Results 201 to 210 of about 248,790 (377)

ALIGNMENT OF MINISATELLITE MAPS: A MINIMUM SPANNING TREE-BASED APPROACH [PDF]

open access: green, 2007
Mohamed Abouelhoda   +3 more
openalex   +1 more source

Toward High‐Performance Electrochemical Energy Storage Systems: A Case Study on Predicting Electrochemical Properties and Inverse Material Design of MXene‐Based Electrode Materials with Automated Machine Learning (AutoML)

open access: yesAdvanced Electronic Materials, EarlyView.
This study demonstrates PyCaret's AutoML framework for predicting the electrochemical and structural properties of MXene‐based electrodes, including intercalation voltage, capacity, and lattice constants. AutoML streamlines workflows, ranks key elemental descriptor, and enables inverse molecular formula prediction based on performance targets.
Berna Alemdag   +3 more
wiley   +1 more source

Electronic Nanomaterials for Plants: A Review on Current Advances and Future Prospects

open access: yesAdvanced Electronic Materials, EarlyView.
Global food security faces mounting challenges from climate change and rapid population growth. This review highlights the pivotal role of electronic nanomaterials–including metals, metal oxides, and carbon‐based structures–in enhancing plant photosynthesis, nutrient uptake, and stress resilience. Furthermore, it explores how emerging platforms such as
Ciro Allará   +8 more
wiley   +1 more source

A polyhedral approach to the generalized minimum labeling spanning tree problem

open access: yesEURO Journal on Computational Optimization, 2019
The minimum labeling spanning tree problem (MLSTP) is a combinatorial optimization problem that consists in finding a spanning tree in a simple graph G, in which each edge has one label, by using a minimum number of labels.
ThiagoGouveiada Silva   +4 more
doaj  

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

A dandelion-encoded evolutionary algorithm for the delay-constrained capacitated minimum spanning tree problem [PDF]

open access: green, 2008
Ángel M. Pérez‐Bellido   +4 more
openalex   +1 more source

State‐of‐the‐Art Machine Learning Technology for Sustainable Lithium Battery Cathode Design: A Perspective

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning applications in Li‐ion batteries. Abstract Technology for lithium‐ion batteries (LIBs) is developing rapidly, which is essential to modern devices and renewable energy sources. The latest development focuses on the optimization of cathode materials, which is critical in determining battery performance and durability.
Adil Saleem   +3 more
wiley   +1 more source

The Haber Bosch Catalyst from Solid state Chemistry to Mesotechnology

open access: yesAdvanced Energy Materials, EarlyView.
A comprehensive, multi‐scale, multi‐modal study of the structural diversity of a technical multi‐promoted Haber Bosch catalyst for ammonia synthesis is provided. The different contributions of ammonia Fe are revealed and the presence of cement phases that have yet not been incorporated into discussions on the function of this catalyst system is shown ...
Kassiogé Dembélé   +20 more
wiley   +1 more source

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