Results 151 to 160 of about 7,163,180 (311)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

GAME-THEORY IN ECONOMICS - RUBINSTEIN,A

, 1992
GAME-THEORY IN ECONOMICS - RUBINSTEIN,
Chris Doucouliagos (13067625)
core  

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

The Application of Game Theory to Forecasting Orders

Littera Scripta, 2015
The article deals with the effort to forecast the development of future sales over a period of several months. The ability to forecast is very important for a company in terms of being able to manage its working capital i.e.
Vojtěch Stehel, Marek Vochozka
doaj  

Blood Cell‐Camouflaged Liquid Metal Nanoconjugates Orchestrate Treg Depletion and STING‐Amplified Photothermal Immunity for Metastatic Triple‐Negative Breast Cancer Therapy

Advanced Science, EarlyView.
Whole‐blood biomimetic engineering transforms liquid metal nanoparticles into a tripartite immunotherapeutic platform that orchestrates regulatory T‐cell depletion, photothermal‐induced immunogenic cell death, and activation of the stimulator of interferon genes pathway.
Nina Sang, Eijiro Miyako
wiley   +1 more source

The Professor’s Dilemma: Teaching Game Theory in Principles of Agricultural Economics [PDF]

Teaching, Game Theory, Agricultural Economics, Teaching/Communication/Extension/Profession, A22, C70, Q19,
Gardner, Justin G.
core  

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Multiplexed Profiling of Individual Extracellular Vesicles Reveals Lung Cancer‐Associated Protein Signatures

Advanced Science, EarlyView.
Cygnus (Cyclic‐imaging gateway to nanovesicles underlying signature) integrates multiplexed single‐EV protein imaging with a practical analysis workflow to examine EV phenotypes at vesicle, subpopulation, and sample scales. ABSTRACT Lung cancer is frequently diagnosed after curative treatment windows have narrowed, creating a need for minimally ...
Mi Hyeon Cho, Yein Chung, Yoonjeong Choi, Baekdong Cha, Jayeon Song, Nuri Oh, Ala Jo, Thomas S. C. Ng, Hyunho Kim, Hyun‐Kyung Woo, Chang Hyun Kim, Cesar M. Castro, Miles A. Miller, Hakho Lee   +13 more
wiley   +1 more source