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| YesAnd Labs LLC | Nabil Laoudji | Principal |
Small Business
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Other Energy Technologies
| YesAnd Labs specializes in driving innovation at the intersection of AI and the natural sciences. Led by an MIT MBA, we focus on fostering collaboration, amplifying advancements, and streamlining complex research ecosystems to accelerate progress. Recent initiatives include producing an expert panel to drive collaboration and amplify impact in autonomous research and materials discovery, and featuring science innovators on our new podcast, Discovery Engines: https://www.youtube.com/@discoveryengines
We are deeply aligned with ARPA-E’s mission to integrate AI and high-throughput experimentation for advancing heterogeneous catalyst development. Our interest lies in supporting the creation of AI-enabled, closed-loop workflows and accelerating the discovery-to-application cycle for catalysts.
Specific ways we can help: • Strategic Facilitation: Designing and guiding collaborations that streamline workflows and align resources with ARPA-E’s ambitious goals. • Communication & Amplification: Translating scientific advancements into impactful narratives to attract resources, talent, and visibility. • Ecosystem Development: Building interdisciplinary partnerships across academic, government, and industrial sectors to enable transformative outcomes.
YesAnd Labs is eager to support this initiative by facilitating partnerships, connecting stakeholders to high-throughput resources, and accelerating catalyst development cycles through strategic collaboration and effective communication. |
| CA |
| Siemens | Ankit Shukla | Research Professional |
Large Business
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Other Energy Technologies
| We focus on research in automation engineering workflows, process automation, Digital Twins, closed-loop optimization and GenAI (CoPilot etc.), among other areas. We are hoping to collaborate with partners who have capability in high throughput experimentation for heterogenous catalyst development. |
| NJ |
| Michigan State University | Ruigang Wang | Professor |
Academic
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Other Energy Technologies
| Dr. Wang's group at Michigan State University specializes on the synthesis and investigation of the processing-structure-property relationships of emission control catalysts, including those used for dry reforming of methane, CO2 hydrogenation, chemical looping carbon capture, and automotive three-way catalytic converter. The team has extensive experience in applying advanced transmission electron microscopy techniques (in situ and in operando TEM, HRTEM, STEM, EELS, EDX) to atomic-level structural and chemical characterization of catalytic materials. |
| MI |
| Oregon State University | Zhenxing Feng | Associate Professor |
Academic
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Other Energy Technologies
| Dr. Feng at OSU is a recognized expert in surface/interface studies using in-situ synchrotron X-ray techniques. Dr. Feng has more than 20 years of experience using the synchrotron sources national-wide. The combination of in-situ XAS and AP-XPS, as highlighted in Feng’s previous works, can provide the information of composition, electronic structure, and local coordination of nano materials, which is key to understanding the catalysts’ evolution in chemical and electrochemical reactions. Dr. Feng has access to sufficient synchrotron beamtime and can ensure the abundant resources to carry out the designed in-situ experiments. |
| OR |
| Sandia National Labs | Dale Huber | Distinguished Member of the Technical Staff |
Federally Funded Research and Development Center (FFRDC)
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Other Energy Technologies
| Sandia has developed an automated microfluidic synthesis platform that is capable of AI-guided synthesis and real-time analysis of catalyst activity. |
| NM |
| University of Massachusetts Lowell (MSI) | Fanglin Che | Assistant Professor, VHRP |
Academic
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| Expertise and Interest: Multi-physics modeling and multi-scale simulations, including Computational Fluid Dynamics (CFD) via COMSOL Multi-physics, Density functional theory (DFT), microkinetic modeling (MKM). Physics-informed AI development for heterogeneous catalysis, including thermal catalysis, electrocatalysis, field-enhanced catalysis. |
| MA |
| National Renewable Energy Laboratory | Robert Baldwin | Principal Scientist |
Federally Funded Research and Development Center (FFRDC)
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Other Energy Technologies
| NREL has interdisciplinary expertise and capabilities in thermochemical and electrochemical catalyst and process development including powder and formed catalyst synthesis and characterization, reaction performance evaluation in bench to pilot-scale systems, multi-scale modeling including ab initio, mesoscale, and reactor-scale modeling of kinetic and transport phenomena, AI-ready database development and development/utilization of AI/ML in diverse research applications. |
| CO |
| National Renewable Energy Laboratory | Nicholas E. Thornburg | Senior Reaction Engineer |
Federally Funded Research and Development Center (FFRDC)
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Other Energy Technologies
