Catalysts for a
sustainable future.

The world is rapidly adopting Green Hydrogen – not only as a replacement for grey and blue molecules, but as a clean energy currency and crucial feedstock for green downstream molecules like ammonia, methanol, and e-fuels. The dirty hydrogen industry today is so large that it emits a billion tons of CO2 per year. No “new economy” use cases for hydrogen are necessary in order to have an enormous environmental impact with green production.

Hard-to-decarbonize industries across the globe – transportation, energy, metals, chemicals, construction, etc. comprise the vast majority of 2050 GHG target challenges. The world can’t trade one problem for another, limiting Green Hydrogen production due to critical mineral constraints. That’s why at Calicat we’re focused on reducing and removing the rare and pricey precious metals used as catalysts for producing hydrogen today.

Catalyst Discovery Engine (CDE)

01. DEPOSIT

Combinatorial PVD and drop on demand printing

02. Characterize

X-Ray fluorescence

03. SCREEN

Accelerated durability testing or Scanning Droplet Cell (SDC)

04. INTEGRATE

Nanoparticle Synthesis and Structural Characterization

05. POWDER TESTING

Ink fabrication and electrolytic testbed

06. Iterate

AI/ machine learning /
data analysis

The catalyst discovery process.

Our CDE is a data-driven rapid screening process that allows scientists to make, characterize, and quantify the catalytic activity of thousands of material compositions per week. This has enabled us to discover several families of novel, non-iridium catalyst materials that have been validated both in-house and through third-party testing around the world.

01. Deposit

We use Drop-on-Demand as well as a Physical Vapor Deposition to synthesize these AI-predicted compositions of matter onto rastering plates with hundreds of samples.

02. Characterize

We use XRF and XRD prior to and after permanence testing to predict durability and specify the species and concentrations which are responsible for the best performance on each plate.

03. Plate screening

Our proprietary Scanning Droplet Cell, the heart of the CDE, turns each tiny dot on a rastering plate into a tiny electrolyzer, then measures its activity. We expose the rastering plates to various conditions and repeat this step to assess permanence.

04. Integrate

Our synthetic team makes small batches of nanoparticles based on the best catalyst materials. We analyze these powders with XRD and SEM to optimize the morphology and size.

05. Test

For particularly promising catalyst candidates, our synthetic chemistry team develops larger quantities of nanoparticles that can be applied to CCMs or PTLs for in-situ screening. Our suite of 25 5cm2 electrolyzer test stations are full of candidate catalyst materials in various stages of development and optimization. They progress through our medium and large test cells and test stacks as they get closer to market.

06. Iterate

Data from years of testing was painstakingly characterized and used to build a proprietary machine learning model. This LLM now has 70% accuracy in predicting both activity and durability of catalyst candidates. All of our testing starts here, with prediction – and ends here, with data intake.

01. Deposit

We use Drop-on-Demand as well as a Physical Vapor Deposition to synthesize these AI-predicted compositions of matter onto rastering plates with hundreds of samples.

02. Characterize

We use XRF and XRD prior to and after permanence testing to predict durability and specify the species and concentrations which are responsible for the best performance on each plate.

03. Screen Plates

Our proprietary Scanning Droplet Cell, the heart of the CDE, turns each tiny dot on a rastering plate into a miniature electrolyzer, then measures its activity. We expose the rastering plates to various conditions and repeat this step to assess permanence.

04. Integrate

Our synthetic chemistry team makes small batches of nanoparticles based on the best-performing catalyst materials from the plate screening step. We analyze these powders with XRD and SEM to optimize their morphology and size.

05. Test

For particularly promising catalyst candidates, our synthetic chemists develop larger quantities of nanoparticles that can be applied to CCMs or PTLs for in-situ screening. Our suite of 25 5-25cm2 electrolyzer test stations are full of candidate catalyst materials in various stages of development and optimization. They progress through our larger test cells and stacks as they get closer to market.

06. Iterate

We painstakingly characterized data from years of testing to build a proprietary machine learning model. This cascading model now has 70% accuracy in predicting both activity and durability of catalyst candidates. All of our testing starts here, with prediction - and ends here, with data intake.

Download CDE overview PDF