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


Apply by November 15, 2024 for full consideration.

News

UpdatedOmar

Chemistry will no longer be an exclusive club’: how AI is changing Omar Yaghi’s work

A new feature article explores Omar Yaghi’s pioneering efforts to integrate artificial intelligence with reticular chemistry, a field he helped establish. By harnessing AI-driven models, Yaghi and his collaborators at BIDMaP are accelerating the design and discovery of new porous materials, revolutionizing applications in clean energy, carbon capture, and water...

ET24

EarthTech2024

Emerging Science and Technology for the Planet

When: December 3 and 5th, 2024 | 9:30AM – 11:00AM
Location: Pimentel Hall 1

EarthTech2024
We are excited to announce the second annual EarthTech Symposium. Building on the
success of last year’s inaugural event, EarthTech2024 will once again bring together
experts from across campus...

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...

Seminars & Events

13
Feb
Teresa

Feb. 13, 2025 - Teresa Head-Gordon: Machine Learning and Artificial Intelligence for Chemistry (and Materials)

The size of chemical space is vast. This makes the application of the first principles of quantum mechanical and advanced statistical mechanics sampling methods to identify binding motifs, conformational equilibria, and reaction pathways extremely challenging, even when considering better physical models, algorithms, or future exascale...
20
Feb
Gabe

Feb. 20, 2025 - Gabe Gomes: Autonomous chemical research with large language models

Transformer-based large language models are making significant strides in various fields, such as natural language processing, biology, chemistry, and computer programming. Here, we show the development and capabilities of Coscientist, an artificial intelligence system that autonomously designs, plans, and performs complex experiments by incorporating large...
27
Feb
David Shih

Feb. 27, 2025 - David Shih: Shedding Light on Dark Matter with Modern Machine Learning and the Gaia Space Telescope

Dark matter is one of the greatest enduring mysteries of fundamental physics. Despite countless direct and indirect searches for dark matter, still, the only evidence we have for it is through its gravitational effects on astrophysical and cosmological scales. In this talk, I will describe...
06
Mar
Matthew

March. 6, 2025 - Matthew Sigman

Biography: Professor Sigman was born in Los Angeles, California in 1970. He received a B.S. in chemistry from Sonoma State University in 1992 before obtaining his Ph.D. at Washington State University with Professor Bruce Eaton in 1996 in organometallic chemistry. He then moved to Harvard...

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.