Results 211 to 220 of about 8,736,056 (314)

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

open access: yesAdvanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan   +4 more
wiley   +1 more source

Clinical evaluation and regression test of a commercial deep-learning auto-segmentation model. [PDF]

open access: yesJ Appl Clin Med Phys
Barati R   +12 more
europepmc   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns   +67 more
wiley   +1 more source

FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery

open access: yesAdvanced Engineering Materials, EarlyView.
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin   +16 more
wiley   +1 more source

Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data

open access: yes
This thesis addresses a pressing issue in the realm of IoT-based fault prediction using sensor data, focusing on the crucial yet challenging aspect of explainability within deep learning models.
Mansouri, Taha
core  

Deep Learning for Deciphering the Plant Cis-Regulatory Code. [PDF]

open access: yesPlants (Basel)
Zhao Z   +8 more
europepmc   +1 more source

3D‐Printed Titanium Gyroid Scaffold Structure Integrated With Tough Hybrid Materials for Cartilage Replacement

open access: yesAdvanced Engineering Materials, EarlyView.
This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin   +12 more
wiley   +1 more source

Deep learning-based dose prediction for stereotactic prostate cancer radiotherapy with CyberKnife. [PDF]

open access: yesJ Appl Clin Med Phys
Magga H   +5 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

Position: topological deep learning is the new frontier for relational learning

open access: yes
Topological deep learning (TDL) is a rapidly evolving field that uses topological features to understand and design deep learning models. This paper posits that TDL is the new frontier for relational learning.
Nasrin, F   +21 more
core  

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