Our Vision: Redesigning Materials for a Sustainable Future

The energy transition is fundamentally a materials transition. Every solar panel, battery, and fuel cell depends on materials that must be designed, synthesized, and optimized at unprecedented speed and scale.

Yet our approach to materials design remains trapped in the past—focusing on single scales, single metrics, idealized compounds—while knowing we face a systems problem that demands systems solutions.

We believe learning from data can transform this process, making it efficient enough to address humanity's sustainability challenges.

The Opportunity

We stand at a unique moment in history. Climate change demands rapid deployment of clean energy technologies, but traditional materials discovery takes decades. We can't afford to wait.

Machine learning offers an unprecedented opportunity to accelerate materials discovery by orders of magnitude. We can predict properties across scales, optimize multiple objectives simultaneously, and design for real-world conditions rather than idealized laboratories.

Our Mission

Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it's the only thing that ever has.

Margaret Mead

For most transformative changes in history, the majority stood on the sidelines while small, dedicated groups drove progress. We believe we can be such a group.

We refuse to become mere service providers applying machine learning to whatever materials problems others bring us. While collaboration and mutual learning are valuable, our mission demands more: we must pioneer new ways of thinking about materials, data, and discovery itself.

We will develop the computational tools, theoretical frameworks, and experimental approaches that make sustainable materials design possible.

Why Us, Why Now

We are scientists with the privilege of education, resources, and freedom. Society has invested in us precisely for moments like this—when fundamental challenges demand breakthrough solutions.

The current trajectory isn't sufficient. Incremental improvements in existing approaches won't deliver the materials we need at the speed we need them.

The stars are there to reach for them.

We choose to reach.

Group Evolution

I do not aim for large growth in the number of people. I have found that in our field, the feedback loops are very fast, and I want to be in a position where I can be involved in the research process. And I feel that I can add most value when I have time to think deeply about the research problems. This sets a natural limit to the size of the group and something in the order of 7--12 people will be what I aim for in the next few years.

I do, however, anticipate that the way we do things will continuously change. I want us to keep a mentality of continuous improvement, where we are always looking for ways to do things better.