| Multiphase chemical reaction engineering, reactor design, heterogeneous catalysis and multiscale modeling for renewable small-molecule chemical syntheses facilitated by multiple renewable energy reactor inputs (e.g., electrons, photons, heat, hydrogen) for deep decarbonization of the chemical industry and heavy transportation sectors. Active research projects in the following areas: (i) renewable ammonia synthesis, separation and utilization; (ii) electrochemical COx conversion, scale-up and energy systems integration for the synthesis of valuable commodity chemicals; (iii) onboard fuel and hydrogen carrier reforming; and (iv) understanding catalyst deactivation in integrated chemical process environments. Joint adjunct faculty appointment in the Colorado School of Mines Department of Chemical and Biological Engineering that supports creation and periodic teaching of an original elective course entitled "CBEN 498/598 – Advanced Reactor Design," which offers a survey of traditional and non-traditional multiphase chemical reactors and their industrial reaction engineering principles to prepare students for career paths in either academic or industrial research & development environments. |
| CO |
| BASF Corporation | Amit A. Gokhale | Director, Process and Chemical Engineering R&D |
Large Business
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Other Energy Technologies
| BASF is one of the largest manufacturers of catalysts as well as chemicals in the world. Our catalyst manufacture capabilities range from chemical catalysts that serve several markets, including sustainable chemicals and energy applications. Over the years, BASF has developed several chemical catalysts and commercialized the same in our own plants and those of our customers via our market catalyst business. In addition, we also operate a custom catalyst business which is firewalled from the rest of the company to allow our customers to develop their proprietary catalysts in partnership with us.
Over the years, we have developed several rules and methodologies that allow us to scale-up catalysts from lab scale to kg and ton scale rapidly. This is accomplished in our Catalyst Scale-up & Characterization Laboratory where we have deep experience in translating catalysts developed in academic labs and startups into industrially relevant formulations. In addition, we are also set up to conduct reactor studies at various scales and using a variety of different reactor types to test the efficacy of catalysts and to inform reactor design. Modeling is a core strength at BASF, and we are capable of developing kinetic models, CFD models for reactor design, process models (e.g. AspenPlus) to develop the entire process/technoeconomics, as well as life cycle analysis models to quantify the CO2 reduction benefits.
With respect to this FOA, BASF, as a partner could take on ANY of the following roles – A) Work with you on a discovery program and advise on selecting the right raw materials and techniques that will reduce the effort required during scale up, B) As a scale-up partner we can provide technical input and facilities for translating lab recipes to industrially relevant formulations. C) If needed, we can assess the effectiveness of the scaled-up catalysts in our labs and help with reactor design D) Conduct overall process, technoeconomics, and GHG reduction analysis E) Provide insights into the chemicals market and develop a robust go to market plan as one of the largest chemical companies in the world. |
| TX |
| Kaio Labs | William Purvis | CEO & Co-Founder |
Small Business
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Other Energy Technologies
| Kaio Labs is developing an autonomous materials discovery platform that combines robotics and AI to accelerate the development of electrocatalysts for CO2 conversion. Our technology addresses the critical challenge of discovering high-performance catalysts that can enable economically viable CO2 electroreduction at industrial scale. Our core capabilities include (i) automated high-throughput experimentation for catalyst synthesis and testing, (ii) machine learning algorithms optimized for multi-objective catalyst discovery, and (iii) custom robotics systems for reproducible materials research.
We are interested in collaborating with teams that have expertise in (i) advanced catalyst characterization techniques, particularly in-situ/operando methods, (ii) membrane-electrode assembly optimization for CO2 electrolyzers, and (iii) industrial-scale electrolyzer design and operation.
Our team brings together deep expertise in physical chemistry, artificial intelligence, and robotics automation, with specific experience in developing models that operate in low-data environments. Our work will offer rapid catalyst screening and performance optimization through our self-driving laboratory platform. |
Website: kaiolabs.com
Email: will@kaiolabs.com
Phone: 5513715309
Address: 2 Cedar St, 2 Cedar St, Newark, NJ 07102, Newark, NJ, 07102, United States
| NJ |
| Dimensional Energy | Brad Brennan | Chief Science Officer |
Small Business
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Other Energy Technologies
| Background: Dimensional Energy (DE) has core competencies in heterogeneous thermocatalysts and integrated systems for reactions along the chemical pathways from CO2 to hydrocarbons. To-date this has led to two commercial catalysts for Reverse Water Gas Shift and Fischer-Tropsch. DE has designed, built, and operated multiple pilot plants using eFuels/PtL pathways.
