Search Results for author: Dane Morgan

Found 8 papers, 3 papers with code

Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering -- Example of ChatGPT

no code implementations7 Mar 2023 Maciej P. Polak, Dane Morgan

Although these methods enable efficient extraction of data from large sets of research papers, they require a significant amount of up-front effort, expertise, and coding.

Prompt Engineering

Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models

no code implementations9 Feb 2023 Maciej P. Polak, Shrey Modi, Anna Latosinska, Jinming Zhang, Ching-Wen Wang, Shanonan Wang, Ayan Deep Hazra, Dane Morgan

In this paper we present a simple method of extracting materials data from full texts of research papers suitable for quickly developing modest-sized databases.

Machine learning for interpreting coherent X-ray speckle patterns

1 code implementation15 Nov 2022 Mingren Shen, Dina Sheyfer, Troy David Loeffler, Subramanian K. R. S. Sankaranarayanan, G. Brian Stephenson, Maria K. Y. Chan, Dane Morgan

Speckle patterns produced by coherent X-ray have a close relationship with the internal structure of materials but quantitative inversion of the relationship to determine structure from images is challenging.

Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs

no code implementations15 Oct 2021 Ryan Jacobs, Mingren Shen, YuHan Liu, Wei Hao, Xiaoshan Li, Ruoyu He, Jacob RC Greaves, Donglin Wang, Zeming Xie, Zitong Huang, Chao Wang, Kevin G. Field, Dane Morgan

In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional Neural Network (Mask R-CNN) model.

object-detection Object Detection +1

A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations

1 code implementation19 Aug 2021 Mingren Shen, Guanzhao Li, Dongxia Wu, Yudai Yaguchi, Jack C. Haley, Kevin G. Field, Dane Morgan

The system provides analysis of features observed in TEM including both static and dynamic properties using the YOLO-based defect detection module coupled to a geometry analysis module and a dynamic tracking module.

Defect Detection object-detection +1

Multi defect detection and analysis of electron microscopy images with deep learning

no code implementations19 Aug 2021 Mingren Shen, Guanzhao Li, Dongxia Wu, YuHan Liu, Jacob Greaves, Wei Hao, Nathaniel J. Krakauer, Leah Krudy, Jacob Perez, Varun Sreenivasan, Bryan Sanchez, Oigimer Torres, Wei Li, Kevin Field, Dane Morgan

Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis.

Defect Detection

Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation

1 code implementation29 Oct 2020 Nick Lawrence, Mingren Shen, Ruiqi Yin, Cloris Feng, Dane Morgan

The use of accurate scanning transmission electron microscopy (STEM) image simulation methods require large computation times that can make their use infeasible for the simulation of many images.

Image-to-Image Translation regression +1

Assessing Graph-based Deep Learning Models for Predicting Flash Point

no code implementations26 Feb 2020 Xiaoyu Sun, Nathaniel J. Krakauer, Alexander Politowicz, Wei-Ting Chen, Qiying Li, Zuoyi Li, Xianjia Shao, Alfred Sunaryo, Mingren Shen, James Wang, Dane Morgan

To further explore GBDL models, we collected the largest flash point dataset to date, which contains 10575 unique molecules.

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