Matter Machine Technologies
Inorganic materials discovery

Discovering new materials. Grounded in science. Guided by AI.

Matter Machine has been established to leverage deep experimental synthesis, and materials characterization expertise coupled to AI guided prediction tools that has been demonstrated to be at the forefront of the discovery of new inorganic materials.

The grand challenge of inorganic materials discovery lies in the chasm between AI guided prediction to synthesis - PTSG the prediction to synthesis gap.

Matter Machine is uniquely positioned as it comes from the other end of the discovery spectrum starting with deep expertise in synthesis and characterization of properties – that expertise is harnessed to deliver targeted AI guided prediction.

Explore our approach

A University of Liverpool spinout

Decorative background: a field of chemical element symbols that periodically resolves into real inorganic compounds. Two of them, lithium silicon sulfide iodide (Li7Si2S7I) and bismuth oxide selenide chloride (Bi4O4SeCl2), come from foundational academic research at the University of Liverpool. They are not Matter Machine Technologies product results.

What we do

New possibilities, made into materials.

We work on the discovery of inorganic materials: the physical substances whose composition and structure enable useful functions, from catalysts to components for batteries. Our approach connects digital tools with practical chemistry expertise, helping to identify promising novel candidates and then turning them into materials that can be synthesized, understood and measured in the laboratory.

Why it matters

Progress depends on what materials can do.

Matter Machine Technologies’ mission is to accelerate the discovery of inorganic materials needed for societal challenges in energy and sustainability in the next decade.

The Matter Machine Technologies (MMT) technology stack delivers a dramatic acceleration of the pace of innovation in the discovery of inorganic materials.

Watch on YouTube, 2:15: The Power of 10X: Using Materials Innovation to Reach Net Zero (opens in a new tab)
The Power of 10X: Using Materials Innovation to Reach Net ZeroVideo by the University of Liverpool.
An integrated approach

Beyond prediction. Into the laboratory.

A predicted candidate material is a starting point, not a finished discovery. We integrate the capabilities needed to connect a scientific idea with a real material and measured evidence.

  1. 01

    Expertise sets the direction

    Deep chemical understanding frames the direction of our innovation work and guides how AI and physics-based tools are used.

  2. 02

    Synthesis makes it real

    Laboratory experimentation tests promising ideas, using Workflow Engineering™ to ensure the highest efficiency lab work, using automated workflows where appropriate.

  3. 03

    Measurement closes the loop

    Structure and property measurements establish what a material does and inform the next discovery cycle.

How the approach works

Foundational academic research

Discovery of Crystalline Inorganic Solids in the Digital Age

Acc. Chem. Res. 2025University of Liverpool

Read the paper in Accounts of Chemical Research

Summarizing two decades of experience, this paper describes the discovery of novel crystalline inorganic solids through computational support combined with experimental validation. Throughout, expert human assessment remains central to evaluating true advances and novelty.

The Matter Machine Technologies tech-stack is built on this proven digital-to-lab workflow.

Read the full summary of the paper
Leadership

The people behind
Matter Machine Technologies.

Scientific discovery and the experience to translate it into real-world opportunity.

  • Prof Matthew Rosseinsky

    OBE FRS

    Founder & Director

    Chair of Inorganic Chemistry at the University of Liverpool. His work brings together digital tools, machine learning and automation with experimental synthesis to discover advanced functional materials.

    Read full biography of Professor Matthew Rosseinsky

  • Dr Gordon Sanghera

    CBE FRS

    Co-Founder & Director

    A biotechnology entrepreneur and chemist leading the Matter Machine commercialization strategy. As co-founder and former CEO of Oxford Nanopore, he brings experience in translating scientific innovation and scaling a deep-technology business.

    Read full biography of Dr Gordon Sanghera

  • Prof Matt Reed

    Co-founder and Strategic Advisor

    Professor Matt Reed is Strategic Program Director for Advanced Materials at the University of Liverpool’s Materials Innovation Factory (MIF), where he develops strategic innovation partnerships between academia, industry and government.

    Read full biography of Professor Matt Reed
Start a conversation

Let’s explore what’s possible.

Interested in inorganic materials discovery? We welcome conversations about scientific collaboration and the potential to turn new materials into useful technologies.

Discuss a collaboration

Founder & Director

Prof Matthew Rosseinsky

OBE FRS

Professor Matthew Rosseinsky OBE FRS is Chair of Inorganic Chemistry at the University of Liverpool. His work brings together digital tools, machine learning and automation with experimental synthesis to discover advanced functional materials.

