Results 121 to 130 of about 2,065,553 (347)

Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities [PDF]

Chemical Engineering and Science, 2021
Indranil Pan, L. Mason, O. Matar
semanticscholar   +1 more source

Transmembrane Activation of Catalysis and Protein Refolding in Synthetic Cells by Enzymes and Nanozymes

Advanced Functional Materials, EarlyView.
Synthetic cells are engineered herein to respond to an external chemical messenger by the activation of intracellular catalysis. The chemical messenger molecules are catalytically generated by an extracellular enzyme or a mineral surface, whereas the intracellular catalysis emerges via direct enzyme activation or via protein refolding.
Dante G. Andersen, Andreas B. Pedersen, Mireia Casanovas Montasell, Søren Moesgaard, Anja Bille Bohn, Alexander N. Zelikin   +5 more
wiley   +1 more source

Sampling Algorithms in Statistical Physics: A Guide for Statistics and Machine Learning

Statistical Science
We discuss several algorithms for sampling from unnormalized probability distributions in statistical physics, but using the language of statistics and machine learning. We provide a self-contained introduction to some key ideas and concepts of the field, before discussing three well-known problems: phase transitions in the Ising model, the melting ...
Faulkner, Michael F., Livingstone, Samuel   +1 more
openaire   +4 more sources

Machine Learning Guided Design of Nerve‐On‐A‐Chip Platforms with Promoted Neurite Outgrowth

Advanced Functional Materials, EarlyView.
Compared to labor‐intensive trial‐and‐error experimentation, a machine learning (ML)‐guided workflow, incorporating cell viability assays, data augmentation, ensemble modeling, and model interpretation, is developed to accelerate nerve‐on‐a‐chip optimization and uncover data‐driven design principles.
Tsai‐Chun Chung, Chu‐Chun Liang, Min‐Wei Huang, Tianle Chen, Joshua M. Little, Snehi Shrestha, Yi‐Chen Ethan Li, I‐Chi Lee, Po‐Yen Chen   +8 more
wiley   +1 more source

Statistical Methods in Topological Data Analysis for Complex, High-Dimensional Data [PDF]

arXiv, 2016
The utilization of statistical methods an their applications within the new field of study known as Topological Data Analysis has has tremendous potential for broadening our exploration and understanding of complex, high-dimensional data spaces. This paper provides an introductory overview of the mathematical underpinnings of Topological Data Analysis,
arxiv  

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Quantum Dots and Perovskites‐Based Physically Unclonable Functions for Binary and Ternary Keys via Optical‐to‐Electrical Conversion

Advanced Functional Materials, EarlyView.
This study investigates optoelectronic PUFs that improve on traditional optical and electrical PUFs. The absorber materials are randomly coated through spray coating, ligand exchange, and dynamic spin coating. Incident light generates wavelength‐dependent binary multikey and enhances security ternary keys, approaching near‐ideal inter‐ and intra ...
Hanseok Seo, Taesung Park, Awais Ali, Byung Ku Jung, Young Kyun Choi, Junhyeok Park, Soong Ju Oh   +6 more
wiley   +1 more source

Use of machine learning to estimate statistics of the posterior distribution in probabilistic inverse problems - an application to airborne EM data.

, 2021
Thomas Mejer Hansen, Christopher C. Finlay   +1 more
openalex   +2 more sources

Experimentally Validated Design Principles of D‐Block Transition Metal Single‐Atom Non‐Dissociative Chemisorption Solid‐State Hydrogen Storage Materials

Advanced Functional Materials, EarlyView.
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue, Chao Li, Yong Gao, Zhenglong Li, Wen‐Gang Cui, Xinqiang Wang, Guoquan Na, Xiaowei Wang, Yiyang Wan, Mingchang Zhang, Yanxia Liu, Fulai Qi, Chenchen Li, Xu Xue, Jian Miao, Jing Zhang, Xiao Han, Pan Wang, Chang Guo, Xiacui Liu, Mingxia Gao, Wenping Sun, Jian Chen, Zhenhai Xia, Hongge Pan   +24 more
wiley   +1 more source

Advanced Multipurpose Spectroscopic Nanobio‐Device for Concurrent Lab‐on‐a‐Chip Label‐Free Separation and Detection of Extracellular Vesicles as Key‐Biomarkers for Point‐of‐Care Cardiovascular Disease Diagnostics

Advanced Healthcare Materials, EarlyView.
AIMSPec‐LoC is a novel lab‐on‐a‐chip platform integrating size‐based extracellular vesicle (EVs) separation with label‐free Raman spectroscopy and AI‐powered classification via SKiNET. This high‐throughput, portable system enables real‐time, multiplexed molecular fingerprinting of EVs from biofluids, offering transformative potential for early, non ...
Emma Buchan, Jonathan James Stanley Rickard, Mark Robert Thomas, Pola Goldberg Oppenheimer   +3 more
wiley   +1 more source