Results 151 to 160 of about 1,208,874 (255)

Stretchable h‐BN/TPU Fibers for Passive‐Active Dual‐Mode Thermal Management and Wearable Haptic Interfaces

Advanced Science, EarlyView.
Optimized 30 wt.% h‐BN/TPU fibers create a thermal conductivity of 2.08 W·m−1·K−1 while retaining mechanical compliance (422% elongation at break). Woven fabrics reduce surface temperature by 5.7°C under simulated solar irradiation. Glove integration enables localized fingertip heating at 29.55°C·s−1 with a thermal relaxation time of approximately 20 s.
Yiwei Zhou, Shanshan Long, Bo Chen, Maohua Li, Linhong Li, Yue Qin, Rongjie Yang, Hanxi Chen, Cheng‐Te Lin, Yixiang Xu, Kean How Cheah, Nan Jiang, Jinhong Yu   +12 more
wiley   +1 more source

Beyond random variation: Monte Carlo analysis and predictability of COPD exacerbations. [PDF]

ERJ Open Res
Bhatt SP, Bodduluri S, Tlimat A, Nakhmani A, Sadatsafavi M.   +4 more
europepmc   +1 more source

LLM‐Assisted Design of Ultralow‐κ$\kappa$ Chalcogenides

Advanced Science, EarlyView.
An AI assisted, physics guided workflow accelerates the discovery of ultralow thermal conductivity materials by combining Bayesian optimization, evidence conditioned LLM reasoning, and automated physics‐based validation. The framework uncovers dynamically stable Ag based chalcogenides with ultralow thermal conductivity and promising thermoelectric ...
Yujie Liu, Congran Jia, Yuzhou Hao, Xuejie Li, Yang Wang, Artem Oganov, Jun Sun, Xiangdong Ding, Turab Lookman, Zhibin Gao   +9 more
wiley   +1 more source

Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution. [PDF]

Stat Comput
Wu C, Pudlo P, Robert CP, Stoehr J.
europepmc   +1 more source

"Computing Densities: A Conditional Monte Carlo Estimator" [PDF]

We propose a generalized conditional Monte Carlo technique for computing densities in economic models. Global consistency and functional asymptotic normality are established under ergodicity assumptions on the simulated process.
Huiyu Li, John Stachurski, Richard Anton Braun   +2 more
core  

Hardware‐Native Gaussian Sampling With Probabilistic Ising Machines for Modern Communication Paradigms

Advanced Science, EarlyView.
Probabilistic Ising machines are introduced as hardware‐native Gaussian samplers for edge communication workloads. Tunable variance and sampling density enable accurate distributions for Falcon‐class post‐quantum signatures and diffusion‐based semantic communication.
Davi Rodrigues, Andrea Grimaldi, Deborah Volpe, Youwei Bao, Shuhan Yang, Eleonora Grassucci, Giulio Siracusano, Massimo Chiappini, Mario Carpentieri, Hyunsoo Yang, Giovanni Finocchio   +10 more
wiley   +1 more source

CeO2‐Based Electrocatalysts for the Oxygen Evolution Reaction: Design, Dynamic Mechanisms, and Electrolyte Adaptability

Advanced Science, EarlyView.
This Review shows how cerium oxide helps water‐splitting catalysts work better and last longer. It explains how CeO2 tunes electronic structure, oxygen‐vacancy behavior, and surface reconstruction, while adapting to alkaline, acidic, and seawater conditions.
Zhen Cui, Ailing Song, Zirui Cui, Manman Duanmu, Zhipeng Ma, Hao Liu, Guangjie Shao, Xinyi Tan, Guoxiu Wang, Hao Tian   +9 more
wiley   +1 more source

Kinetic Monte Carlo-Ising Machine Optimization for Atomistic Inverse Design of Solid Electrolytes. [PDF]

J Phys Chem Lett
Koizumi A, Tada T, Tamura R.
europepmc   +1 more source

Magnetoelectric Multiferroics for the Next‐Generation Ultralow‐Power Electronics

Advanced Science, EarlyView.
Magnetoelectric coupling provides a unifying route from electric‐field control of magnetic order to non‐volatile MeRAM, MESO logic, and emerging antiferromagnetic and magnonic devices. By connecting switching physics with device benchmarks, material platforms, and integration strategies, distinctive technological opportunities are identified alongside ...
Yang Liu, Yunlong Sun, Hao Luo, Duoduo Zhao, Yuhan Zeng, Xuzihan Zhang, Zhewei Liu, Hao Peng, Zhijing Zhang, Jack Yang, Ji Zhang, Danyang Wang, Junjie Shi, Sean Li   +13 more
wiley   +1 more source

A Monte Carlo Potts model for solidification. [PDF]

Nat Commun
Oh SH, Lee BJ.
europepmc   +1 more source