Interest: We would like to broadly incorporate AI and rapid iterative testing sequences into our workflow for our current catalyst areas and future routes. This could involve partnering to develop the AI pathway and to develop the High Throughput Testing hardware/software systems.
Capabilities: - Synthesis of heterogeneous catalysts from raw materials to final product. - Lab and pilot plant scale catalyst testing sites. - Engineering support for test rigs. |
| NY |
| Newfound Materials, Inc. | Matthew J. McDermott | CEO |
Small Business
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Other Energy Technologies
| Newfound Materials develops a data-driven/AI-based predictive synthesis platform for accelerated materials discovery and high-throughput experimentation. We specialize in reaction network modeling, pathway prediction, and recipe generation for inorganic synthesis. Our platform's algorithms and approach were developed over 5+ years of synthesis science research at U.C. Berkeley and Lawrence Berkeley National Laboratory.
We specialize in downselecting to the most theoretically optimal synthesis recipes to test in the lab, and are interested in partnering to co-develop new R&D approaches for heterogeneous catalyst development. |
| TX |
| Virginia Tech | Hongliang Xin | Associate Professor |
Academic
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Power Generation: Renewable
| My group centers on the integration of artificial intelligence with quantum chemistry and large-scale atomistic simulations in catalysis research. Leveraging automation and AI agents, we develop closed-loop systems that couple high-throughput experimentation with real-time data analysis and optimization. My expertise includes scalable, explainable AI frameworks and multimodal data integration, enabling the rapid prediction of catalytic properties and design of new materials. |
| VA |
| Saint-Gobain NorPro | Marissa Reigel | Director of Research and Development |
Large Business
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Other Energy Technologies
| Saint-Gobain NorPro's advanced ceramic technologies span well over 100 years with well-known solutions for fixed bed reactor processing and heat & mass transfer applications. We are a supplier of custom catalyst carriers, bed topping media, support media and other products that support energy production. We work with our customers to supply heterogeneous catalyst supports that fit their application needs. We can tailor surface area, porosity, surface chemistry, size and shape. |
| OH |
| MIT | Ju Li | professor |
Academic
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| Autonomous experiments using active learning and AI: https://www.nature.com/articles/s41578-023-00588-4
CRESt – Copilot for Real-world Experimental Scientist: https://www.youtube.com/watch?v=POPPVtGueb0 https://www.youtube.com/shorts/cgTIoC-KXQs https://www.youtube.com/watch?v=sibCICesrEY https://chemrxiv.org/engage/chemrxiv/article-details/64a81dcd6e1c4c986bf83225
Universal Interatomic Potential: https://youtu.be/WY4IL4Ovuns |
| MA |
| Lawrence Berkeley National Laboratory | Ji Su | Material Staff Scientist & Engineer |
Federally Funded Research and Development Center (FFRDC)
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| Background: Dr. Su is a staff scientist at LBNL with 15 years of experience in heterogeneous catalyst design and development, as well as surface chemistry.
Interests: Collaborating with experts in AI/ML to accelerate the development of catalysts, close the gap between rational design to engineered design. Partnering with engineering experts to establish a robotic automation system for catalyst synthesis, test and in situ characterization.
Capabilities: Su Group at Berkeley Lab lunched the Applied Catalysis Hub: Energy & Environmental (ACHEE). ACHEE includes three major platforms: (i) Catalyst Discovery (high entropy materials and traditional catalyst upgrading) and Fabrication (kg scale catalyst pellets); (ii) Catalysis Process Demonstration (High throughput reactor array: 10x10 channel in designing, And bench scaleup reactors for: 1-10 L gas reactant/min, and liquid reactant 1L/day); (iii) Catalysis Mechanism Interpretation (atomic/molecular understanding).
ACHEE is designed to address technical gaps and develop new technologies in applied catalysis for the energy and environmental sectors. Leveraging novel catalyst design concepts, advanced catalyst materials, and innovative catalysis process designs, ACHEE aims to generate new technologies at TRL 4-6, making them ready for further development by the industry. ACHEE is also designed to coordinate Berkeley Lab with industry partners, especially those in early stages of technology development, to enable and accelerate the development and adoption of new technologies developed at Berkeley lab and elsewhere.
