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ADVANCED MANUFACTURING

Description:

9.     ADVANCED MANUFACTURING

Maximum Phase I Award Amount: $200,000

Maximum Phase II Award Amount: $1,100,000

Accepting SBIR Phase I Applications: YES

Accepting STTR Phase I Applications: YES

 

EERE’s Advanced Manufacturing Office (AMO) (http://energy.gov/eere/amo) collaborates with industry, small business, universities, national laboratories and other stakeholders on emerging manufacturing technologies to drive U.S. energy productivity and economic competitiveness. AMO has a dual mission to develop technologies that reduce manufacturing energy intensity and/or reduce the life cycle energy impact of manufactured goods.

 

This Topic reflects DOE’s support for Advanced Manufacturing Research and Development (R&D) as part of its funding to advance the Industries of the Future. It includes activities that develop new paradigms, methods, processes, or equipment for new or existing manufacturing products, materials, or supply chain components and that provide an advantage over existing techniques or tools. Advantages include reduced time to market, enabling new performance attributes, improving small-batch production, cost savings, energy savings, or reduced environmental impact from the manufacturing of products.

 

All proposals to this topic must:

·         Propose a tightly structured program which includes clear, manufacturing-relevant technical milestones/timeline that demonstrate clear progress, are aggressive but achievable, and are quantitative;

·         Provide evidence that the proposer has relevant manufacturing experience and capability;

·         Clearly define metrics and expected deliverables;

·         Explain applications of project output and potential for future commercialization;

·         Include projections for cost and/or performance improvements that are tied to a clearly defined baseline and/or state of the art products or practices;

·         Explicitly and thoroughly differentiate the proposed innovation with respect to existing commercially available products or solutions;

·         Include an energy savings impact and impact grid as well as a preliminary cost analysis;

·         Report all relevant performance metrics; and

·         Justify all performance claims with theoretical predictions and/or relevant experimental data.

 

The Phase I application should detail material, design and/or bench scale systems that are scalable to a subsequent Phase II prototype development.

 

NOTE: In addition to the subtopics below, AMO is considering funding proposals in response to the following three multi-office topics: Topic 20 – Joint Topic: CABLE Materials And Applications; Topic 11 – Joint Topic: Polymers Upcycling and Recycling; and Topic 13 – Joint Topic: Advanced Building Construction Technologies.

 

Applications must be responsive to the following subtopics. Applications outside of these subtopic areas will not be considered.

 

a.      Innovation Research in Application Specific Integrated Circuit ASIC Semiconductor Chip Design for Edge Computing in Manufacturing

The objective of this subtopic is to maintain US manufacturing leadership by providing small business opportunities to develop technologies that will be applied in next-generation manufacturing [1]. Small businesses that provide applied Artificial Intelligence (AI) semiconductor technology design and concept development are afforded the opportunity to work with US semiconductor fabricators to bring AI technology that will rely on 5G broadband wireless communications to applications in the US manufacturing sector [2]. Many technologies that are presently applied in manufacturing process control, for example, that rely on wired communication links, will be superseded by wireless communications, and adaptive control approaches based on AI and machine learning strategies will be possible with the digital computing power that will be accessible with 5G broadband wireless communications.

 

This subtopic solicits feasibility research in new application-specific integrated circuit (ASIC) designs that will enable AI application in edge computing applications such as automatic control. This subtopic reflects DOE’s support for to enable 5G/Advanced Wireless Technologies as part of its focus on enabling the Industries of the Future as well as DOE\EERE’s support for Advanced Microelectronics.

 

The introduction of 5G broadband wireless communications will enable manufacturers to access resources available only with 5G wireless – such as cloud computing and complex wireless sensor networks. This broadband access, in turn, will facilitate the application of digital computing at points of access or presence in manufacturing operations (edge computing). This includes AI applications in automatic control of discrete and continuous processes. Open and closed loop control in manufacturing requires sensing of process or operation variables and the application of algorithms by controllers to act on sensor measurements to control final elements in control loops. AI-based control approaches derive algorithms for closed loop control and models for open loop control using a variety of machine learning approaches to analyze data.

 

ASIC designs developed for this subtopic are expected to be 5G compatible and be of direct use in edge computing applied to US manufacturing, such as applications in automatic control. Small businesses providing promising new ASIC designs would be expected to work with semiconductor circuit manufactures to fabricate the new ASIC and integrate these into edge computing systems that would be used by manufacturers, with a specified purpose such as automatic control of processes and operations. Grant applications responsive to this Phase 1 funding opportunity will specify the proposed end use in US manufacturing of new ASIC designs, the AI and machine learning approaches to be applied by the ASIC, the possible integration of the ASIC into an edge computing system, and discuss the benefits of the possible new technology as compared with current manufacturing practice in the US.

