Results 231 to 240 of about 1,043,746 (297)

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Advanced Functional Materials, EarlyView.
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam, Ouassim L'Karkouri, Danqing Liu   +2 more
wiley   +1 more source

Multidimensional maturation of antibody variable domains with machine-learning assistance. [PDF]

MAbs
Ito T, Kawada S, Nakazawa H, Murakami A, Umetsu M.   +4 more
europepmc   +1 more source

Molecularly Engineered Highly Stable Memristors with Ultra‐Low Operational Voltage: Integrating Synthetic DNA with Quasi‐2D Perovskites

Advanced Functional Materials, EarlyView.
Molecularly engineered memristors integrating Ag nanoparticle–embedded synthetic DNA with quasi‐2D halide perovskites enable ultra‐low‐operational voltage, forming‐free resistive switching, and record‐low power density. This synergistic integration of customized DNA and 2D OHP in bio‐hybrid architecture enhances charge transport, reduces variability ...
Kavya S. Keremane, Abhinav Gorthy, Luyao Zheng, Chiranth C Ravi, Haodong Wu, Jiamao Zheng, Neela H. Yennawar, Shashank Priya, Rashmi Jha, Bed Poudel   +9 more
wiley   +1 more source

Large, climate-sensitive soil carbon stocks mapped with pedology-informed machine learning in the North Pacific coastal temperate rainforest

, 2018
Gavin McNicol, Chuck Bulmer, David V. D’Amore, Paul Sanborn, Sari C. Saunders, Ian Giesbrecht, Santiago Gonzalez Arriola, Allison Bidlack, David Butman, Brian Buma   +9 more
openalex   +1 more source

The Cuttlebone Blueprint for Multifunctional Metamaterials: Design Taxonomy, Functional Decoupling, and Future Horizons

Advanced Functional Materials, EarlyView.
Cuttlebone‐inspired metamaterials exploit a septum‐wall architecture to achieve excellent mechanical and functional properties. This review classifies existing designs into direct biomimetic, honeycomb‐type, and strut‐type architectures, summarizes governing design principles, and presents a decoupled design framework for interpreting multiphysical ...
Xinwei Li, Zhendong Li
wiley   +1 more source

Machine learning models for the prediction of uterine fibroids. [PDF]

Medicine (Baltimore)
Tao JL, Wei YT, Chen JM, Liang CC, Zhang HF, Wang XN, Ning Y, Cao L, Bi B.   +8 more
europepmc   +1 more source

From Bug to Feature: Harnessing Cross‐Sensitivity for Multiparametric Luminescence Sensing

Advanced Functional Materials, EarlyView.
Cross‐sensitivity in luminescence sensing is reframed from a limitation into a resource for multiparametric detection. Using ruby microspheres as a model system, cross‐sensitivity is quantitatively assessed and exploited through linear discriminant analysis, enabling simultaneous, correction‐free pressure and temperature sensing with a single ...
Nikita Panov, Liyan Ming, Stanislav Sinogeikin, Erving Ximendes, Daniel Jaque, Riccardo Marin   +5 more
wiley   +1 more source

Interpretable Machine Learning for Survival Analysis. [PDF]

Biom J
Langbein SH, Krzyziński M, Spytek M, Baniecki H, Biecek P, Wright MN.   +5 more
europepmc   +1 more source

Metal–Organic Frameworks for Gaseous Pollutant Management: From Capture to Neutralization and Reutilization

Advanced Functional Materials, EarlyView.
This review maps how MOFs can manage hazardous gases by combining adsorption, neutralization, and reutilization, enabling sustainable air‐pollution control. Covering chemical warfare agent simulants, SO2, NOx, NH3, H2S, and volatile organic compounds, it highlights structure‐guided strategies that boost selectivity, water tolerance, and cycling ...
Yuanmeng Tian, Zeyu Tao, Kaikai Ma, Xiaoliang Wang, Bo Yu, Yiu Wan Yip, Zhijie Chen, Jin Shang, Bin Fei   +8 more
wiley   +1 more source

Machine Learning-Based Transcriptomic Diagnosis of Periodontitis. [PDF]

Int Dent J
Cheng Y, Yang H, Mo H, Xu P.
europepmc   +1 more source