Results 181 to 190 of about 1,615,597 (299)

A Log-linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm [PDF]

In this paper I present a proposal to obtain appropriate initial conditions when solving general equilibrium rational expectations models with the Parameterized Expectations Algorithm.
Javier J. Pérez
core  

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Structural Parameterized Complexity

, 2015
We revisit fixed-parameter tractability, fixed-parameter reducibility and kernelizability. The standard formulations of their definitions are enhanced for greater correctness from a structural complexity point of view.
Witteveen, Jouke E.
core  

Multiscale Modelling of the Electrocatalysis of Microenzymes: Insights Into the Performance of Microperoxidase at an Aqueous/Graphene Interface and Their Exploitation to Improve Performance

Advanced Science, EarlyView.
A novel multiscale MD/DFT framework to elucidate microenzyme adsorption and electron transfer is reported. This method reveals distinct configurations for microperoxidase‐11 on graphene and those best suited for electron transfer. Rate constants align with the limited experimental data, establishing this framework as a tool for optimizing microenzyme ...
Milan Mijajlovic, Cheng Hu, Yuhui Sun, Matthew J. Penna, Meisam V. Kiamahalleh, Wenrong Yang, Mark J. Biggs   +6 more
wiley   +1 more source

PARAMETERIZED EXPECTATIONS ALGORITHM: HOW TO SOLVE FOR LABOR EASILY [PDF]

Euler-equation methods for solving nonlinear dynamic models involve parameterizing some policy functions. We argue that in the typical macroeconomic model with valuable leisure, labor function is particularly convenient for parameterizing.
Lilia Maliar, Serguei Maliar
core  

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Emergent Spinning and Orbital Motion in Clustered Wind‐Assisted Flyers

Advanced Science, EarlyView.
Inspired by natural snowflake geometries, paper‐cut flyers exhibit geometry‐defined spinning and orbital motions during cluster formation in a wind tunnel. Collective flights of multiple paperflakes reveal dynamic clustering, fragmentation, and continuously evolving spin behaviors.
Bingnan Zhou, Rahul Chand, Fahad Ahmed Korai, Jianfeng Yang, Valtteri Savonen, Fan Liu, Qi Yang, Hao Zeng   +7 more
wiley   +1 more source

Enhanced Ionic Conductivity at the Solid Electrolyte Interphase of Oxygen‐Doped Li6PS5Cl

Advanced Science, EarlyView.
Machine‐learned molecular dynamics and machine‐learning‐based phase identification reveal the kinetically formed SEI at buried Li | Li6PS5Cl interfaces. The SEI is dominated by Li2S‐based anion‐substituted phases, while oxygen doping enhances SEI ionic conductivity.
Sojeong Yang, Sungwoo Kang, Atefeh Yadegarifard, Hyun‐Jae Lee, Nongnuch Artrith, Jung‐Hoon Lee, Byungju Lee   +6 more
wiley   +1 more source