Test Bed: Toward a Network of Programmable Cloud Laboratories
Posted: Aug 05, 2025 12:00:00 AM EDT
Closes: 11/20/2025
Funding Information
Estimated Total Funding
$100,000,000
Award Floor
$2,000,000
Expected Number of Awards
6
Description
Autonomous experimentation is poised to accelerate research and unlock critical scientific advances that bolster U.S. competitiveness and address pressing societal needs. Programmable Cloud Laboratories are able to execute automated workstreams, including self-driving lab workflows, to efficiently move research goals through artificial intelligence (AI) enabled experiment design, laboratory preparations, data collection, data analysis and interpretation. While limited-scale efforts have shown promise, versatile programmable and self-driving labs capable of addressing complex research questions with trustworthy results will require coordinated technological advances and an engaged research community. Additional challenges include the availability of automated laboratory infrastructure, standardized approaches to data collection for interoperability, advances in AI for data interpretation and experimental design, and more. This solicitation aims to address such gaps and realize the potential of autonomous experimentation.
The Test Bed: Toward a Network of Programmable Cloud Laboratories (PCL Test Bed) program seeks to establish and facilitate the operation of distributed autonomous laboratory facilities. These laboratories will combine technological and human capacity to enable integration, testing, evaluation, validation, and translation of cutting-edge technology solutions in automated science and engineering. The PCL Test Bed will consist of a set of Programmable Cloud Laboratory Nodes (PCL Nodes) that can be remotely accessed to run custom workflows specified and programmed by users, that are linked together via computational networking, shared science questions, and data and artificial intelligence (AI) standards.
The PCL Test Bed will facilitate access to advanced scientific equipment, accelerate translation and scaling of basic research into industry applications, enhance reproducibility and the exchange of experimental data, and assist in training the next generation of scientists and engineers in state-of-the art methodologies. It will help develop community norms, best practices, and formal standards for automated laboratory procedures, workflows, and instrument testing and validation. It will also advance consistent practices for the collection, sharing, and use of metadata and training data and the use and exploitation of AI methods. This program will also support the development of automated laboratory methods, including self-driving autonomous experiment workflows.
Proposals must have a set of well-defined science drivers poised to derive significant benefit from targeted use of the PCL Test Bed capabilities, including but not limited to synthesis, optimization, and/or characterization experiments, in specific sub-disciplines within materials science, biotechnology, chemistry or other areas of science and engineering. These science drivers will guide the protocols and standards necessary for each node and facilitate collaboration across the Test Bed. For example, science drivers could include but are not limited to:
Materials science, materials synthesis and characterization efforts that advance U.S. competitiveness.
Biotechnology experiments in scalable, high-throughput engineering and characterization services for proteins or microbes with novel applications in the U.S. bioeconomy.
High-throughput experimentation for the accelerated development of catalysts to support more efficient chemical synthesis to address urgent national needs.
User Recruitment and On-Boarding Workshops will be a key component of the PCL Test Bed program and will serve to recruit users to individual PCL Nodes and the Test Bed to help make progress on the proposed science drivers, provide access to technology, test the limits of the experimental set-up of the nodes, and explore new research opportunities between the PCL Nodes and institutions including, but not limited to, R2 Universities, PUI (Primarily Undergraduate Institutions), and two-year institutions.
The PCL Test Bed will be available to researchers in academia as well as industry, including current and former awardees from the Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs. The portfolio of projects is available here,https://seedfund.nsf.gov/portfolio.
PCL Nodes are expected to develop and implement plans for continued operation after the period of this award.
The Test Bed: Toward a Network of Programmable Cloud Laboratories (PCL Test Bed) program seeks to establish and facilitate the operation of distributed autonomous laboratory facilities. These laboratories will combine technological and human capacity to enable integration, testing, evaluation, validation, and translation of cutting-edge technology solutions in automated science and engineering. The PCL Test Bed will consist of a set of Programmable Cloud Laboratory Nodes (PCL Nodes) that can be remotely accessed to run custom workflows specified and programmed by users, that are linked together via computational networking, shared science questions, and data and artificial intelligence (AI) standards.
