Results 131 to 140 of about 27,183 (256)

Fast reactor safety [PDF]

Nature, 1979
openaire   +1 more source

Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization

AIChE Journal, EarlyView.
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son, Chan Kim, Ji Hun Pak, Hain Lee, Jong Min Lee   +4 more
wiley   +1 more source

Synthesis of functionalized polyolefins in a new continuous bench‐scale reactor apparatus

AIChE Journal, EarlyView.
Abstract In‐reactor functionalized polyolefins (FPOs), produced by molecular catalysts, are a new class of polymer materials with applications ranging from high performance adhesives to bitumen compatibilization. In this work, we disclose a procedure for the synthesis of FPOs in a new Continuous Bench‐scale Reactor Apparatus (COBRA).
Miloud Bouyahyi, Job Guzman, Travis Conant, Reggie Tennyson, Christoph Brose, Riccardo Conti, Peter Kolb, Andreas Müller   +7 more
wiley   +1 more source

Advanced Nuclear Energy Pathways for a Net-Zero World: Fuel Cycles, Reactors, and Policy Readiness. [PDF]

Glob Chall
Haggam RA, Jayabal R, S S, Ayyar M, Soudagar MEM, M S, Rajendran S, D S, Sivanraju R.   +8 more
europepmc   +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, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 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

Toward Multi(radio)metalated DNA: Enzymatic Polymerization of Metal‐Chelate‐Modified Deoxyribonucleoside Triphosphates

Angewandte Chemie, EarlyView.
This work presents the first enzymatic polymerization of defined metal‐chelator‐modified nucleotides that leverage polymerase fidelity for uniform (radio)metal loading with successful incorporation of five different metals: Ga, In, Tb, Lu, and Y.
Antonio A. W. L. Wong, François Bénard, David M. Perrin   +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

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