Results 51 to 60 of about 162,787 (208)

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

Advanced 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, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Traceability of Agri‐Food Products: The Key to Conscious Trade

Agribusiness, EarlyView.
ABSTRACT Globalization and growing concerns about sustainability have led to improvements in product traceability, quality, and sustainability. Traceability contributes to environmental protection and supports sustainable development by fostering transparency in agricultural practices and encouraging the responsible use of resources.
Scarlett Queen Almeida Bispo, Fernanda Aparecida Silva, Michelle Márcia Viana Martins, Marcelo José Braga Nonnenberg, Ruan da Silva Vianna, Carla Cristina Passos Cruz   +5 more
wiley   +1 more source

Computer Vision Enables Monitoring and Kinetic Analysis of Structurally Diverse Carbon Monoxide Surrogates

Angewandte Chemie, EarlyView.
A non‐contact computer vision method enables monitoring and quantitative comparison of vessel‐specific CO release kinetics from structurally diverse surrogates in two‐chamber COware reactors, revealing that surrogate reactivity scores correlate with carbonylation reaction outcomes.
Kristin Donnachie, Ciaran Griffin, Morven L. Gray, Timothy J. D. McCabe, Marc Reid   +4 more
wiley   +2 more sources

Towards a Common Language of Infrastructure Interdependency [PDF]

, 2015
Infrastructure systems can exist interdependently with one another either by design, necessity or evolution. There is evidence that interdependencies can be the source of emergent benefits and hazards, and therefore there is value in their ...
Carhart, N., Rosenberg, G.
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Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Development of an automatic lameness detection system for dairy cattle : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Manawatu, New Zealand [PDF]

, 2016
Lameness in dairy cattle negatively effects the welfare of affected cows and is the third biggest cause of economic loss to the dairy industry in New Zealand.
Dalbeth, Aaron
core