Andrew J. Lew

553 total citations
15 papers, 438 citations indexed

About

Andrew J. Lew is a scholar working on Materials Chemistry, Biomaterials and Organic Chemistry. According to data from OpenAlex, Andrew J. Lew has authored 15 papers receiving a total of 438 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Materials Chemistry, 5 papers in Biomaterials and 3 papers in Organic Chemistry. Recurrent topics in Andrew J. Lew's work include Machine Learning in Materials Science (7 papers), Supramolecular Self-Assembly in Materials (3 papers) and Polydiacetylene-based materials and applications (3 papers). Andrew J. Lew is often cited by papers focused on Machine Learning in Materials Science (7 papers), Supramolecular Self-Assembly in Materials (3 papers) and Polydiacetylene-based materials and applications (3 papers). Andrew J. Lew collaborates with scholars based in United States, Belgium and South Korea. Andrew J. Lew's co-authors include Markus J. Buehler, Julia H. Ortony, Chi-Hua Yu, Kai Jin, Dae‐Yoon Kim, Michela Geri, Xiaobing Zuo, Guillaume Lamour, Benjamin Gilbert and Elia Beniash and has published in prestigious journals such as Advanced Materials, ACS Nano and Nature Nanotechnology.

In The Last Decade

Andrew J. Lew

14 papers receiving 426 citations

Peers

Countries citing papers authored by Andrew J. Lew

Since Specialization

Citations

This map shows the geographic impact of Andrew J. Lew's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew J. Lew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew J. Lew more than expected).

Fields of papers citing papers by Andrew J. Lew

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew J. Lew. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew J. Lew. The network helps show where Andrew J. Lew may publish in the future.

Co-authorship network of co-authors of Andrew J. Lew

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. Lew. A scholar is included among the top collaborators of Andrew J. Lew based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew J. Lew. Andrew J. Lew is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Accelerating materials recipe acquisition via LLM-mediated reinforcement learning 2025 ·MRS Advances ·Andrew J. Lew	1
2	Enhancing cross-sensor data integration through domain conversion of satellite imagery with hyperparameter optimized machine learning 2025 ·Andrew J. Lew, (unknown), Timothy Perkins, P. Corlies, (unknown), (unknown), A. Friedman, Laila S. Jeong, Robert Sundberg	0
3	Designing architected materials for mechanical compression via simulation, deep learning, and experimentation 2023 ·npj Computational Materials ·Andrew J. Lew, Kai Jin, Markus J. Buehler	39
4	Single-shot forward and inverse hierarchical architected materials design for nonlinear mechanical properties using an Attention-Diffusion model 2023 ·Materials Today ·Andrew J. Lew, Markus J. Buehler	47
5	A Molecular‐Scale Understanding of Misorientation Toughening in Corals and Seashells 2023 ·Advanced Materials ·Andrew J. Lew, Cayla A. Stifler, (unknown), (unknown), A. Schöll, (unknown), (unknown), (unknown), Philippe Compère, Davide Ruffoni, Markus J. Buehler, Benjamin Gilbert	17
6	Deep learning virtual indenter maps nanoscale hardness rapidly and non-destructively, revealing mechanism and enhancing bioinspired design 2023 ·Matter ·Andrew J. Lew, Cayla A. Stifler, (unknown), (unknown), Davide Ruffoni, Benjamin Gilbert, Markus J. Buehler	13
7	Role of the Mineral in the Self-Healing of Cracks in Human Enamel 2022 ·ACS Nano ·Andrew J. Lew, Elia Beniash, Benjamin Gilbert, Markus J. Buehler	14
8	DeepBuckle: Extracting physical behavior directly from empirical observation for a material agnostic approach to analyze and predict buckling 2022 ·Journal of the Mechanics and Physics of Solids ·Andrew J. Lew, Markus J. Buehler	13
9	Fracture at the two-dimensional limit 2022 ·MRS Bulletin ·Bo Ni, Doug Steinbach, Zhenze Yang, Andrew J. Lew, (unknown), Qiyi Fang, Markus J. Buehler, Jun Lou	14
10	Deep learning model to predict fracture mechanisms of graphene 2021 ·npj 2D Materials and Applications ·Andrew J. Lew, Chi-Hua Yu, (unknown), Markus J. Buehler	68
11	A deep learning augmented genetic algorithm approach to polycrystalline 2D material fracture discovery and design 2021 ·Applied Physics Reviews ·Andrew J. Lew, Markus J. Buehler	38
12	Self-assembly of aramid amphiphiles into ultra-stable nanoribbons and aligned nanoribbon threads 2021 ·Nature Nanotechnology ·(unknown), (unknown), Dae‐Yoon Kim, Michela Geri, Guillaume Lamour, Andrew J. Lew, Xiaobing Zuo, (unknown), Julia H. Ortony	75
13	Effects of molecular flexibility and head group repulsion on aramid amphiphile self-assembly 2021 ·Molecular Systems Design & Engineering ·(unknown), Andrew J. Lew, Dae‐Yoon Kim, (unknown), (unknown), Julia H. Ortony	5
14	Encoding and exploring latent design space of optimal material structures via a VAE-LSTM model 2021 ·Forces in Mechanics ·Andrew J. Lew, Markus J. Buehler	30
15	Beyond Covalent Crosslinks: Applications of Supramolecular Gels 2018 ·Gels ·(unknown), Andrew J. Lew, Julia H. Ortony	64

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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