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AI-Assisted Discovery and Synthesis of Novel Perovskite Materials

Research & Development

What it collects

Operational data
Anonymized data
  • Public datasets containing known perovskite material properties and synthesis parameters, used to train and inform the AI discovery and optimization pipeline.
Run by
National Research Council Canada (NRC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

Research & Development

This system uses generative AI and Bayesian optimization to help researchers discover new perovskite materials and determine optimal synthesis parameters faster than traditional trial-and-error methods. It is used internally by Government of Canada scientists at the National Research Council and does not process personal information. The system is currently in development and was built in collaboration with the University of Ottawa under the AI for Design Challenge Program.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Public datasets containing known perovskite material properties and synthesis parameters, used to train and inform the AI discovery and optimization pipeline.

Processing

Optimization
  • Bayesian Optimization is used to identify optimal synthesis parameters for ball milling, minimizing the number of experimental trials needed to achieve targeted material properties.

What it does

Creating (Generative AI)
Human decides
  • Generative AI is used to propose novel perovskite material candidates with targeted properties. Researchers review and decide which candidates to pursue experimentally.
Deciding (Analytical AI)
Human decides
  • Bayesian Optimization is used to identify optimal ball milling synthesis parameters. The system scores and ranks parameter configurations, with researchers making final experimental decisions.

Outputs

A recommendation or prediction
Anonymized data
  • The system produces candidate novel perovskite material formulations and recommended synthesis parameters (e.g. ball milling settings) for researchers to evaluate and test experimentally.

Run by

National Research Council Canada (NRC)
  • Federal government research institution responsible for developing and deploying this AI pipeline for perovskite material discovery and synthesis, in collaboration with the University of Ottawa.

Government of Canada AI and Data Use Register — 2526-NRC-CNRC-020

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me
  • This system is used internally by Government of Canada employees at NRC. Outputs are not available to members of the public.
Available to the accountable organization
  • Outputs are available to NRC scientists and Government of Canada employees working on perovskite research within the AI for Design Challenge Program.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Algorithmic TransparencyThe Government of Canada has disclosed AI use in this system. As this system is used by GC employees for internal research and does not affect members of the public, formal individual rights are not directly applicable; however, general transparency is provided through the public AI Register.

Risks and safeguards

No risks or safeguards have been published for this system yet.