In 2024, 3 startup companies have been spun off from Su group. |
| CA |
| GE Vernova Advanced Research | Naveenan Thiagarajan | Principal Engineer |
Large Business
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| GE Vernova Advanced Research (GEVAR) is a hub for innovation, research and development, focused on decarbonization, renewables, and electrification to enable a zero-carbon future.
Specific to the topics of AI-accelerated catalysis and reactor development, our technologies and expertise include: - material discovery, development, and characterization labs to develop novel materials for hot & harsh environments. GEVAR’s Materials Informatics capability delivers 2-200x acceleration in materials development relative to state-of-the-art through modern data-driven techniques. - materials development and characterization via traditional first-principles computational methods, such as density functional theory, currently being applied to carbon capture sorbent development and stability assessments of thermal barrier coating oxide compositions. - demonstrated advanced additive manufacturing capabilities to develop robust (novel metal, refractory alloys etc.), high temperature (~>900 C), high heat-transfer structures (DE-EE0008737, DE-AR0001120). - AI capabilities to harness data to drive material discovery, industrial asset optimization, and inspection. We have developed innovative machine learning workflows with capabilities of Bayesian Learning and optimization, history matching or calibration, uncertainty quantification, optimization using efficient surrogates, and hybrid reasoning with demonstrated real-world impacts (DE-AR0001203, https://doi.org/10.1007/s12008-024-01905-z). - electrochemical cell and stack synthesis and characterization capabilities that include development of large-scale solid oxide electrolyzers and novel battery chemistries (CX-029102).
The highlighted background work and broad capabilities could be leveraged for AI-enabled rapid development of design, process, and structures to support novel, industrial-scale catalysis aimed at net-zero emissions. |
| NY |
| Princeton University | Andrew Rosen | Assistant Professor |
Academic
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Other Energy Technologies
| My interests are at the intersection of AI, high-throughput computing, and quantum-mechanical modeling for the design and discovery of clean energy materials. |
| NJ |
| Pacific Northwest National Laboratory | Yangang Liang | Materials Scientist |
Federal Government
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Other Energy Technologies
| Dr. Yangang Liang is a materials scientist in the Battery Materials & Systems group at PNNL. He joined PNNL in 2020, focusing on developing and applying AI-guided high throughput experimentation methodologies to accelerated design and discovery of novel energy storage materials by collaborating with data scientists. His doctoral work focused on development of functional metal oxide thin films via high-throughput pulsed laser deposition for advanced energy applications. He received his Ph.D. in Materials Science and Engineering from University of Maryland at College Park, and both his M.S. and B.S. in Chemistry from Fudan University. Prior to joining PNNL, Dr. Liang worked in GE Global Research Center (Shanghai and New York) and Biolegend (San Diego) for about 9 years, focusing on designing and producing functional materials for applications in Catalysts, Industrial Water Treatment, Polymer Detections, OPV, OLEDs, SOFC, Battery, Flow Cytometry, LED, and CT. High-Throughput Experimentation Capabilities at PNNL: ARES (Automated Robotics for Energy Storage) Lab PNNL’s ARES Lab houses two state-of-the-art modular robotic platforms (Big Kahuna, Unchained Labs), with one operated in a nitrogen purge box for general experiments and another in an argon glove box for highly sensitive experiments. These systems are fully configurable, accommodating multi-well microarray substrates (e.g., 2 to 96-well microplates), and equipped with advanced tools such as an analytical balance, solid dispensers, liquid handlers, capping/uncapping station, on-deck magnetic stirrer with heating/cooling function, vortex mixer, centrifuge, and eight individual optimization sampling reactors (up to 400 psi/27.5 bar). The ARES Lab integrates high-throughput property characterizations, covering basic physical property measurements like solubility, conductivity, viscosity, and electrochemical measurements. Offering a fully automated research platform, it facilitates materials synthesis, sample preparation, and ink/electrolyte formulation and optimization, particularly for solution-based workflows. The seamless integration of these capabilities with artificial intelligence and machine learning facilitates a significant reduction in development cycles for innovative functional materials. Part robot, part workstation, part intelligent database, PNNL’s ARES lab enables automated combinatorial materials synthesis, high-throughput screening, and optimizations for large |
| WA |
| Molecule Works Inc. | Wei Liu | CTO |
Small Business
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| Molecule Works Inc. (MWI) has invented a new electrochemical (EC) reactor and process for direct conversion of CO2 and moisture in air into liquid hydrocarbon fuels. Promising results have been achieved. Now, we would like to optimize indivdiual compoenents and build reactor prototypes. Cathode catalyst is one of the critical components that determine producivity, electrical efficiency, and longtime of the EC reactor. Its performance must be tested in actual cell configuraiton with other components. Finding inexpensive and high-performance cathode catalysts requires extensive cell tests and become very expensive. We are looking for team members to develop a robot-typle testing machine to speed up the catalyst and cell development pace. |
| WA |
| GE Aerospace Research | Ghanshyam Pilania | Senior Engineer-Materials Informatics |
Large Business
|
Other Energy Technologies
| For more than 130 years, GE has invented the future of industry. From Thomas Edison’s first incandescent light bulb to today’s internet-connected jet engines, GE’s home-grown technologies spur world-changing transformations. Fundamental to GE’s DNA is the ardent desire to innovate, which is where you’ll find GE Aerospace Research. We operate at the intersection of science and creativity, delivering innovative solutions that the future of engineering and technology.
