Applications

Application / Materials Science

Quantum in Materials Science.

Designing superconductors, magnets, and materials that don't exist yet.

Every technology sits on a material — semiconductors, magnets, superconductors, polymers. Quantum computers predict material properties from first principles, replacing decades of trial-and-error in the lab.

Every Chip Sits On A Material

Every technology — phones, planes, batteries — is bottlenecked by materials science.

Why quantum, why now.

  • Strongly-correlated electron systems (superconductors, magnets) defy classical simulation.
  • Room-temperature superconductivity would rewrite the entire electric grid.
  • First-principles design collapses R&D timelines from decades to years.

Timeline — past and future.

What already happened, and what's next for quantum materials science.

  1. 1986

    High-temperature superconductors discovered — physics still doesn't fully explain them.

  2. 2019

    Google's Sycamore chip performs quantum supremacy on a random circuit sampling task.

  3. 2020

    IBM simulates lithium hydride — first industrial-scale materials benchmark.

  4. 2023

    Quantinuum + BMW simulate battery cathode fragments.

  5. 2025

    Google Willow enables larger error-corrected materials simulations.

  6. 2028Forecast

    First strongly-correlated material property predicted before lab measurement.

  7. 2032Forecast

    First superconductor discovered via quantum simulation.

  8. 2040Forecast

    Room-temperature superconductor commercialized — transforms grid and transport.

Where it hits.

Superconductors

Predict critical temperatures and design room-temperature candidates.

Magnets

Rare-earth-free permanent magnets for motors and generators.

Polymers

Design plastics that recycle infinitely or biodegrade cleanly.

Semiconductors

Next-gen transistor materials past the end of silicon scaling.

What's already happening.

  • Quantum-simulated small-molecule catalysts at BASF, Merck, Roche.
  • Battery cathode simulation at PsiQuantum + Mercedes.
  • Semiconductor materials research at Samsung, TSMC, Toyota.
  • Quantum-inspired materials informatics platforms at Multiverse Computing and IonQ partners.

Companies in quantum materials science.

Who's actually building here — hardware makers, industry partners, and pure-play startups.

PsiQuantum

Materials-focused FTQC roadmap; Mercedes and SLAC partnerships.

Google Quantum AI

Deepest strongly-correlated materials research portfolio.

IBM Quantum

Materials benchmarks across Qiskit Nature and industrial partners.

Samsung

Semiconductor materials + qubit fabrication research.

Toyota

Battery and magnet materials work with QunaSys, Google, IBM.

BASF

Broadest industrial partnership across chemistry and materials quantum vendors.

Ecosystem highlights

GoogleIBMPsiQuantumToyotaSamsung
Time horizon

First advantage: 3–7 years for strongly-correlated materials.

Interesting corners.

  • Materials is the field where quantum's 'first useful advantage' probably shows up — because classical methods hit fundamental walls, not just compute walls.
  • Strongly-correlated electron systems are the exact regime classical methods fail hardest.
  • The real bottleneck isn't running the simulation — it's translating a materials question into the right quantum algorithm.
  • A single validated result — a new high-Tc superconductor — would justify a decade of quantum investment overnight.
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