Results 151 to 160 of about 70,365 (263)
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Adaptive dynamics of diverging fitness optima. [PDF]
Duong MH, Spill F, Van Rensburg B.
europepmc +1 more source
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source
Current interest in artificial cell research underscores its potential to deepen our understanding of life's fundamental processes. This review highlights advances in bottom‐up coacervate‐based artificial cell engineering via combined integration of cellular hallmarks.
Arjan Hazegh Nikroo +3 more
wiley +2 more sources
Effective Dynamics of Local Observables for Extended Fermi Gases in the High-Density Regime. [PDF]
Fresta L, Porta M, Schlein B.
europepmc +1 more source
Autonomous AI‐Driven Design for Skin Product Formulations
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
Discrete stochastic maximal regularity. [PDF]
Evangelopoulos-Ntemiris F, Veraar M.
europepmc +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Approximation of Dirac Operators with Confining Electrostatic and Lorentz Scalar δ -Shell Potentials. [PDF]
Stelzer-Landauer C.
europepmc +1 more source
CRISPR/Cas9 has revolutionized the field of gene therapy, but delivery remains an outstanding issue. We propose a nonviral gold‐nanoparticle platform for co‐delivery of CRISPR/Cas9 ribonucleoprotein and long 2.1 kilobase dsDNA transgene constructs. This CRISPR‐AuNP is inexpensive to produce and mediate gene editing and DNA delivery in T cells and CD34+
Rachel A. Cunningham +8 more
wiley +1 more source