One of our core competencies is in probabilistic design and materials informatics for application-specific materials discovery and process optimization. Leveraging GE's robust and integrated proprietary materials informatics framework, the team has a demonstrated track record of real-world materials design for numerous structural and functional materials in an industrial setting. With state-of-the art capabilities in multi-fidelity information fusion, multi-objective optimization, close loop adaptive design/active learning and deep materials expertise coupled with high throughput characterization and electrochemical testing we are well positioned to serve as a strong partner on the upcoming FOA. |
| NY |
| Sora Fuel Corporation | Patrick Sarver | Chief Scientific Officer |
Small Business
|
Other Energy Technologies
| Sora Fuel is developing a potentially transformative electrolyzer technology that faces the classic catalyst optimization problem of maintaining excellent selectivity at meaningful rates. Optimization of this process could be aided by (i) generating sufficient high-quality, full-cell data to leverage AI/ML-based techniques and (ii) improved characterization of the small variations in catalyst structure, morphology, and formulation that can drive significant changes in performance.
We would thus be interested in potentially collaborating with teams with expertise in (i) high-throughput experimentation approaches for long-duration testing of complete membrane-electrode assemblies; (ii) multi-modal catalyst characterization to correlate performance with changes in catalyst structure and/or environment, and (iii) application of AI/ML approaches to problems in catalysis. We bring a team with deep expertise in electrochemistry and electrochemical engineering, with specific background on the design, operation, optimization, and scaling of complex electrochemical cells. |
| MA |
| Copernic Catalysts | Aruna Ramkrishnan | CTO and Co-Founder |
Small Business
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Power Generation and Energy Production: Liquid and Gaseous Fuels/Nuclear
| Copernic utilizes cutting-edge catalyst screening platform (in-house high throughput experiments + computational tools like DFT, AI and ML with our partner Schrodinger), to transform the production of commodity chemicals and e-fuels like ammonia for a low-carbon future. Copernic has already shown proof of concept of our platform for ammonia synthesis through development of a world-class Haber Bosch catalyst at 10x industry speed. We are interested e-fuels and commodity chemicals in general and in particular, CO2 utilization chemistries including products like sustainable aviation fuel. Please reach out to aruna.rk@coperniccatalysts.com for more information. |
| MA |
| Physics Inverted Materials, Inc. | Emil Annevelink | CEO |
Small Business
|
Other Energy Technologies
| Physics Inverted Materials develops machine learning technology to create multi-scale digital twins of materials. Our machine learning models capture the chemical, mechanical, thermal, and electro-chemical properties of materials down to the atomic scale to accurately predict materials properties and device performance under realistic industrial conditions. Our simulation technology has been used to screen material candidates as well as design new materials. We aim to partner with materials manufacturers to create a complete digital model of your manufacturing process so that we can digitally test and predict the ability of new catalyst materials to be drop-in replacements to your current process. |
| PA |
| University of Washington | Shijing Sun | Assistant Professor |
Academic
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Transportation
| My lab works on building autonomous platforms for energy materials and systems, we have HTE capability, AI/ML for closed experimentation and data management expertise. I'm interested but not limited to potentially partnering with computational scientists and catalysis domain experts. |
Website: www.uwsunlab.com
Email: shijing@uw.edu
Phone: 8572429606
Address: 3900 E Stevens Way NE, Box 352600 Seattle, WA 98195, Seattle, WA, 98195, United States
| WA |