Using microscopic imaging and ensemble deep learning to classify the provenance of archaeological ceramics

Q Wang, X **ao, Z Liu - Scientific Reports, 2024 - nature.com
Considering the substantial inaccuracies inherent in the traditional manual identification of
ceramic categories and the issues associated with analyzing ceramics based on chemical or …

[HTML][HTML] Tailoring Laser Powder Bed Fusion Process Parameters for Standard and Off-Size Ti6Al4V Metal Powders: A Machine Learning Approach Enhanced by …

F Liravi, S Soo, S Toorandaz, K Taherkhani… - Inventions, 2024 - mdpi.com
An integral part of laser powder bed fusion (LPBF) quality control is identifying optimal
process parameters tailored to each application, often achieved through time-consuming …

SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation

Y Chen, R Al-Maskari, I Horvath, M Ali, L Höher… - arxiv preprint arxiv …, 2025 - arxiv.org
Recent innovations in light sheet microscopy, paired with developments in tissue clearing
techniques, enable the 3D imaging of large mammalian tissues with cellular resolution …

[HTML][HTML] Rapid Assessment of Stable Crystal Structures in Single-Phase High-Entropy Alloys via Graph Neural Network-Based Surrogate Modelling

N Beaver, A Dive, M Wong, K Shimanuki, A Patil… - Crystals, 2024 - mdpi.com
To develop a rapid, reliable, and cost-effective method for predicting the structure of single-
phase high-entropy alloys, a Graph Neural Network (ALIGNN-FF)-based approach was …

Development of a Materials Data Science Framework for the Analysis of Phase Transformations and Similarity in Material Systems

S Nalin Venkat - 2025 - rave.ohiolink.edu
To study the impact of properties on the performance of material systems, it is crucial to
investigate their phase transformations. Phase transformations can be monitored using …