Wesley F. Reinhart

Pennsylvania State University

United States

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Articles (8)

Year:

2024

Year:

2024

Year:

2024

We use machine learning to characterize aggregates of a model copolymer and then predict the morphology of unseen monomer sequences. The high-throughput screening is successful in identifying sequences that self-assemble into the target structures.

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (3)

Antonia Statt

UNITED STATES

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Wenjie Li

Assistant Research Professor

Pennsylvania State University

UNITED STATES

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Rebecca Napolitano

Pennsylvania State University

UNITED STATES

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Wesley F. Reinhart

Research Interests

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Articles (8)

Crystal growth characterization of WSe2 thin film using machine learning

Design and validation of refractory alloys using machine learning, CALPHAD, and experiments

Quantitative analysis of MoS2 thin film micrographs with machine learning

Predicting aggregate morphology of sequence-defined macromolecules with recurrent neural networks

Unsupervised learning of sequence-specific aggregation behavior for a model copolymer

Crack Detection in Images of Masonry Using CNNs

Smart cities built with smart materials

Generative deep learning as a tool for inverse design of high entropy refractory alloys

Collaborators (3)

Antonia Statt

Wenjie Li

Rebecca Napolitano

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