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Topic Training

What kind of training will we offer?

We are currently working on a master’s degree, a microcredentials program, as well as a series of workshops. Please stay tuned for more information.

Topic Membership

How can I join the Acceleration Consortium?

The Consortium is a diverse, global entity composed of 3 main groups: government, principal investigators (PIs), and industry. Within each, there are many sub-groups, including large enterprises, start-ups, SMEs, investment firms, like-minded organizations and more. What each group has in common is an interest in the discovery, design, and commercialization of new materials and molecules. To learn more, visit our Join page.

What benefits do I get as a Consortium member?

Members gain access to a wide range of opportunities, expertise, technology, and talent, including: 

  • Access to self-driving labs, including open-source software and databases, hardware designs, and support staff 
  • Expert consultations
  • Collaborative and directed pre-competitive research projects
  • Residence and training programs
  • Professional development, including workshops and courses 
  • Access to a talent pipeline with a wide range of cross-disciplinary expertise, including leveraged internships 

Is there a fee to join the Consortium?

The cost of joining the Consortium is dependent on the company size (employees) and the role you play in the lab of the future. For principal investigators (PIs) and global acceleration partners, the only fee is your time spent engaging in Consortium activities. To learn more, visit our Join page.

Why did we decide to form a consortium?

Global issues benefit greatly from global approaches. By convening experts across disciplines, sectors, and geographies, we aim to expedite research translation and commercialization. We are on the edge of a materials innovation paradigm shift, a transformation that cannot happen in isolation. Here is where the whole is greater than the sum of its parts. It’s the groundbreaking work of each of our members around the world that will help us get closer to achieving our ambitious goal of accelerating materials discovery and design.

Topic Materials / Molecules

What are some potential application areas for self-driving labs?

As a platform technology, MAPs are largely material agnostic and can be applied to a wide range of areas that are critical to a healthier, more sustainable world, including: 

  • green products (biodegradable plastics and fibres)
  • electronics (cheaper, higher capacity, eco-friendly leds and wearable devices)
  • energy (renewable energy production and storage)
  • construction and transportation (lighter, stronger, corrosion-resistant alloys, and eco-friendly cement
  • healthcare (antiviral coatings, drug delivery and bio-compatible polymers for regenerative medicine)
  • drugs (molecular design, testing and production of drugs and therapeutics)
  • something entirely new that we have yet to dream up!

Why do we need to accelerate materials and molecular discovery?

The global and urgent need for better materials is never-ending. Cheaper, more sustainable and accessible, and faster to manufacture are required to address major global issues, from pandemics and climate change to waste management. ​​Traditional methods are slow and expensive, whereas self-driving labs can bring planet-saving materials to market faster at a fraction of the cost.

How much does it cost to develop a new material?

On average, it costs $10–100 million to bring a material from ideation to market using conventional materials. Self-driving labs can radically reduce this figure, to as little as $1 million.

Topic Technology

What is a materials acceleration platform (MAP), also known as a self-driving lab?

Materials Acceleration Platforms (MAPs) are a new integrated approach for accelerating scientific discovery. MAPs combine the growing areas of artificial intelligence (AI) and robotics with chemistry and materials science. An AI-driven, adaptive component should be coupled with automated synthesis and characterization for an experiment to be considered a MAP.

Will the digitization and automation of chemistry eliminate job prospects for scientists?

MAPs present a scenario where humans have not been “replaced,” instead they work alongside robotic and AI-powered counterparts. Researchers can hand off tedious hours of trial and error to focus more on designing the objectives and other higher-level analysis. 

How much does it cost to construct a self-driving lab?

It ranges from as little as 100,000-250,000 USD to several million dollars.

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