The PCL Test Bed will facilitate access to advanced scientific equipment, accelerate translation and scaling of basic research into industry applications, enhance reproducibility and the exchange of experimental data, and assist in training the next generation of scientists and engineers in state-of-the art methodologies. It will help develop community norms, best practices, and formal standards for automated laboratory procedures, workflows, and instrument testing and validation. It will also advance consistent practices for the collection, sharing, and use of metadata and training data and the use and exploitation of AI methods. This program will also support the development of automated laboratory methods, including self-driving autonomous experiment workflows.
Proposals must have a set of well-defined science drivers poised to derive significant benefit from targeted use of the PCL Test Bed capabilities, including but not limited to synthesis, optimization, and/or characterization experiments, in specific sub-disciplines within materials science, biotechnology, chemistry or other areas of science and engineering. These science drivers will guide the protocols and standards necessary for each node and facilitate collaboration across the Test Bed. For example, science drivers could include but are not limited to:
Materials science, materials synthesis and characterization efforts that advance U.S. competitiveness.
Biotechnology experiments in scalable, high-throughput engineering and characterization services for proteins or microbes with novel applications in the U.S. bioeconomy.
High-throughput experimentation for the accelerated development of catalysts to support more efficient chemical synthesis to address urgent national needs.
User Recruitment and On-Boarding Workshops will be a key component of the PCL Test Bed program and will serve to recruit users to individual PCL Nodes and the Test Bed to help make progress on the proposed science drivers, provide access to technology, test the limits of the experimental set-up of the nodes, and explore new research opportunities between the PCL Nodes and institutions including, but not limited to, R2 Universities, PUI (Primarily Undergraduate Institutions), and two-year institutions.
The PCL Test Bed will be available to researchers in academia as well as industry, including current and former awardees from the Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs. The portfolio of projects is available here,https://seedfund.nsf.gov/portfolio.
PCL Nodes are expected to develop and implement plans for continued operation after the period of this award.
Synopsis
Autonomous experimentation is poised to accelerate research and unlock critical scientific advances that bolster U.S. competitiveness and address pressing societal needs. Programmable Cloud Laboratories are able to execute automated workstreams, including self-driving lab workflows, to efficiently move research goals through artificial intelligence (AI) enabled experiment design, laboratory preparations, data collection, data analysis and interpretation. While limited-scale efforts have shown promise, versatile programmable and self-driving labs capable of addressing complex research questions with trustworthy results will require coordinated technological advances and an engaged research community. Additional challenges include the availability of automated laboratory infrastructure, standardized approaches to data collection for interoperability, advances in AI for data interpretation and experimental design, and more. This solicitation aims to address such gaps and realize the potential of autonomous experimentation.
The Test Bed: Toward a Network of Programmable Cloud Laboratories (PCL Test Bed) program seeks to establish and facilitate the operation of distributed autonomous laboratory facilities. These laboratories will combine technological and human capacity to enable integration, testing, evaluation, validation, and translation of cutting-edge technology solutions in automated science and engineering. The PCL Test Bed will consist of a set of Programmable Cloud Laboratory Nodes (PCL Nodes) that can be remotely accessed to run custom workflows specified and programmed by users, that are linked together via computational networking, shared science questions, and data and artificial intelligence (AI) standards.
The PCL Test Bed will facilitate access to advanced scientific equipment, accelerate translation and scaling of basic research into industry applications, enhance reproducibility and the exchange of experimental data, and assist in training the next generation of scientists and engineers in state-of-the art methodologies. It will help develop community norms, best practices, and formal standards for automated laboratory procedures, workflows, and instrument testing and validation. It will also advance consistent practices for the collection, sharing, and use of metadata and training data and the use and exploitation of AI methods. This program will also support the development of automated laboratory methods, including self-driving autonomous experiment workflows.
Proposals must have a set of well-defined science drivers poised to derive significant benefit from targeted use of the PCL Test Bed capabilities, including but not limited to synthesis, optimization, and/or characterization experiments, in specific sub-disciplines within materials science, biotechnology, chemistry or other areas of science and engineering. These science drivers will guide the protocols and standards necessary for each node and facilitate collaboration across the Test Bed. For example, science drivers could include but are not limited to:
User Recruitment and On-Boarding Workshops will be a key component of the PCL Test Bed program and will serve to recruit users to individual PCL Nodes and the Test Bed to help make progress on the proposed science drivers, provide access to technology, test the limits of the experimental set-up of the nodes, and explore new research opportunities between the PCL Nodes and institutions including, but not limited to, R2 Universities, PUI (Primarily Undergraduate Institutions), and two-year institutions.
