Results 161 to 170 of about 28,483 (263)

Development and experimental validation of a predictive resilient framework for cyber‐physical systems

AIChE Journal, EarlyView.
Abstract Cyber‐physical process systems integrate process dynamics, control, sensing, actuation, and communication, making them vulnerable to attacks that falsify data, alter control actions, or disrupt networks and drive operations toward unsafe states.
Luyang Liu, Ritu Ranjan, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

Nickel Wall-coated Microreactors for Enhanced Sensitivity and Peak Resolution in Compound-specific Carbon and Nitrogen Isotope Analysis. [PDF]

Anal Chem
Al-Ghoul H, Elsner M.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Stirring glycopeptides away from the constraints of solid-phase synthesis misconceptions. [PDF]

Front Mol Biosci
Ben Abba Amiel D, Gilon C, Hurevich M.
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Constructing p‐d Orbital Hybridization via In Situ Generation of Bi19Br3S27/NiSx for Highly Selective Photothermal CO2 Reduction to C2H4

Angewandte Chemie, EarlyView.
An in situ crystalline/amorphous Bi19Br3S27/NiSx interface unlocks orbital hybridization‐driven CO2 conversion. Newly formed p‐d coupling reshapes the reaction pathway, promotes C─C coupling, and steers photo‐thermal CO2 reduction toward highly selective C2H4 production.
Guangmei Gan, Zhixiong Yang, Mengying Wang, Yang Shi, Yuan Li, Gaoke Zhang, Jie Wu   +6 more
wiley   +2 more sources

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Guiding Photochemical Process Intensification Through Kinetic Diagnostics

Angewandte Chemie, EarlyView.
Photochemical methodologies are typically optimized for yield, yet yield alone provides limited insight into scalability. We show that simple kinetic diagnostics identify the dominant process limitations and guide targeted engineering interventions.
Jasper H. A. Schuurmans, Prakash Chandra Tiwari, Timothy Noël   +2 more
wiley   +2 more sources

Sensitivity-informed framework for enrichment distribution in MNR for thermal performance enhancement. [PDF]

Sci Rep
Aziz U, Khan H, Hussain Z, Ullah K, Shah I, Jung DW.   +5 more
europepmc   +1 more source

Revealing Hidden Raman Signatures Through Attention‐Based Spectral Unmixing

Advanced Intelligent Systems, EarlyView.
Weak Raman signatures are recovered from background‐dominated spectra using a transformer‐based, reference‐free spectral unmixing AI framework. Self‐attention reconstructs substrate contribution directly from mixed data, enabling reliable extraction of previously inaccessible vibrational features.
Dmitriy A. Poteryayev, Pietro Novelli, Annalisa Coriolano, Riccardo Dettori, Valentina Tozzini, Fabio Beltram, Massimiliano Pontil, Antonio Rossi, Stiven Forti, Camilla Coletti   +9 more
wiley   +1 more source