Results 131 to 140 of about 1,754,330 (293)

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

Process‐informed co‐optimization of liquid air energy storage and data centers under off‐design thermodynamic operation

AIChE Journal, EarlyView.
Abstract The rapid growth of AI data centers (AIDCs) is intensifying stress on power systems and exposing operators to volatile electricity markets. This work develops a process‐informed co‐optimization framework that integrates liquid air energy storage (LAES) with AIDC operation. Unlike black‐box storage models, the proposed formulation captures LAES
Zhicong Fang, Xiaopo Cheng, Hui Geng, Jiaze Ma   +3 more
wiley   +1 more source

Insights into the Degradation Mechanism of Aqueous LiMn2O4–Cathode Interfaces by Computational Vibrational Spectroscopy

Angewandte Chemie, EarlyView.
LiMn2O4${\rm LiMn}_2{\rm O}_4$ is of high interest for sustainable energy storage and conversion. Its mixed‐valence Mn3+${\rm Mn}^{3+}$/Mn4+${\text{Mn}}^{4+}$ structure drives site‐specific behavior at aqueous interfaces, featuring proton‐generating Mn4+${\text{Mn}}^{4+}$ centers and electron‐rich Mn3+${\rm Mn}^{3+}$ sites that render the surrounding ...
K. Nikolas Lausch, Redouan El Haouari, Philipp Schienbein, Jörg Behler   +3 more
wiley   +2 more sources

Meyer-König and Zeller operators based on the \(q\)-integers

Journal of Numerical Analysis and Approximation Theory, 2000
Not available.
openaire   +4 more sources

Embedded Morgan Fingerprints for More Efficient Molecular Property Predictions With Machine Learning

Advanced Intelligent Discovery, EarlyView.
High dimensionality of Morgan fingerprints causes overfitting and slow training. Embedded Morgan Fingerprint (eMFP) compresses this encoding while keeping key structural information intact. Tested on five regression models across three databases for HOMO–LUMO gap prediction, eMFP outperforms standard fingerprints, training faster on large, high ...
Emilio Nuñez‐Andrade, Isaac Vidal‐Daza, Rafael Gómez‐Bombarelli, James W. Ryan, Francisco J. Martin‐Martinez   +4 more
wiley   +1 more source

PRISM, a Bidirectional NMR Foundation Model: From Peak List to Structure and Back

Angewandte Chemie, EarlyView.
Structure elucidation from NMR can consume an expert for hours or even days. PRISM addresses this with a bidirectional transformer trained on 1.19 M real experimental spectra: it translates 1H and 13C peak lists into structures with 60.1% stereo‐aware top‐1 accuracy (72.5% stereo‐unaware), and, working in reverse, predicts spectra back from structures,
Ajnabiul Hoque, Frank Glorius
wiley   +2 more sources

ALGEBRAIC INDEPENENCE OF CERTAIN FORMAL POWER SERIES (II) [PDF]

Journal of Sciences, Islamic Republic of Iran, 1992
We shall extend the results of [5] and prove that if f = Z o a x ? Z [[X]] is algebraic over Q (x), where a = 1, ƒ 1 and if ? , ? ,..., ? are p-adic integers, then 1 ? , ? ,..., ?
doaj  

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

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source