Results 181 to 190 of about 297,742 (251)

Computational and Data‐Driven Strategies for Lignocellulosic Biomass Valorization: From Multiscale Modeling to Digitalized Biorefinery Design

Advanced Science, EarlyView.
This Review critically connects structural recalcitrance, molecular modeling, solvent and catalyst design, pyrolysis, machine learning, reactor simulation, and FAIR digital infrastructure. Emphasis is placed on experimentally validated information transfer across scales, uncertainty and applicability domains, and the recycle, durability, techno ...
Abdullahi Bello Umar, Jiaxian Zheng, Xiangfeng Lin, Hongwu Liao, Haoqian Xu, Yufei Huang, Zaharaddeen Nasiru Garba, Adamu Uzairu, Weiwei Zhao, Zhanhui Yuan   +9 more
wiley   +1 more source

Microbial diversity and component variation in Xiaguan Tuo Tea during pile fermentation v3

, 2017
Haizhou Li, Min Li, Xinrui Yang, Jiuyun Chu, Changwang He, Weitao Wang, Feng Han, Ping Li   +7 more
openaire   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

Advanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang, Nellie Laleni, Sina Ranjbar, Andreas Tsiougkos, Nandakishor Yadav, Vasilis Pavlidis, Thomas Kämpfe   +6 more
wiley   +1 more source

Fully Recyclable Printed Magnetoresistive Sensors Covering Broad Operational Ranges for Sustainable Interactive Electronics

Advanced Electronic Materials, EarlyView.
This work presents a sustainable printing and recycling strategy for magnetic sensors designed for IoT applications. By combining solvent‐orthogonal binders with tailored magnetic fillers, the sensors achieve tunable sensitivity across low to high magnetic field ranges.
Rui Xu, Guannan Mu, Shirong Huang, Sebastian Lehmann, Gianaurelio Cuniberti, Kornelius Nielsch, Denys Makarov   +6 more
wiley   +1 more source

Combined Application of a Composite Microbial Inoculant and Bulking Agents Improves Chicken Manure Composting. [PDF]

Microorganisms
Gao J, Zhao D, Zhao Y, Liu F, Zhu H, Cao Z, Wang J, Li Z, Li Z, Hu L, Li Z.   +10 more
europepmc   +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley   +1 more source

Sonocatalytic carbon dioxide reduction for syngas production over surface‐roughened CuxO catalyst

AIChE Journal, EarlyView.
Abstract The transition to a carbon‐circular economy requires efficient technologies for converting CO2 into value‐added chemical feedstocks. Sonocatalytic CO2 conversion has recently emerged as a compelling approach to drive this conversion. Here, we report a surface‐roughened CuxO catalyst for sonocatalytic CO2 reduction in aqueous media, achieving a
Dong Xia, Yi Qin, Hessan Khalid, Yagya N. Regmi, Laurie A. King, James Kwan   +5 more
wiley   +1 more source

Impact of processing techniques on chemical compositions and sensory attributes across five types of Yunnan large-leaf teas. [PDF]

Food Chem X
Dang X, Li Y, Lv Z, Lu F, Li W, Zhang Y, Shi X, Yi G, Duan H, Hou Y.   +9 more
europepmc   +1 more source

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

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source