A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, EarlyView.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Impact of Local Public Services and Taxes on Dwelling Choice within a Single Taxing Jurisdiction: A Discrete Choice Model [PDF]
Discrete choice models of household location assume local public finance variables remain the same within a given taxing jurisdiction. Thus far, no such model has tested the validity of this assumption. This study employs McFadden’s (1978, 2001) discrete
Bulent Uyar, Kenneth H. Brown
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Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Advanced Engineering Materials, EarlyView.Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates [PDF]
In discrete choice experiments respondents are generally assumed to consider all of the attributes across each of the alternatives, and to choose their most preferred.
W. George Hutchinson +2 more
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Advances in Sustainable and Wearable Textile Based Soft Robotics
Advanced Functional Materials, EarlyView.This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas +6 more
wiley +1 more source
Optimal Designs for Discrete Choice Models Via Graph Laplacians. [PDF]
J Stat Theory PractRöttger F, Kahle T, Schwabe R.
europepmc +1 more source
Modeling adoption of innovations in agriculture using discrete choice models [PDF]
This paper is concerned with the development of varieties and fertilization techniques of greenhouse tomatoes, and their spatial diffusion in the northwestern region of the Negev in Israel.
Shlomo Bekhor +2 more
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Ionic Precursors Transformed Into Vinyl Acetate Synthesis Catalyst via Reaction‐Driven Restructuring
Advanced Functional Materials, EarlyView.This work demonstrates that a simple physical mixture of Pd and Au ionic precursors, KOAc promoter, and SiO2 support can transform into a highly active vinyl acetate synthesis catalyst through reaction‐driven restructuring. The results highlight reaction‐induced restructuring as an innovative and sustainable catalyst design strategy.
Byeong Jun Cha +11 more
wiley +1 more source
A Break from the Norm? Parametric Representations of Preference Heterogeneity for Discrete Choice Models in Health. [PDF]
Med Decis MakingBuckell J +3 more
europepmc +1 more source
Individual Characteristics and Stated Preferences for Alternative Energy Sources and Propulsion Technologies in Vehicles: A Discrete Choice Analysis [PDF]
This paper empirically examines the determinants of the demand for alternative energy sources and propulsion technologies in vehicles. The data stem from a stated preference discrete choice experiment with 598 potential car buyers. In order to simulate a
Andreas Ziegler
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