For industries that depend on high-performance tools, the materials to build them can't always come from the country that needs them most. So the question becomes whether we can design, characterise, and qualify a substitute faster than a geopolitically constrained supply chain can fail. Thank you to Richard Roberts and @Mining_Beacon for the piece. Link here: lnkd.in/exZ2_qwH We'll be at the @IMARC_Mining and Resources Conference (IMARC) in October, where our Founder, Alain Richardt, will join a panel on how substitution sits alongside mining in a sovereign supply chain. Come and say hello.

We can now discover alternatives to geopolitically constrained materials in weeks instead of years. Getting them into production still takes years. Writing in @ASPI_org's, The Strategist, our founder Alain Richardt makes the case for treating substitution as a strategy in its own right rather than a fallback. aspistrategist.org.au/dont-j…

Yesterday, our Founder, Alain Richardt, sat down with @GarthBray from the @nzherald at the GD1 (Global From Day One) "Believe Bigger" Conference. They discussed how we're discovering synthetic alternatives to reduce reliance on geopolitically constrained supply chains in months, not decades.

A material candidate and a qualified material are not the same thing. A candidate is a prediction. Proposed composition, predicted structure, modelled properties. It has not been synthesised, tested, or qualified. Physical testing remains the ultimate validation. What has changed is how much of the qualification work can be done before a single sample is built. Traditional defence materials qualification takes over a decade. Simulation-first development compresses that to around 2.5 years. Generating candidates is the start of the process. At 2.5 years, materials development becomes a variable that programmes can plan around. Read more here: atomictessellator.com/resear…

We're excited to welcome Edison Florez to the team. Edison brings a rare combination of a PhD in computational chemistry and physics, a deep experience building simulation-driven discovery platforms, and a track record of connecting hard science to commercial outcomes. That last part matters as much as the first. We're building the computational infrastructure for materials discovery. Having someone who has done this from first principles makes us significantly better at it. Welcome, Edison.

Every era of human progress has a #materialsdiscovery at its centre. The Bronze Age. The Silicon Age. We name entire civilisations after the materials they learned to work with. The bottleneck has always been discovery. We're building the infrastructure to remove it.

#SimulationFirst materials development means arriving at physical testing with a small number of high-confidence candidates. Not a wide field of unknowns. The organisations that operate this way are not simply working faster. They are making better decisions earlier, with less capital at risk. #MaterialsDiscovery #AdvancedEngineering

Structural engineers model before they build. Aeronautical engineers run CFD before a prototype enters a wind tunnel. #AdvancedMaterials has traditionally skipped this step because the tools didn't exist to qualify candidates before physical exploration. We're building the computational infrastructure to change that. Learn more here: bit.ly/4dh0Cgq #SimulationFirst #MaterialsEngineering

We've been building something that requires a different kind of thinker. Computational materials infrastructure sits at the intersection of physics, data, and scale. The questions we're asking don't have obvious answers yet, which means the people we need have to be comfortable operating in that space. That's why we're excited to welcome Juliusz Abramczyk (Jules) to the Atomic Tessellator team. Jules brings over a decade of engineering experience across cloud, data, and ML, most recently leading Data and AI at Fullstop.ai and Head of Cloud at XPON Technologies. He holds more Google Cloud certifications than most teams combined, and has spent his career building the kind of infrastructure that turns raw data into genuine intelligence. Whilst Jules' technical depth was impressive, it was his worldview that sealed it. He sees AI as 'a global fabric of computation, memory, and intelligence' and that kind of thinking fits naturally into what we're building. We're here to do work that matters at a civilisational scale. It helps to have people who find that motivating rather than daunting. Welcome, Jules.

The search space for possible #AdvancedMaterials is effectively infinite. Physical experimentation explores a fraction of it. Computation explores orders of magnitude more, at orders of magnitude less cost. The #MaterialsBottleneck is infrastructural, not scientific.

Every engineering challenge eventually becomes a materials challenge. The battery that cannot store enough. The armour that cannot hold. The component that fails under thermal stress. These are not failures of engineering. This is the #MaterialsBottleneck in action - the constraint behind every constraint. #AdvancedMaterials #Engineering

We're Atomic Tessellator (atomictessellator.com/). The materials bottleneck is the hidden constraint on human progress. We built the infrastructure to remove it.

MLIPs. DFT. Ab initio simulation. The science has been advancing for years. What has been missing is the infrastructure to make it accessible, reproducible and deployable within the constraints of real programmes. That is what we are building. #MaterialsScience #ComputationalMaterials