Results 181 to 190 of about 2,070,201 (256)

Global photovoltaic solar panel dataset from 2019 to 2022. [PDF]

open access: yesSci Data
Li A, Liu L, Li S, Cui X, Chen X, Cao X.
europepmc   +1 more source

Sphingomonas solaris sp. nov., isolated from a solar panel in Boston, Massachusetts. [PDF]

open access: yesInt J Syst Evol Microbiol, 2020
Tanner K   +5 more
europepmc   +1 more source

Economic Impact of Sustainability in Wine Sector: A Systematic Literature Review

open access: yesAgribusiness, EarlyView.
ABSTRACT Sustainability has become a key issue in the wine sector, raising questions about its compatibility with firms' economic performance. Despite growing attention to environmental and social practices, evidence on their economic implications remains fragmented.
Valentina Di Chiara   +2 more
wiley   +1 more source

Machine learning driven many‐objective moving horizon scheduling optimization

open access: yesAIChE 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

open access: yesAIChE 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   +3 more
wiley   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

open access: yesAdvanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi   +3 more
wiley   +1 more source

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