez, Thomas Gouëzec, Maurice Bourrel, Enric Santanach‐Carreras, Nicolas Passade‐Boupat, Laurence Talini, François Lequeux, Pascal Panizza   +8 more
wiley   +1 more source

A Cost-Effective Electric Vehicle Intelligent Charge Scheduling Method for Commercial Smart Parking Lots Using a Simplified Convex Relaxation Technique. [PDF]

Sensors (Basel), 2020
Jawad M, Qureshi MB, Ali SM, Shabbir N, Khan MUS, Aloraini A, Nawaz R.   +6 more
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source