PFACTS: Faster solutions for forever chemicals
- Brandi Ransom
- Dan Sanders
- et al.
- 2024
- ACS Fall 2024
Bio
Dan Sanders received a Bachelor’s degree in Polymer Science and Engineering in 1996 and Master’s degree in Macromolecular Science in 1999, both from Case Western Reserve University (Cleveland, OH). He went on to receive his Ph.D. in Chemistry from the California Institute of Technology (Pasadena, CA) working in the lab of Prof. Robert H. Grubbs. In 2004, he joined IBM’s Almaden Research Center as a Research Staff Member and is currently, a Principal Research Staff Member and Senior Manager in charge of the Materials Discovery department at IBM Research – Almaden. As part of IBM Research’s Accelerated Discovery strategy, Dan’s organization seeks to apply informatics, simulation, Artificial Intelligence, and advanced lab automation to speed the discovery of new sustainable materials and apply these techniques to pertinent use cases of relevance for IBM and the world. Currently, his department is working on advanced battery materials and sustainable materials for semiconductor fabrication, including the development of AI-tools for the design of replacements for per- and polyfluoroalkyl substances (PFAS).
Publications
Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction
- 2023
- NeurIPS 2023
An AI-assisted Workbench for Material Discovery
- 2023
- ACS Fall 2023
Integrating Chemical Language and Physicochemical Features for Enhanced Molecular Property Prediction with Multimodal Language Models
- 2023
- KDD 2023
Toward Human-AI Co-creation to Accelerate Material Discovery
- Dmitry Zubarev
- Carlos Raoni De Alencar Mendes
- et al.
- 2022
- NeurIPS 2022
Accelerating materials discovery using artificial intelligence, high performance computing and robotics
- Edward O. Pyzer-Knapp
- Jed W. Pitera
- et al.
- 2022
- npj Computational Materials
Sample-efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
- Samuel Hoffman
- Vijil Vijil
- et al.
- 2021
- NeurIPS 2021
Meta-Reinforcement Learning as the Driver of Data Acquisition in Autonomous Polymer Discovery
- Sarath Swaminathan
- Victoria Piunova
- et al.
- 2021
- APS March Meeting 2021
Meta-Reinforcement Learning as the Driver of Data Acquisition in Autonomous Polymer Discovery
- Sarathkrishna Swaminathan
- Chinyere Agunwa
- et al.
- 2020
- MRS Fall Meeting 2020
Accessing Creativity and Institutional Knowledge of Polymer Chemists via Expert-in-the-Loop AI—Case of Acrylic Polymer Design
- Victoria Piunova
- Dmitry Zubarev
- et al.
- 2020
- MRS Fall Meeting 2020
Patents
- US
- 12135927
- US
- 12110592
- DE
- 602019024474.6
- JP
- 7361499
- US
- 11500285
- DE
- 11 2011 100 578
- DE
- 11 2015 003 339
- EP
- 3584240
- US
- 11226561
- DE
- 11 2011 100 590
Projects
Sustainable Replacements for PFAS
We're addressing the environmental and human health impact of PFAS ‘forever chemicals’ by accelerating the discovery of sustainable replacements and improved capture materials.
Accelerated Discovery of Battery Materials
Leveraging our expertise in materials science, AI, quantum and high performance computing, we're developing a more powerful, sustainable, and energy-efficient battery.
Accelerator Technologies
We're developing technological solutions to assist subject matter experts with their scientific workflows by enabling the Human-AI co-creation process.
Blog posts
Mitigating the environmental harm of PFAS ‘forever chemicals’
NewsKim MartineauAccelerating discovery for societal and economic impact
ExplainerJed Pitera, Mathias Steiner, Daniel P. Sanders, Young-Hye Na, Maxwell Giammona, Kristin Schmidt, and Tim Erdmann
Top collaborators
RF
Renato Cerqueira
Senior Manager, Knowledge-centric Systems
KS
Kristin Schmidt
Strategy Assistant for Accelerated Discovery & Vice-Chair of Physical Sciences Council
EA
Emilio Vital Brazil
Senior Research Scientist - Manager AI-Assisted Decision Making
EA
Eduardo Soares
Research Scientist