Results 151 to 160 of about 48,362 (255)

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Sustainable removal of Acid Black 172 from wastewater using Lantana camara derived biochar insights from adsorption and statistical physics modeling. [PDF]

Sci Rep
Rahman MH, Jethave G, Fegade U, Alluqmani AE, Martuza MA, Haque ME, Shatnawi Z, Al-Shayeb AF, Islam MK, Arifuzzaman M.   +9 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

More protein-ligand data are needed for AlphaFold-like models to enable drug discovery. [PDF]

Curr Opin Struct Biol
Singh S, Clerkin AB, Castellanos MA, Chodera JD.   +3 more
europepmc   +1 more source

GEO-SPATIAL IMAGERY AMD POPULAR PHYSICS

GEO-SPATIAL IMAGERY AMD POPULAR PHYSICS
P(論文) This paper is concerned with the ways in which geo-spatial imagery functions in the presentation of modern physics to the general reader. Focusing on metaphorical descriptions of the experiences of both specialists and non-specialists in approaching the subject, it points to a disjunction between the images commonly used within works of popular ...
openaire  

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Combinatorial optimization enhanced by shallow quantum circuits with 104 superconducting qubits. [PDF]

Natl Sci Rev
Zhu X, Zou Z, Jin F, Mosharev P, Luo M, Wu Y, Chen J, Zhang C, Gao Y, Wang N, Zou Y, Zhang A, Shen F, Bao Z, Zhu Z, Zhong J, Cui Z, Han Y, He Y, Wang H, Yang JN, Wang Y, Shen J, Liu G, Song Z, Deng J, Dong H, Zhang P, Song C, Wang Z, Li H, Guo Q, Yung MH, Wang H.   +33 more
europepmc   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

A physics-guided temporal convolutional learning with XGBoost integration for degradation-aware and robust electric vehicle range prediction. [PDF]

Sci Rep
Esakkiappan K, Gowtham P, Ammal VBSA, Shalini D, Mariprasath T, Al Bustanji S, Bereznychenko V.   +6 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source