Results 121 to 130 of about 1,389,522 (295)

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Certificate of affiliation given to Meat Cutters, Poultry and Creamery Employees by Amalgamated Meat Cutters and Butcher Workmen of North America

open access: yes, 1941
Certificate of affiliation given to Meat Cutters, Poultry and Creamery Employees by Amalgamated Meat Cutters and Butcher Workmen of North America, local union #613, Parsons, Kansas. Legible names on the document include J.W.
Amalgamated Meat Cutters and Butcher Workmen of North America
core  

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

The effect of excercise stress on the meat quality from different muscles in lamb

open access: yes
AgResearch and Meat Industry Association Meat Innovation Workshop 2022, Professor Jim Morton from Lincoln University presented during Session 4: Technologies for the Future on Wednesday, 1st June at 11:40 AM.
Lee, Hannah, Ross, A, Morton, James
core  

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

open access: yesAdvanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei   +7 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

open access: yesAdvanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung   +7 more
wiley   +1 more source

Effects of wet aging, dry bag aging, and stepwise aging methods on meat quality and sensory attributes of steaks from pasture and grain finished steers [PDF]

open access: yes
The study aimed to evaluate the effect of 2 finishing diets (F: pasture or grain) and 4 meat aging methods (AM) on physicochemical traits, microbiological loads, and sensory attributes of beef, with aging methods as follows: wet aging (WA) for 40 d; dry ...
Brito, Gustavo   +6 more
core   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

open access: yesAdvanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh   +8 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

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