Results 141 to 150 of about 61,199 (270)

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
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, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

Markov blankets, information geometry and stochastic thermodynamics. [PDF]

Philos Trans A Math Phys Eng Sci, 2020
Parr T, Da Costa L, Friston K.
europepmc   +1 more source

Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis

Advanced Intelligent Systems, EarlyView.
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang, Marco Peres, Carlo Bradac, Gil Gonçalves   +3 more
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Information thermodynamics of cellular ion pumps

Physical Review Research
The framework of bipartite stochastic thermodynamics is a powerful tool to analyze a composite system's internal thermodynamics. It has been used to study the components of different molecular machines such as ATP synthase. However, this approach has not
Julián D. Jiménez-Paz, Matthew P. Leighton, David A. Sivak   +2 more
doaj   +1 more source

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

Advanced Intelligent Systems, EarlyView.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin, Rudolf M. Füchslin, Achille Giacometti, Helmut Hauser, Marco Werner   +4 more
wiley   +1 more source

Repeating Nuclear Transients From Repeating Partial Tidal Disruption Events

Astronomische Nachrichten, EarlyView.
ABSTRACT Extragalactic nuclear transients that exhibit repeating outbursts can be modeled as the repeated dynamical interaction between bound stars and supermassive black holes (SMBHs). A subset of these transients, with recurrence timescales of months‐to‐years, have been explained as accretion flares from the repeated tidal stripping of a star by an ...
Ananya Bandopadhyay, Eric R. Coughlin, Julia Fancher, C. J. Nixon, Dheeraj R. Pasham   +4 more
wiley   +1 more source

Genetically Programmed Control of Overflow Metabolism

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Overflow metabolism is a highly undesirable phenomenon that occurs in virtually all cell factories. Although several schemes have been applied to avoid overflow metabolism, this problem remains far from being solved. In this study, a genetic sensor for detecting overflow metabolism was designed, and its substrate specificity and reversibility ...
Lærke M. Jensen, Andriy Glushchuk, Thilde P. Hjorth, Alvaro R. Lara   +3 more
wiley   +1 more source

Roles of 2D halide perovskites in 2D/3D heterojunctions for high‐performance perovskite solar cells

Bulletin of the Korean Chemical Society, EarlyView.
This review establishes a design framework for two‐dimensional (2D)/three‐dimensional (3D) perovskite heterojunctions, redefining the 2D perovskite layer as an active semiconductor component. We classify 2D structures by spacer chemistry and analyze their roles within the heterojunction.
Seungmin Lee, Oui Jin Oh, Dong Hyun Kim, Dong Hun Kang, Jun Hong Noh   +4 more
wiley   +1 more source