 

Questions – Contact: Brian Valentine, Brian.Valentine@ee.doe.gov

 

b.      Novel Manufacturing Methods for Membranes and Desalination System Components

This subtopic solicits proposals to develop continuous, precise, and smart manufacturing techniques that have the potential to lower the cost and facilitate the adoption of high-performance membrane materials and design architectures. Together, such changes in design and materials manufacturing methods could substantially reduce the time to market for new membranes critical for desalination of water. Novel manufacturing methods must be explored to ensure new materials for membranes and desalination systems can be produced with suitable low-cost and scalability. Therefore, the R&D supported under this subtopic must improve materials, design, and manufacturability of high-performance membranes and desalination system components with the goal of reducing costs relative to current methods.

 

This subtopic supports the objectives of the Water Security Grand Challenge, a DOE-led framework to advance transformational technology and innovation to meet the global need for safe, secure, and affordable water [1].

 

Proposals must address one of the following three areas of interest to be considered responsive to this subtopic:

1.      Low-cost membrane materials and manufacturing methods: R&D is needed to advance the next generation of membrane materials and manufacturing methods. Researchers developing new membrane materials must balance material performance (e.g., separation properties, thermal conductivity, catalytic activity), against robustness (e.g., mechanical, chemical) and manufacturability (e.g., cost, scalability). Materials R&D can lead to improvements in surface chemistry and interfaces that enable development of materials having 1) high-target ion selectivity, 2) high contaminant removal and water permeability, and 3) greater chemical resistance, antifouling and corrosion-resistance compared to state of the art. Innovations in both membrane materials and related manufacturing methods could vastly expand the range of water chemistries over which modular membrane systems are cost-competitive and potentially eliminate the need for energy-intensive pretreatment and post-treatment. Innovations in high-performance materials and multifunctional membranes enabled by new approaches in materials discovery, synthesis, and characterization are sought. Novel methods of manufacturing that lower cost and improve chemical and hydrodynamic performance that could substantially lower the energy intensity, levelized cost of water (LCOW), water intensity, and failure frequency of treatment processes to increase the nation’s ability to tap nontraditional water sources also are sought. Such materials for membranes may become more cost effective if they can leverage recent additive, gradient, and roll-to-roll manufacturing advances that lower production costs.

 

2.      Manufacturing ultra-low cost, high sensitivity sensors and sensor networks for water quality measurements and detection of emerging contaminants: Current water treatment systems are designed to operate at nominally steady-state conditions, relying on human intervention to adapt to variations in water quality and correct failures in process performance. Simple, robust sensor networks coupled with sophisticated analytics and controls systems could enhance performance efficiency, process reliability, and treatment process adaptability while minimizing the need for onsite, manual interventions. These innovations could significantly lower the cost of distributed, fit-for-purpose desalination systems and their operational expenses, thus reducing the overall cost of water treatment This area of interest is focused on developing new, innovative sensors and overcoming related manufacturability challenges for high sensitivity sensors and sensor networks for water quality measurements and detection of emerging contaminants. These sensor data could be used to optimize desalination and other water treatment processes. Data needs for process control and monitoring could also be addressed through these new sensors and sensor networks.

 

3.      Novel methods and technologies for in-situ characterization of membranes during roll-to-roll or otherwise continuous manufacturing: Traditional manufacturing methods can hinder the adoption of novel materials and new architectural designs in desalination system components such as membranes. To reduce membrane costs, there is a need to develop roll-to-roll (R2R) platforms and other continuous manufacturing processes that allow careful control of membrane microstructure and performance. For example, development of new ceramic and composite materials could be accelerated to commercial scale with research on additive and R2R manufacturing, enabled by development of methods to deposit ceramics on complex shapes and rough surfaces. These advances require the development of 1) in-situ characterization techniques that enable control of membrane properties during manufacturing; 2) in operando materials characterization techniques that facilitate understanding of membrane performance under varying conditions; and 3) manufacturing innovations that enable the scalable deployment of novel membrane materials in cost-competitive modules. Process optimization could be achieved by advanced characterization capabilities, such as in-situ X-ray scattering during R2R processing. Cutting-edge characterization tools at national user facilities could be leveraged for materials and processes design and optimization of membrane manufacturing.

 

Questions – Contact: Melissa Klembara, Melissa.Klembara@ee.doe.gov

 

References: Subtopic a:

1.      Semiconductor Industry Association. “New SIA Report Highlights Industry’s Strength and Looming Challenges.” Report on the State of US semiconductor industry, June 18, 2020, https://www.semiconductors.org/new-sia-report-highlights-industrys-strength-and-looming-challenges/

 

2.      McEllan, P. “AI Drives A New Wave For Semiconductors.” Semiconductor Engineering, June 4, 2020 https://semiengineering.com/ai-drives-a-new-wave-for-semiconductors/

 

References: Subtopic b:

1.      U.S. Department of Energy. “About the Water Security Grand Challenge.” US DOE, 2020, https://www.energy.gov/water-security-grand-challenge/water-security-grand-challenge

 

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