Results 161 to 170 of about 41,523 (260)

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics

Advanced Electronic Materials, EarlyView.
Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim, Mabel Bartlett, Liyang Wang, Karl Bates, Mengdi He, Myungbo Kim, Carmel Majidi, Tzahi Cohen‐Karni   +7 more
wiley   +1 more source

Evaluating the Efficacy and Safety of Patient "Virtual" Self-Removal of Ureteric Stents With Extraction Strings Following Ureterorenoscopy. [PDF]

Cureus
Desai C, Sarmah P, Devarajan R.
europepmc   +1 more source

Livestock Tango: U.S. and Latin America Dance Together, but Who Will Lead?

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This study examines the competitiveness between Latin American and U.S. livestock and meat sectors. We employ a computable general equilibrium modeling framework to evaluate two scenarios: coordinated improvements in Latin American productivity, transport efficiency, and market access (Scenario I), and the minimum productivity gains required ...
Taís C. Menezes, Amanda M. Countryman, Dustin L. Pendell   +2 more
wiley   +1 more source

Evaluation and Management of Intrauterine Device (IUD) Complications in Ethiopia. [PDF]

Public Health Chall
Sium AF, Abdu AN, Prager S.
europepmc   +1 more source

Effects of Environmental and Health Information on Willingness to Pay for Local and Organic Foods in Taiwan

Agribusiness, EarlyView.
ABSTRACT Using a lab‐in‐the‐field experiment, we investigate how providing information about food miles and pesticide residue influences willingness to pay (WTP) for potatoes among 407 shoppers in Taiwan, split between a supermarket and a farmers market.
Chiu‐Lin Huang, Edward C. Jaenicke, Martina Vecchi, Sheng‐Jang Sheu   +3 more
wiley   +1 more source

A Physical Framework for Algorithmic Entropy. [PDF]

Entropy (Basel)
Edmonds J.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Reduced Density Matrix and Cumulant Approximations of Quantum Linear Response. [PDF]

J Chem Theory Comput
von Buchwald TJ, Kjellgren ER, Kongsted J, Sauer SPA, Coriani S, Ziems KM.   +5 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source