TECHNOLOGY LICENSING OPPORTUNITY: AmineBind ML
Special Notice from Department of Energy.
Data as of Oct 24, 2026. Sources: SAM.gov and Grants.gov. Snapshot govcon-directory-20261024T104923Z-2151694.
This product uses the Grants.gov API but is not endorsed or certified by the U.S. Department of Health and Human Services. Counts and totals are computed by DSE from public SAM.gov and Grants.gov notices. Text from Grants.gov may be shortened or have contact details removed. The original notice on Grants.gov is the authoritative version.
Closing in 129 days
Notice details
- Agency
- Department of Energy
- Sub-tier agency
- ENERGY, DEPARTMENT OF
- Notice type
- Special Notice
- Solicitation number
- S-196258
- Product/service code
- AJ12
- Place of performance
- Los Alamos, New Mexico
- Posted
- Sep 2, 2026
- Response deadline
- Mar 2, 2027
- Source
- SAM.gov
Description
A descriptor?based software and model for amine-based carbon capture discovery Organizations that design sorbents for removing CO2 from air gain a fast, chemistry?aware way to rank candidates and focus resources on the most promising structures. AmineBind ML, a trained surrogate model, packaged with user?friendly software, predicts CO2 binding energies for amine active sites from simple molecular inputs. Teams can screen vast chemical spaces in minutes, align material choices with target regeneration temperatures and reduce trial?and?error in lab campaigns. Overview Developed by Los Alamos National Laboratory, the software ingests a chemical structure as a SMILES string, identifies amine binding sites, then uses a descriptor?based machine learning surrogate model trained on roughly 20,000 electronic?structure calculations to predict CO2 binding energetics. Inference runs far faster than density functional theory, which enables high?throughput exploration of millions of candidate chemistries for direct air capture. Predictions at the atomic scale can be combined with mesoscale modeling to feed broader materials pipelines. Technology Description AmineBind ML includes a Python?based toolkit that parses molecular inputs in SMILES format, computes chemically meaningful descriptors for amine sites, and applies a trained model to estimate CO2 binding energies. Training data come from binding energetics computed for ~20,000 molecules, anchoring predictions to first?principles
Summarized from the official notice. The description is shortened; read the full text on the official notice.
Official notice
Requirements and amendments are controlled by the official notice.
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See DSE GovCon plans →Prior awards (USAspending)
Department of Energy obligated $327,577,822 under NAICS 541715 on awards whose period of performance started in the last 12 months.
Source: USAspending.gov, U.S. Department of Treasury, Bureau of the Fiscal Service, https://www.usaspending.gov. Accessed Oct 24, 2026. Award totals are computed by DSE from USAspending.gov award data.
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Set up free alerts →Frequently asked questions
When is the response deadline?
The published deadline is Mar 2, 2027. That is 129 days after the data date.
What NAICS code applies?
NAICS 541715, Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology).
Which agency issued this notice?
Department of Energy.
Where is the official notice?
The link under Official notice opens the source listing.