Results 181 to 190 of about 533,021 (321)

Combining Structured Data with Domain Knowledge in Battery Materials Research: The Case of Conductive Networks

open access: yesAdvanced Engineering Materials, EarlyView.
The combination of battery product and characterization ontology (BPCO) and domain knowledge guides hypotheses development and leads to new insights into material–property relationship of battery materials. The use of “intermediate data” is introduced as a concept, and examples are shown on its use to analyze the agglomeration of carbon black and its ...
Lisa Beran   +5 more
wiley   +1 more source

Enhanced PET image reconstruction utilizing morphological filtering and MLEM algorithm

open access: yesAlexandria Engineering Journal
Positron Emission Tomography (PET) image reconstruction remains a pivotal area in PET technology, critically influencing clinical diagnostic outcomes. Addressing the need for enhanced image quality, this study introduces a novel algorithm for PET image ...
Qian He, Ke Wang
doaj  

A Low-Cost Optomechatronic Diffuse Optical Mammography System for 3D Image Reconstruction: Proof of Concept. [PDF]

open access: yesDiagnostics (Basel)
Rivera-Fernández JD   +6 more
europepmc   +1 more source

High Repetition Rate Laser‐Induced Printing of Bioink with Picosecond Pulse Durations: Optimization of the Printing Process

open access: yesAdvanced Engineering Materials, EarlyView.
This study explores the use of laser‐induced forward transfer in the picosecond regime to create in vitro biomodels. Focusing on hydrodynamics and rheology, it investigates jet dynamics through time‐resolved imaging, optimizing laser fluence, biological ink viscosity, and printing distance to precisely control the volume and location of bioink ...
Lucas Duvert   +5 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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