The PCL Test Bed will be available to researchers in academia as well as industry, including current and former awardees from the Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs. The portfolio of projects is available here,https://seedfund.nsf.gov/portfolio.
PCL Nodes are expected to develop and implement plans for continued operation after the period of this award.
The Test Bed: Toward a Network of Programmable Cloud Laboratories (PCL Test Bed) program seeks to establish and facilitate the operation of distributed autonomous laboratory facilities. These laboratories will combine technological and human capacity to enable integration, testing, evaluation, validation, and translation of cutting-edge technology solutions in automated science and engineering. The PCL Test Bed will consist of a set of Programmable Cloud Laboratory Nodes (PCL Nodes) that can be remotely accessed to run custom workflows specified and programmed by users, that are linked together via computational networking, shared science questions, and data and artificial intelligence (AI) standards.
The PCL Test Bed will facilitate access to advanced scientific equipment, accelerate translation and scaling of basic research into industry applications, enhance reproducibility and the exchange of experimental data, and assist in training the next generation of scientists and engineers in state-of-the art methodologies. It will help develop community norms, best practices, and formal standards for automated laboratory procedures, workflows, and instrument testing and validation. It will also advance consistent practices for the collection, sharing, and use of metadata and training data and the use and exploitation of AI methods. This program will also support the development of automated laboratory methods, including self-driving autonomous experiment workflows.
Proposals must have a set of well-defined science drivers poised to derive significant benefit from targeted use of the PCL Test Bed capabilities, including but not limited to synthesis, optimization, and/or characterization experiments, in specific sub-disciplines within materials science, biotechnology, chemistry or other areas of science and engineering. These science drivers will guide the protocols and standards necessary for each node and facilitate collaboration across the Test Bed. For example, science drivers could include but are not limited to:
- Materials science, materials synthesis and characterization efforts that advance U.S. competitiveness.
- Biotechnology experiments in scalable, high-throughput engineering and characterization services for proteins or microbes with novel applications in the U.S. bioeconomy.
- High-throughput experimentation for the accelerated development of catalysts to support more efficient chemical synthesis to address urgent national needs.
User Recruitment and On-Boarding Workshops will be a key component of the PCL Test Bed program and will serve to recruit users to individual PCL Nodes and the Test Bed to help make progress on the proposed science drivers, provide access to technology, test the limits of the experimental set-up of the nodes, and explore new research opportunities between the PCL Nodes and institutions including, but not limited to, R2 Universities, PUI (Primarily Undergraduate Institutions), and two-year institutions.
The PCL Test Bed will be available to researchers in academia as well as industry, including current and former awardees from the Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs. The portfolio of projects is available here,https://seedfund.nsf.gov/portfolio.
PCL Nodes are expected to develop and implement plans for continued operation after the period of this award.
Eligibility
Eligible Applicants:
*Who May Submit Proposals: Proposals may only be submitted by the following:
-For-profit organizations: U.S.-based commercial organizations, including small businesses, with strong capabilities in scientific or engineering research or education and a passion for innovation.
-Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.
-Institutions of Higher Education (IHEs): Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of sub-awards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus.
-For-profit organizations: U.S.-based commercial organizations, including small businesses, with strong capabilities in scientific or engineering research or education and a passion for innovation.
-Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.
-Institutions of Higher Education (IHEs): Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of sub-awards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus.
Funding Activity Categories
CFDA Numbers
- 47.041 - Engineering
- 47.049 - Mathematical and Physical Sciences
- 47.050 - Geosciences
- 47.070 - Computer and Information Science and Engineering
- 47.074 - Biological Sciences
- 47.075 - Social, Behavioral, and Economic Sciences
- 47.076 - STEM Education (formerly Education and Human Resources)
- 47.079 - Office of International Science and Engineering
- 47.083 - Integrative Activities
- 47.084 - NSF Technology, Innovation, and Partnerships
Contact Information
Agency: National Science Foundation
Contact: U.S. National Science Foundation
Email: grantsgovsupport@nsf.gov
Phone: 703-292-4203
NSF grants.gov support
grantsgovsupport@nsf.gov
grantsgovsupport@nsf.gov
Additional Information
Document Type: synopsis
Opportunity Category: Discretionary
Version: 1
Last Updated: Aug 05, 2025 11:00:07 PM EDT
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