Accelerating Intelligent Materials & Manufacturing Systems (AIM₂S)

Accelerating Intelligent Materials & Manufacturing Systems (AIM₂S) is a U.S. Department of Energy (DOE) opportunity sponsored by the Advanced Materials and Manufacturing Technologies Office (AMMTO) with the aim of integrating artificial intelligence (AI) technologies to address bottlenecks in the U.S. energy manufacturing industrial base, including supply chains, materials qualification, product quality, throughput, process consistency, cost, and adoption of new materials and processes.

Projects will address one of two technical areas:

1. AI-enabled Materials Qualification and Integration and
2. Intelligent AI Manufacturing Systems.

Approaches may include physics-informed machine learning, digital twins, automated data and sensor fusion, uncertainty-aware models, high-throughput computational or experimental workflows, real-time monitoring, adaptive process control, predictive optimization, and system-level production optimization.

Solutions must advance a defined energy-relevant material, component, process, equipment system, qualification workflow, or manufacturing outcome toward production-relevant validation and domestic integration with a clearly identified manufacturing bottleneck and end-use/application case. DOE anticipates up to $20 million in total performer funding, with expected individual awards of approximately $1.1 million to $2.2 million over up to 24 months.

EnergyWerx is compiling a Teaming Partner List^[1] to facilitate the formation of project teams for this Opportunity. The Teaming Partner List allows entities that may wish to participate in a project to express their interest to other applicants and explore potential partnerships.

• Interested entities may apply to the Teaming Partner List HERE
• The Teaming Partner List can be viewed HERE (Password is case sensitive: AIM2S) and will be updated regularly to reflect new teaming partners who provide their organization's information.

[1] DISCLAIMER: By submitting a request to be included on the Teaming Partner List, the requesting organization consents to the publication of the referenced information. By facilitating the Teaming Partner List, DOE is not endorsing, sponsoring, or otherwise evaluating the qualifications of the individuals and organizations that are identifying themselves for placement on this Teaming Partner List. DOE will not pay for the provision of any information, nor will it compensate any applicants or requesting organizations for the development of such information.

AIM₂S is organized around two complementary technical objectives:

• AI-enabled Materials Qualification and Integration: Develop AI-enabled frameworks for rapid, reliable qualification and integration of advanced materials for grid infrastructure, energy storage, and power generation systems, including gas, nuclear, hydropower, geothermal, and coal.
• Intelligent AI Manufacturing Systems: Develop, integrate, and validate AI-enabled technologies that improve equipment, process sequences, automation, production systems, and manufacturing workflows under operationally relevant conditions.

Projects are expected to mature technologies from approximately TRL 3/MRL 2 toward TRL 6/MRL 4 and show measurable progress toward a specific application-relevant outcome. AI model development in isolation is not responsive; the AI approach must materially advance qualification time, throughput, quality, yield, reliability, cost, scrap reduction, process stability, or pilot-scale readiness.

Submission Window: [MONTH] [DATE], 2026 - [MONTH] [DATE], 2026

• Start the AIM₂S Application

Applications are due no later than [MONTH] [DATE], 2026

The AIM₂S Opportunity launched on [MONTH] [DATE], 2026. Please click here for the full announcement article for more information.

Informational Webinars: DOE will present and summarize the details of the AIM₂S Opportunity. Potential applicants will gain a better understanding of the Opportunity's scope, scale, and intent and have the opportunity to ask questions of DOE staff.

• Register for the Informational Webinar on [MONTH] [DATE], 2026 at 3:00 PM ET
  
  • Focuses predominantly on explaining the Opportunity with some time for questions at the end.
• Register for the Informational Webinar on [MONTH] [DATE], 2026 at 3:00 PM ET
  
  • Focuses predominantly on explaining the Opportunity with some time for questions at the end.

For an optimal experience, we recommend downloading the Microsoft Teams software to your computer, smartphone, or tablet.

The anticipated program schedule and funding structure are:

• Maximum period of performance: Up to 24 months.
• Funding: Up to $20 million total; expected individual performer awards of approximately $1.1 million to $2.2 million.

Detailed scope, deliverables, performance metrics, and milestones will be finalized in each performer's Business-to-Business (B2B) agreement.

Submission Window: [MONTH] [DATE], 2026 - [MONTH] [DATE], 2026

• Start the AIM₂S Application

Applications are due no later than [MONTH] [DATE], 2026

Eligibility Criteria

The PIA mechanism is intended to support a broad range of performers, including startups, small businesses, established industry, universities, national laboratories, and nontraditional partners. Applicants should demonstrate, as applicable:

• A proposed AI-enabled materials or manufacturing technology at approximately TRL 3-6 and/or MRL 2-4 at the time of application.
• A credible technical basis, supported by preliminary data, prototype models, published research, prior demonstrations, relevant software tools, domain expertise, and/or access to appropriate datasets.
• A clearly defined, commercially important energy-relevant material, process, component, equipment system, qualification workflow, or manufacturing outcome.
• A quantitative validation plan, including a quantitative baseline representing current industrial practice or the relevant state-of-practice, quantitative performance, target metrics, and access to the personnel, data, equipment, facilities, partners, and validation environments needed to execute the work.
• A credible pathway toward pilot-scale demonstration, commercial adoption, or integration into domestic energy manufacturing supply chains.
• Risk-based cybersecurity, data-governance, access-control, and sensitive technical information protections appropriate to the project.
• Where applicable, approaches should address interoperability with existing manufacturing equipment, data systems, digital-thread architectures, and relevant industry standards.
• Qualification as a domestic entity and certification that the applicant is not owned by, controlled by, or subject to the jurisdiction or direction of a government of a Foreign Country of Concern.
• Compliance with DOE restrictions on participation in Malign Foreign Talent Recruitment Programs, including ongoing due diligence and required notification.
• Applicable DOE Research, Technology and Economic Security due-diligence and disclosure requirements, including Transparency of Foreign Connections and DOE-compliant biosketch/current and pending support forms, as specified in the final opportunity.

Review Criteria

DOE/AMMTO will select performers and may fund proposals in whole, in part, or not at all. Review is expected to emphasize:

• Alignment with one of the AIM₂S technical objectives and a clearly defined energy-manufacturing bottleneck.
• Technical merit and credibility of the AI approach, including the role of domain knowledge or physics, data quality, uncertainty management, and validation.
• Clarity of starting and target TRL/MRL, technical maturation logic, milestones, and quantitative evidence required to demonstrate progress.
• Substantial and measurable improvements relative to current practice including qualification time, throughput, quality, yield, reliability, cost, scrap, process stability, or pilot-scale readiness.
• Execution readiness, including team capability, access to data, facilities, equipment, partners, and a practical plan for production-relevant validation.
• Cybersecurity, data governance, access control, and protection of proprietary or sensitive technical information.
• Commercialization and deployment pathway, including integration into domestic energy manufacturing supply chains and contribution to supply-chain resilience.

Portfolio-level outcomes identified include 30-50% shorter materials qualification and certification timelines; 2x acceleration of priority-material insertion (Objective 1) and 2x acceleration of throughput (Objective 2); 20-40% improvements in quality and yield; 50% improvements in reliability and process stability; 25-50% cost reductions; and 20-40% scrap reductions. Each proposal should define project-specific baselines and target metrics.