Planet
Climate Change, Machine Learning and Advanced Materials
Postdoctoral Fellowships Applications Are Open


Apply by November 15, 2024 for full consideration.

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News

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Omar

Yaghi lab develops new material to dramatically improve Direct Capture of CO2

Omar Yaghi, the James and Neeltje Tretter Professor of Chemistry at UC Berkeley, and graduate student Zihui Zhou are senior author and first author respectively of a paper that will appear online on Oct. 23 in the journal Nature. UC Berkeley researchers created a highly efficient material for capturing CO2 from air...

Story

Aditi Krishnapriyan and Bingqing Cheng winners in the Toyota Research Institute’s Synthesis Advanced Research Challenge

The Synthesis Advanced Research Challenge (SARC), a multiyear, multimillion-dollar initiative by the Toyota Research Institute (TRI), has selected four winning applications to focus on the development of cutting-edge tools for predictive synthesis. BIDMaP’s Aditi Krishnapriyan and  Bingqing Chen, were one of the winners with their project: Machine Learning and Atomistic...

Omar Yaghi

Omar Yaghi Awarded Balzan Prize for 2024

Omar Yaghi, Co-director and Chief Scientist at the Bakar Institute of Digital Materials for the Planet, BIDMaP, and the James and Neeltje Tretter Professor of Chemistry, has been honored with the prestigious Balzan Prize for 2024 of Switzerland and Italy. This award recognizes Yaghi's transformative contributions to the field of...

Seminars & Events

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07
Nov
Sherry Yang

Nov. 7, 2024 - Sherry Yang: Harnessing Generative Models for Scalable Materials Discovery

Generative models are increasingly used to produce novel scientific data, including crystal structures. In this talk, I will present two methods leveraging generative models for materials discovery. First, I will talk about UniMat, a unified crystal structure representation, which enables scalable generation of high-fidelity crystal...
14
Nov
Lin

Nov. 14, 2024 - Lin Lin: Optimization and anti-symmetry in neural network variational Monte Carlo

Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small molecules, but the high cost of optimizing such wavefunctions prevents their application to larger systems. We propose the Subsampled...
21
Nov
BARTOSZ

Nov. 21, 2024 - Bartosz Grzybowski

Biography: Prof. Bartosz Grzybowski is one of the global pioneers of computational synthesis planning and applications of chemical AI in the discovery of new functional molecules and materials. He has also made fundamental contributions to the theory of chemical reaction networks, dynamic/non-equilibrium self-assembly, nanoscience, and...
05
Dec
Vini

Dec. 5, 2024 - Vinicius Mikuni

Biography: Dr. Mikuni is a NESAP for Learning Postdoctoral Fellow at NERSC. His current research focuses on machine learning development and application for experimental High Energy Physics, including Likelihood-free deep learning for detector simulation, unfolding, and anomaly detection on the search for new physics processes...

About BIDMaP

COST_EFFICIENT2x
Cost-efficient climate change

The Bakar Institute of Digital Materials for the Planet (BIDMaP) aims to speed up the development of reticular chemistry and modular structures for achieving cost-efficient, easily deployable ultra-porous metal-organic frameworks (MOFs) and covalent organic frameworks (COFs).

These programs will help limit and address the impacts of climate change and extend to downstream technologies like conversion of CO2 to clean fuels, biodegradable polymers, enzymes, and pharmaceuticals. BIDMaP brings together top computation and machine learning experts with chemistry and other physical science researchers to exploit the vast potential these reticular structures have in achieving clean air, clean energy, and clean water.

NEW_FRONTIER2x
A new frontier

MOFs are crystalline structures in which a combination of multi-metal units and organic linkers are stitched together by strong bonds to make frameworks encompassing ultra-high surface areas (up to 7,000 square meters per gram of MOF material), folded and compacted into tiny spaces.

Each of the more than 100,000 frameworks in existence can selectively attract, filter, store or release specific molecules like carbon dioxide and water, operating in different environments and with high precision.

COFs are yet another class of ultra-porous crystals made entirely from strongly bonded organic molecules with no metals; their versatility offers another frontier in applications for electronics and climate-related catalytic conversions of carbon dioxide.