Results 81 to 90 of about 66,012 (265)

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

Advanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher, Katarzyna P. Sokol, Philipp Simons, Kun Joong Kim, Michael Foshey, Yunsheng Tian, Thorben Prein, Lincoln J. Miara, Elsa Olivetti, Wojciech Matusik, Jennifer L. M. Rupp   +10 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Adaptive Multiswarm Comprehensive Learning Particle Swarm Optimization

Information, 2018
Multiswarm comprehensive learning particle swarm optimization (MSCLPSO) is a multiobjective metaheuristic recently proposed by the authors. MSCLPSO uses multiple swarms of particles and externally stores elitists that are nondominated solutions found so ...
Xiang Yu, Claudio Estevez
doaj   +1 more source

Matrix factorization-based multi-objective ranking-What makes a good university?

PLoS ONE, 2023
Non-negative matrix factorization (NMF) efficiently reduces high dimensionality for many-objective ranking problems. In multi-objective optimization, as long as only three or four conflicting viewpoints are present, an optimal solution can be determined ...
János Abonyi, Ádám Ipkovich, Gyula Dörgő, Károly Héberger   +3 more
doaj   +1 more source

Finding the optimal design of a passive microfluidic mixer. [PDF]

, 2019
The ability to thoroughly mix two fluids is a fundamental need in microfluidics. While a variety of different microfluidic mixers have been designed by researchers, it remains unknown which (if any) of these mixers are optimal (that is, which designs ...
Brisk, Philip, Chen, Jin, Grover, William H, Rodgers, Victor GJ, Wang, Junchao, Zhang, Naiyin   +5 more
core   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Method of Feasible Directions with Hit-and-Run Sampling for Solving Linearly Constrained Multi-Objective Optimization Problems

Journal of Optimization, Differential Equations and Their Applications
This paper proposes an extension of Zoutendijk’s Method of Feasible Directions (MFD) for solving linearly constrained multi-objective optimization problems.
Ramdani Zoubir, Addoune Smail, Brahmi Boualem   +2 more
doaj   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Evolutionary multiobjective optimization of the multi-location transshipment problem

, 2011
We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service ...
A Pan, BW Silverman, G Tagaras, H Jonsson, H-G Beyer, Khaled Ghédira, KS Krishnan, Lamjed Ben Saïd, Nabil Belgasmi   +8 more
core   +2 more sources