Results 181 to 190 of about 8,140,957 (328)

Load Distributing Metamaterials Via Discrete Optimization

Advanced Functional Materials, EarlyView.
Mechanical metamaterials are computationally optimized to homogenize transmitted forces by minimizing the spread of reaction forces. The resulting architectures transform localized loading into broader, more uniform force distributions and experimentally demonstrate robust load spreading under quasi‐static and impact loading.
Andrea Detry, Hannes Holey, Raja Zulkarnain, Roberto Guerra, Ilaria Papa, Michael Zaiser, Stefano Zapperi   +6 more
wiley   +1 more source

Parallelizable search-space decomposition for large-scale combinatorial optimization problems using quadratic unconstrained binary optimization. [PDF]

Sci Rep
Kawase E, Kikuchi S, Tamai H, Tanaka S.
europepmc   +1 more source

CO2‐to‐CO Conversion in a Gas‐Fed, Zero‐Gap, PEM Electrolyzer Enabled by Polycations and Nitrogen‐Doped Carbon‐Supported Cobalt Nanoparticles

Advanced Functional Materials, EarlyView.
A gas‐fed, zero‐gap, PEM CO2 electrolyzer is realized by incorporating PDDA+ ions onto the carbonaceous Co/N‐C electrocatalyst, with gaseous H2 and CO2 fed into the anode and cathode, respectively. Operating without an aqueous electrolyte, the system sustains a peak FECO of 65.1% at 100 mA cm−2. ABSTRACT Electrochemical carbon dioxide reduction (ECO2R)
Yuen Leong Chow, Hsi‐Wen Wu, Aimin Li, Yalou Guo, Duhong Chen, Jie Zhang, Paul A. Webley   +6 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Precision meets speed through an FPGA-based natively sparse Ising machine for combinatorial optimization. [PDF]

Nat Commun
Yao B, Ebler D, Shi X, Wang J, Zhang F, Zhang W, Sun J.   +6 more
europepmc   +1 more source

Advances in Solution‐Processed Textile Triboelectric Nanogenerators: Ink Formation, Processing Strategies, Applications, and Challenges

Advanced Functional Materials, EarlyView.
Advanced ink systems for solution‐processed textile triboelectric nanogenerators are systematically summarized, spanning conductive, tribo‐negative, and tribo‐positive layers. By connecting ink chemistry, deposition methods, and device function, the present review reveals the key governing principles of solution development and highlights practical ...
Xinlong Sun, Stephen Beeby
wiley   +1 more source

Adaptive approach heuristics for the generalized assignment problem [PDF]

The Generalized Assignment Problem consists in assigning a set of tasks to a set of agents with minimum cost. Each agent has a limited amount of a single resource and each task must be assigned to one and only one agent, requiring a certain amount of the
Helena Ramalhinho-Lourenço, Daniel Serra   +1 more
core  

Retraction: Application of enhanced benders decomposition algorithm in circular assembly line balancing problem with task splitting. [PDF]

PLoS One
PLOS One Editors.
europepmc   +1 more source

Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes

Advanced Functional Materials, EarlyView.
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu, Aditya Raghavan, Utkarsh Pratiush, Ian Mercer, Pochun Hsieh, Albert Suceava, Chih‐Yu Lee, Edgar Dimitrov, Mauricio Terrones, Ichiro Takeuchi, Venkatraman Gopalan, Jon‐Paul Maria, Sergei V. Kalinin   +12 more
wiley   +1 more source

The Quantum Optimization Benchmarking Library. [PDF]

Nat Comput Sci
Koch T, Bernal Neira DE, Chen Y, Cortiana G, Egger DJ, Heese R, Hegade NN, Gomez Cadavid A, Huang R, Itoko T, Kleinert T, Maciel Xavier P, Mohseni N, Montanez-Barrera JA, Nakano K, Nannicini G, O'Meara C, Pauckert J, Proissl M, Ramesh A, Schicker M, Shimada N, Takeori M, Valls V, Van Bulck D, Woerner S, Zoufal C.   +26 more
europepmc   +1 more source