Results 51 to 60 of about 527,546 (285)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Ultrahigh‐Linear Bio‐Inspired Janus Elastomeric Strain Sensor with High Sensitivity and Stretchability via Surface Wrinkle Engineering

Advanced Science, EarlyView.
A bio‐inspired Micro‐wrinkled Janus elastomeric flexible strain sensor mimicking wrinkled‐leaf viburnum is developed. Endowed with a synergistic sensing mechanism including wrinkle‐guided microcracks, modulus‐gradient‐driven strain division, and a parallel conductive circuit, it achieves ultra‐high linearity, sensitivity, wide strain range, and ...
Jing Lin, Ye Li, Simi Yu, Xing Cheng, Longxin Qian, Yufei Chen, Womin Li, Zhipeng Yang, Yinlei Lin, Dechao Hu, Jianyi Luo, Lan Liu   +11 more
wiley   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Harnessing Methyltransferase‐Guided Targeting for Sequence‐Specific Proximity Labeling of DNA

Angewandte Chemie, EarlyView.
A novel methyltransferase‐mediated approach leveraging rationally designed S‐adenosyl‐L‐methionine (SAM) analogues was developed to achieve sequence‐specific DNA labeling but in proximity to the natural transfer site, addressing key limitations of previously established methods, including ligand instability and methylation‐sensitive labeling.
Xiong Chen, Gang Wen, Niels Ooghe, Sergey Abakumov, Taoufik Rohand, Volker Leen, Peter Dedecker, Tanja Weil, Johan Hofkens   +8 more
wiley   +2 more sources

Éxito y fracaso en restauraciones postendodónticas individuales

Ateneo, 2020
Las restauraciones postendodónticas individuales (RPI) con sistema de poste y corona, permiten devolver la funcionalidad, estética y conservar las piezas dentales que han perdido su integridad coronal.
Johnny Fabián Torres Vicuña, Santiago Patricio Barzallo Cueva, Vicente Eduardo Espinosa Granda   +2 more
doaj  

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Photocatalytic Cross‐Coupling of Phenols and Heteroaryl Halides With Machine Learning‐Guided Reaction Prediction

Angewandte Chemie, EarlyView.
Photocatalytic cross‐coupling: A redox‐neutral photochemical method enables direct C(sp2)─C(sp2) bond formation between phenols and heteroaryl halides using an organic dye and base. Complementary radical generation allows efficient cross‐coupling in up to 91% yield. Mechanistic studies, DFT, HTE, and machine learning rationalize and predict reactivity,
Matthew C. Carson, Alice Wu, Kalyana B. Duggal, Madeline E. Rotella, Marisa C. Kozlowski   +4 more
wiley   +2 more sources

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

Intraocular lens power calculation using total keratometry and ray tracing in eyes with previous small incision lenticule extraction – A case series

American Journal of Ophthalmology Case Reports
Purpose: To assess the IOL power calculation accuracy in post-SMILE eyes using ray tracing and a range of total keratometry based IOL calculation formulae. Observations: Ray tracing showed excellent predictability in IOL power calculation after SMILE and
Roman Lischke, Rainer Wiltfang, Martin Bechmann, Thomas C. Kreutzer, Siegfried G. Priglinger, M. Dirisamer, Nikolaus Luft   +6 more
doaj   +1 more source

A market model for stochastic smile: a conditional density approach [PDF]

, 2005
The purpose of this paper is to introduce a new approach that allows to construct no-arbitrage market models of for implied volatility surfaces (in other words, stochastic smile models).
Zilber, A.
core   +2 more sources