Results 211 to 220 of about 3,006,412 (323)

The efficiency of the manufacturing of chemical products through the overall industrial metabolism [PDF]

, 2010
Dewulf, Jo, Kang, Wang, Van der Vorst, Geert, Van Langenhove, Herman   +3 more
core  

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

How Does Transcription-Associated Mutagenesis Shape tRNA Microevolution? [PDF]

Genome Biol Evol
Baños H, Wang L, Simonti C, Paaby AB, Heitsch C.   +4 more
europepmc   +1 more source

Solid–liquid equilibria in the LiOH–ethanol–water system: Solubility measurements and thermodynamic modeling

AIChE Journal, EarlyView.
Abstract The demand for LiOH is driven by the growth of the electric vehicle industry. Evaporative crystallization of LiOH·H2O is energy intensive, whereas ethanol‐based antisolvent crystallization has emerged as a more sustainable alternative. From a process design perspective, the crystallization yield depends on the ethanol dosage, and thermodynamic
Xiaoqi Xu, Chentao He, Janet A. W. Elliott, Liuyin Xia   +3 more
wiley   +1 more source

Thermodynamic and exergoeconomic analysis of a solar-assisted LiBr/H₂O ejector-absorption refrigeration system with triple-layer thermal storage. [PDF]

Sci Rep
Chammam A, Abbood RS, Majid SH, Sapaev IB, Arunkumar DT, Mishra A, Singh R, Mahapatro A, Alayi R.   +8 more
europepmc   +1 more source

Asking the 5 W's for designing next‐generation bioprocessing

AIChE Journal, EarlyView.
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook, Karoline Maria Vieira Nogueira, Raj Sukumar, Jenna Miller, Hal S. Alper   +4 more
wiley   +1 more source

Interfacial Stability and Design Strategies for Halide Solid Electrolytes in High-Voltage All-Solid-State Sodium-Ion Batteries. [PDF]

Small Methods
Jang M, Kwon E, Jeon C, Kim S, Yu S.
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

Equivariant diffusion solution for inorganic crystal structure determination from powder X-ray diffraction data. [PDF]

Nat Commun
Yu D, Zhu Z, Leng F, Zhu Y.
europepmc   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source