Data-driven design of polymer-based biomaterials: high-throughput simulation, experimentation, and machine learning

RA Patel, MA Webb - ACS Applied Bio Materials, 2023 - ACS Publications
Polymers, with the capacity to tunably alter properties and response based on manipulation
of their chemical characteristics, are attractive components in biomaterials. Nevertheless …

Applied machine learning as a driver for polymeric biomaterials design

SM McDonald, EK Augustine, Q Lanners… - Nature …, 2023 - nature.com
Polymers are ubiquitous to almost every aspect of modern society and their use in medical
products is similarly pervasive. Despite this, the diversity in commercial polymers used in …

A user's guide to machine learning for polymeric biomaterials

TA Meyer, C Ramirez, MJ Tamasi, AJ Gormley - ACS Polymers Au, 2022 - ACS Publications
The development of novel biomaterials is a challenging process, complicated by a design
space with high dimensionality. Requirements for performance in the complex biological …

Mapping biomaterial complexity by machine learning

E Ahmed, P Mulay, C Ramirez… - … Engineering Part A, 2024 - liebertpub.com
Biomaterials often have subtle properties that ultimately drive their bespoke performance.
Given this nuanced structure–function behavior, the standard scientific approach of one …

Challenges and opportunities of polymer design with machine learning and high throughput experimentation

JN Kumar, Q Li, Y Jun - Mrs Communications, 2019 - cambridge.org
In this perspective, the authors challenge the status quo of polymer innovation. The authors
first explore how research in polymer design is conducted today, which is both time …

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

EC Day, SS Chittari, MP Bogen, AS Knight - ACS Polymers Au, 2023 - ACS Publications
Synthetic polymers are highly customizable with tailored structures and functionality, yet this
versatility generates challenges in the design of advanced materials due to the size and …

[HTML][HTML] Biomaterials by design: Harnessing data for future development

K Xue, FK Wang, A Suwardi, MY Han, P Teo, P Wang… - Materials Today Bio, 2021 - Elsevier
Biomaterials is an interdisciplinary field of research to achieve desired biological responses
from new materials, regardless of material type. There have been many exciting innovations …

Integration of machine learning and coarse-grained molecular simulations for polymer materials: physical understandings and molecular design

D Nguyen, L Tao, Y Li - Frontiers in Chemistry, 2022 - frontiersin.org
In recent years, the synthesis of monomer sequence-defined polymers has expanded into
broad-spectrum applications in biomedical, chemical, and materials science fields. Pursuing …

Machine learning on a robotic platform for the design of polymer–protein hybrids

MJ Tamasi, RA Patel, CH Borca, S Kosuri… - Advanced …, 2022 - Wiley Online Library
Polymer–protein hybrids are intriguing materials that can bolster protein stability in non‐
native environments, thereby enhancing their utility in diverse medicinal, commercial, and …

Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials

S Stuart, J Watchorn, FX Gu - npj Computational Materials, 2023 - nature.com
It has proved challenging to represent the behavior of polymeric macromolecules as
machine learning features for biomaterial interaction prediction. There are several …