He earned a degree and a DPhil in Chemistry from the University of Oxford in 1990, then worked at AT&T Bell Laboratories before becoming University Lecturer in Chemistry at the University of Oxford in 1992. He moved to Liverpool in 1999. His research interests span a wide range of functional properties including optical, electronic, magnetic, catalytic and porous materials for applications including energy generation and storage, superconductivity, sustainable manufacturing and information technology.

A central theme of his work is the relationship between a material’s composition, structure and properties: using scientific understanding to guide the creation of materials in the laboratory. His career-long aim is to translate computer-guided materials chemistry into practical technological solutions. By developing AI-guided workflows that accelerate experimental discovery, his group fuses learning from data at scale with the expert insight needed to discover differentiated materials in practice.

He was elected a Fellow of the Royal Society in 2008, and became a Royal Society Research Professor in 2013. He has received many international awards, most recently the Basolo Medal of the American Chemical Society Chicago Section in 2022 and the 2024 George B. Kistiakowsky Prize Lecture at Harvard University. He received the 2023 Eni Energy Frontiers Award for the digital design and discovery of next-generation energy materials from the President of Italy. He was recognized in the 2024 King’s Birthday Honours List as an Officer of the Order of the British Empire (OBE) for services to materials chemistry research and innovation. In 2025, he was awarded the Royal Medal of the Royal Society by the King for “pioneering contributions to the design and discovery of materials, changing our understanding of synthesis to create function with digital tools.”

University of Liverpool profile

Co-Founder & Director

Dr Gordon Sanghera

CBE FRS

Dr Gordon Sanghera CBE FRS is a biotechnology entrepreneur and chemist who leads commercialization strategy for Matter Machine Technologies. He co-founded Oxford Nanopore Technologies and served as its Chief Executive Officer for 21 years, leading the business from an Oxford University spinout to its listing on the London Stock Exchange in October 2021.

Earlier in his career, he worked at MediSense, contributing to the development of blood glucose monitoring technologies. The business was acquired by Abbott Laboratories in 1996. He has spent much of his career advancing bioelectronic platforms for glucose monitoring and DNA sequencing.

Under his leadership, Oxford Nanopore pioneered portable, real-time sequencing devices used in genomics, healthcare research and environmental science. This experience of taking scientific technologies from early development to broader use informs his focus on commercialization at Matter Machine Technologies.

Gordon was appointed a CBE for contributions to science and innovation. In July 2026, he was elected a Fellow of the Royal Society in recognition of his pioneering contributions to biotechnology and genomic science.

Royal Society profile

Co-founder and Strategic Advisor

Prof Matt Reed

Professor Matt Reed is Strategic Program Director for Advanced Materials at the University of Liverpool’s Materials Innovation Factory (MIF), where he develops strategic innovation partnerships between academia, industry and government.

A chemist and data scientist by background, Matt holds an Executive MBA in Technology Management from Chalmers University of Technology, Sweden. He has nearly 40 years’ senior R&D leadership experience, including 10 years with Shell and 27 years with Unilever, in UK, European and global roles. His work has resulted in scientific publications, patents, three co-authored books and the co-founding of five companies. He has also advised UK and EU bodies on advanced measurement science.

At Unilever, Matt led its £22m investment in the MIF and its global university Open Innovation strategy. He subsequently secured a £15m UK Government Local Innovation Partnership Grant to establish the University of Liverpool’s AI Materials Hub for Innovation (AIM-HI).

Born and based in Liverpool, Matt co-founded LYVA Labs in 2021 to support innovation and economic growth in the Liverpool City Region. LYVA Labs has since helped leverage more than £60m of investment and grant funding into Liverpool-based innovative companies.

Foundational academic research

Discovery of Crystalline Inorganic Solids in the Digital Age

The central premise of the paper is that computational predictions yield candidates for laboratory exploration, not discoveries in themselves. A new material is only “discovered” when it has been physically realized in the lab, and the measured properties are used to locate this new material in the context of previously known and understood materials.

Rather than using computational models merely to substitute elements into known parent structures (which is valuable, but does not create breakthrough novelty), this tutorial paper outlines a four-step digital-to-lab workflow that is designed to discover entirely new chemical spaces and crystal structures that deliver outstanding new properties. These steps are:

  1. Prioritize candidate chemistries using bespoke Machine Learning tools,
  2. Target compositions using novel crystal structure prediction tools,
  3. Use physics informed models to evaluate whether candidate compositions and structures can be synthesized in the lab, and
  4. Experimentally realize the new materials and characterize their structures using high-resolution measurement tools.
Read the paper in Accounts of Chemical Research