Special NoticePosted Sep 1, 2026·Responses due Mar 2, 2027

TECHNOLOGY LICENSING OPPORTUNITY: AmineBind ML

Energy · TRIAD - DOE CONTRACTOR

Stage
Early notice (sources sought, presolicitation or special notice)
NAICS
541715
Value
Not stated
Solicitation
S-196258
Set-aside
No Set aside used
PSC
AJ12
Place
Los Alamos, NM, USA
Contact
Satya Srinivasan (licensing@lanl.gov)
CSV Email

Capture briefs (a one-page, shareable copy of this page) are part of Pro. The CSV here holds the notice, its timeline and past awards.

Where this opportunity stands

Every notice posted under solicitation S-196258 in this department, oldest first.

Early notice
  • Sep 1, 2026 · this notice
    Special Notice
Solicitation
None posted
Award
Not yet. Typical award: Sep 22, 2026 to Nov 22, 2026, middle of the range Oct 2, 2026.
Measured from 192 past early notices at Energy, Department of that later posted an award (middle half of cases, counted from Sep 1, 2026).
Responses are due Mar 2, 2027, so an award before then is unlikely; past cases include short solicitations.

Next steps for this stage

Standard steps for the notice type; not advice about this buyer.

  • Answer the notice: this is when the requirement can still be shaped.
  • Contact the contracting officer named on the notice.
  • Check who won similar work; they are the likely bidders.

What the notice says

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 Nat… (show all)

ional 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 energetics and supporting generalization across diverse amine chemistries. Model inference achieves orders?of?magnitude speed?ups versus DFT, which enables rapid ranking and down?selection prior to expensive simulations or synthesis. This bundle supports screening of millions of structures for direct air capture, delivering candidate materials that balance strong CO2 uptake with manageable regeneration temperatures to minimize operational costs and mitigate sorbent degradation. The atomic?level predictions can integrate with mesoscale treatments, creating a robust modeling pipeline that links molecular binding energetics to process?level performance. Advantages Rapid screening of large chemical spaces from simple SMILES inputs Orders?of?magnitude faster predictions than DFT for CO2 binding energetics Better targeting of materials that balance capture strength and regeneration needs Integration with mesoscale models to support end?to?end materials workflows Software package designed for researchers in chemistry and materials science Market Applications Direct air capture (materials discovery, sorbent optimization) Specialty chemicals (amine functional design, process modeling) Computational chemistry software (screening tools, model?based decision support) Environmental services (air capture planning, emissions reduction analysis) TRL 3 Software information: T5090 U.S. Patent pending LA-UR-26-27826 LANL Tech Partnerships: Unlock the Innovative Potential Los Alamos National Laboratory offers a wide range of cutting-edge technologies and capabilities that may provide your company with a competitive edge in the market and unlock the innovative potential that can enhance, refine, and revolutionize your products. LANL�s licensing program focuses on moving inventions developed by our researchers to commercial innovations. Patented and patent pending inventions and copyrighted software are available to existing and start-up companies through exclusive and non-exclusive licensing agreements. For specific discussions, please contact licensing@lanl.gov. Note: This is not a call for external services for the development of this technology. https://www.lanl.gov/engage/collaboration/feynman-center/partner-with-us/licensing-technology m.lanl.gov/tech-search

Who won similar work

834 award notices on SAM.gov in the last 24 months. Match: Same agency (Energy), any industry: a loose match.

Loose match: same agency, any industry. Read the titles before treating these as competitors.

WinnerAwardsValueLast
DH TECHNOLOGIES, INC.16$2.8MSep 29, 2026
VALI COOPER INTERNATIONAL LLC14$37.2MAug 5, 2026
ENERGY BY NATIVE AMERICAN DESIGN CORP11$2.8MJun 2, 2026
RLH INC.11$514KSep 2, 2026
COUNTERTRADE PRODUCTS, INC.11$300KSep 24, 2026
THUNDERCAT TECHNOLOGY, LLC9$3.4MAug 13, 2026
VECTOR RESOURCE INC8$85.9MAug 3, 2026
HUGHES BROTHERS INC8$10.3MAug 20, 2026
Aantilia LLC8$504KSep 24, 2026
SOFTWARE INFORMATION RESOURCE CORP.8$82KJul 27, 2026

Value counts single-winner awards. "Shared" awards are multiple-award contracts that list every winner with the same total ceiling; that ceiling is not one company's win, so it is not added in.

Latest awards

Competitive landscape

For the 8 most frequent past winners above. Lobbying is matched by the company's exact name or exact ticker; agencies are as named on the filings.

  • 0 of these past winners lobbied Energy, Dept of since 2024 (0 filings)
  • 0 of their lobbyists list a past Energy, Dept of job
  • No corporate PAC money from them to the overseeing committees since 2024
  • 0 foreign-agent (FARA) registrations
See who and the source records with Pro

Policy around it

Bills the past winners named while lobbying this agency's issues, rules from the department, and executive orders that name the agency, last 12 months.

  • 0 bills named on the past winners' lobbying filings
  • 75 rules from the department in the last 12 months
  • 0 executive orders naming the agency in the last 12 months
See who and the source records with Pro

Market

For past winners matched exactly to a listed company. Insider trades are open-market buys and sells (Form 4) in the last 90 days, shown as facts; our own study found insiders do not reliably buy ahead of awards.

  • 0 of the past winners are listed companies
  • 0 insider buys and 0 insider sells at them in the last 90 days
See who and the source records with Pro

Sources: SAM.gov notices and award notices; Senate LDA lobbying filings; FEC filings; FARA; Federal Register; congress.gov; SEC Form 4. Every row above links to its record.

Companies are matched to tickers by exact name only. A company we could not match shows no market rows; that is a miss, not a finding.