Results 31 to 40 of about 60,835 (182)
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Biofuels, Bioproducts and Biorefining, EarlyView.Abstract Among the Porphyridium genus, Porphyridium marinum exhibits the highest phycoerythrin (PE) content. In this study, the metabolic trade‐off between biomass, PE, and sulfated exopolysaccharide (EPS) production was assessed under varying nitrogen and sulfur availability, light intensity, residence time, and cultivation mode.
Rosaria Tizzani +3 more
wiley +1 more source
Biotechnology and Bioengineering, EarlyView.ABSTRACT Adeno‐associated viral (AAV) vectors for gene therapy are becoming integral to modern medicine, providing therapeutic options for diseases once deemed incurable. Currently, viral vector purification is a critical bottleneck in the gene therapy industry, impacting product efficacy and safety as well as accessibility and cost to patients ...
Kelvin P. Idanwekhai +9 more
wiley +1 more source
Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges
Biotechnology and Bioengineering, EarlyView.ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz +3 more
wiley +1 more source
The Effect of Variable Na/K on the CO2 Content of Slab‐Derived Rhyolitic Melts
Geophysical Monograph Series, Page 195-208., 2020 This book is Open Access. A digital copy can be downloaded for free from Wiley Online Library.
Explores the behavior of carbon in minerals, melts, and fluids under extreme conditions
Carbon trapped in diamonds and carbonate-bearing rocks in subduction zones are examples of the continuing exchange of substantial carbon ...
Michelle Muth +2 more
wiley +2 more sources
A combinatorial approach to knot recognition
, 2015 This is a report on our ongoing research on a combinatorial approach to knot recognition, using coloring of knots by certain algebraic objects called quandles.
A Fish +14 more
core +1 more source
Carbon Energy, EarlyView.The inverted F‐type ZnWO4/In2S3 heterojunction enables efficient charge separation and retention of strong oxidative capability through interfacial electric field regulation, leading to non‐toxic degradation of contaminants for sustainable water treatment.
Yanxian Jin +9 more
wiley +1 more source
Folding Alternant and Goppa Codes with Non-Trivial Automorphism Groups [PDF]
, 2014 The main practical limitation of the McEliece public-key encryption scheme is probably the size of its key. A famous trend to overcome this issue is to focus on subclasses of alternant/Goppa codes with a non trivial automorphism group. Such codes display
de Portzamparc, Frédéric +4 more
core +2 more sources
The Canadian Journal of Chemical Engineering, EarlyView.Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source