Results 151 to 160 of about 64,667 (273)
Advanced Energy Materials, EarlyView.We identify two decisive levers for SAM interfaces: molecular design (carboxylic acid‐based, phosphonic acid, other anchoring chemistries, and polymeric SAMs) and mixing routes (co‐assembly, in situ assembly, pre‐ and post‐treatment). Coordinated tuning of headgroups and assembly pathways optimises energy alignment and film formation, suppresses ...
Jiaxu Zhang, Bochun Kang, Feng Yan
wiley +1 more source
Aryne Generation from Aryl Halides Via Photothermal Red-Light Activation. [PDF]
J Am Chem SocPreston-Herrera C +3 more
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Amyotrophic Lateral Sclerosis as a Multistep Process in the United States: A Population-Based Study. [PDF]
Ann Clin Transl NeurolBerry J +7 more
europepmc +1 more source
Conjugate-symplecticity of linear multistep methods
, 2008 For the numerical treatment of Hamiltonian differential equations, symplectic integrators are the most suitable choice, and methods that are conjugate to a symplectic integrator share the same good long-time behavior. This note characterises linear multistep methods whose underlying one-step method is conjugate to a symplectic integrator.
openaire +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
A fluorescent probe under the microscope showing dual recognition of B-DNA and G-quadruplex DNA. [PDF]
Commun ChemGramolini L +3 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Forecasting tuberculosis in Ethiopia using deep learning: progress toward sustainable development goal evidence from global burden of disease 1990-2021. [PDF]
BMC Infect DisTadese ZB +5 more
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
Advanced Intelligent Discovery, EarlyView.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