Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) with Machine Learning Enhancement to Determine Structure of Nanoparticle Mixtures and Solutions-Reference-Cited by-同舟云学术

Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) with Machine Learning Enhancement to Determine Structure of Nanoparticle Mixtures and Solutions

Published:2022-07-01 Issue:7 Volume:8 Page:996-1007
ISSN:2374-7943
Container-title:ACS Central Science
language:en
Short-container-title:ACS Cent. Sci.

Author:

Heil Christian M.¹,Patil Anvay²,Dhinojwala Ali²^ORCID,Jayaraman Arthi¹³^ORCID

Affiliation:

1. Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States

2. School of Polymer Science and Polymer Engineering, The University of Akron, 170 University Avenue, Akron, Ohio 44325, United States

3. Department of Materials Science and Engineering, University of Delaware, 201 DuPont Hall, Newark, Delaware 19716, United States

Funder

Air Force Office of Scientific Research

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acscentsci.2c00382

Reference61 articles.

1. Directed Self-Assembly of Nanoparticles

2. Colloidal self-assembly at an interface

3. Self-assembly of nanoparticles at interfaces

4. Molecular-based design and emerging applications of nanoporous carbon spheres

5. Gadolinium Doping Enhances the Photoacoustic Signal of Synthetic Melanin Nanoparticles: A Dual Modality Contrast Agent for Stem Cell Imaging

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