Results 171 to 180 of about 100,121 (273)

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

NeuralVisionNet: a probabilistic neural process model for continuous visual anticipation. [PDF]

Front Comput Neurosci
He H, Chen R, Wang Y, Chen X.
europepmc   +1 more source

Silicon‐Based Anodes for Sulfide Solid‐State Batteries: Failure Mechanisms and Multiscale Design Strategies

Advanced Energy Materials, EarlyView.
Silicon anodes in sulfide SSBs face coupled electrochemo‐mechanical failure by interface instability. This review examined recent advances and proposed mitigation strategies via material‐, electrode/interface‐, and cell‐level‐ engineering. We further evaluate scalable synthesis of sulfide SEs.
Murugesan Karuppaiah, JaeWook Seo, SeEun Park, Seung Hyeok Chu, Jung Kyoo Lee   +4 more
wiley   +1 more source

Learning stable radiation boundaries for wave simulations via passive neural state-space models. [PDF]

iScience
Li A, Wang X, Wang Y, Wang S.
europepmc   +1 more source

Analyzing individual rent price ratios in eastern German agricultural land markets: A GAMLSS approach

Agribusiness, EarlyView.
Abstract This study explores the rent price ratio in agricultural land markets, crucial for evaluating market efficiency, policy needs, and farmer decision‐making. Traditionally, the analyses faced challenges due to the absence of concurrent sale and rent data for the same land, potentially leading to biased results.
Marius Michels, Cord‐Friedrich von Hobe, Miryam Sarah Merk, Thomas Kneib, Oliver Musshoff   +4 more
wiley   +1 more source

Energy optimized scheduling in wireless sensor networks (WSNs) using hybrid bio-inspired reinforcement learning approach. [PDF]

Sci Rep
Sarobin MVR, Akil S, Shalu SB, Sriyaa S, Tamizhnambi Y, HariShankar S.   +5 more
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Fast automated adjoints for spectral PDE solvers. [PDF]

Proc Natl Acad Sci U S A
Skene CS, Burns KJ.
europepmc   +1 more source

A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method

AIChE Journal, EarlyView.
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen, Y. Sterkenburgh, Y. Tang, N. G. Deen, M. W. Baltussen   +4 more
wiley   +1 more source

Comparing intercell distance and cell wall midpoint criteria for discrete global grid systems

Many diverse applications have begun to study processes and patterns at a global scale. To aid in this research, discrete global grid systems (DGGSs) are data models which enable environmental modeling, monitoring and sampling across the earth at a ...
Gregory, Matthew Jay
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