NoMaD · Project

A Search Engine That Helps Companies Find the Right Materials Faster

digitalTestedTRL 5

Imagine you're designing a new battery or a lighter car part, and somewhere in Europe a supercomputer already simulated the perfect material for your needs — but that data is buried in one of dozens of incompatible databases you don't even know exist. NoMaD built a single search engine that pulls together all these scattered simulation results into one place, translates them into a common language, and lets you browse them through a visual interface. Think of it as a Google for materials science data — instead of searching the web, you search millions of computer-simulated material properties to find what works for your product.

By the numbers

consortium partners across Europe

countries represented in the consortium

project deliverables completed

industry partner in consortium

The business problem

What needed solving

Companies developing new products — from smartphones to solar cells to artificial hips — need to find the right materials, and computational simulations generate enormous amounts of data that could help. But this data is scattered across dozens of repositories in incompatible formats, making it nearly impossible for an R&D team to search, compare, or reuse results from different simulation tools. Without a unified way to access this information, companies either duplicate expensive computations or miss existing solutions entirely.

The solution

What was built

The project built a web-based search engine with a graphical user interface for querying materials science simulation data across multiple codes and repositories. They demonstrated this for at least one material class and developed a common data format that converts outputs from leading simulation codes into comparable, searchable records. In total, 25 deliverables were completed including big-data analytics and statistical learning tools.

Audience

Who needs this

Electronics and semiconductor manufacturers screening candidate materials for new componentsBattery and energy storage companies searching for better electrode or electrolyte materialsSpecialty chemical firms running computational campaigns for catalysts or coatingsAutomotive and aerospace companies exploring lighter or stronger structural materialsMaterials informatics startups building AI-driven material discovery tools

Business applications

Who can put this to work

Electronics & Semiconductor Manufacturing

enterprise

Target: Companies developing new electronic components, display technologies, or sensor materials

If you are an electronics manufacturer spending months testing candidate materials for new chip designs or display panels — this project built a searchable database with a web-based GUI that lets you query computational results across multiple simulation codes in one place. Instead of commissioning expensive new simulations from scratch, your R&D team can first check what has already been computed across European research labs, potentially cutting early-stage material screening time significantly.

Battery & Energy Storage

any

Target: Battery makers and energy storage startups looking for better electrode or electrolyte materials

If you are a battery company struggling to identify promising new materials for higher energy density or longer cycle life — NoMaD created a materials encyclopedia with big-data analytics and statistical learning tools. The search engine demonstrated for specific material classes lets your researchers compare properties across metals, inorganic semiconductors, and other material families without needing access to 11 different partner institutions' individual databases.

Chemical & Advanced Materials

mid-size

Target: Specialty chemical companies and materials suppliers developing coatings, catalysts, or composites

If you are a chemical company running computational screening campaigns to find the next high-performance coating or catalyst — this project converted simulation outputs from leading codes into a common format, making results comparable for the first time. With 25 deliverables including a working search engine and graphical interface, your computational chemists can access and visualize data that was previously locked in incompatible formats across 6 countries.

Frequently asked

Quick answers

What would it cost my company to access the NoMaD platform?

The NoMaD repository (nomad-coe.eu) was built as open research infrastructure under a publicly funded project. Based on available project data, the platform provides free access to materials data. Commercial integration or custom analytics built on top of the platform would require separate arrangements with the consortium.

Can this handle the volume of data our industrial R&D team generates?

The platform was designed for petascale computational data, handling outputs from simulations that consume millions of CPU hours daily across HPC centers worldwide. The common data format supports leading simulation codes used across the field, so industrial-scale computational workflows should be compatible.

Who owns the IP, and can we license the tools?

The project was coordinated by Max Planck Society (Germany) under an RIA funding scheme, which typically means results are openly available. The consortium of 11 partners across 6 countries contributed to the platform. Specific licensing terms for commercial use of the analytics tools or data format converters would need to be discussed with the coordinator.

Is this just a research prototype or something we can actually use today?

The project delivered a working web-based graphical user interface and demonstrated the search engine for at least one material class (metals, semiconductors, surfaces, molecules, etc.). The platform at nomad-coe.eu continued operating after the project ended in 2018, suggesting it moved beyond prototype stage.

How does this integrate with simulation codes we already use?

NoMaD was specifically designed to integrate leading computational materials science codes by converting their inputs and outputs into a common format. The consortium included 6 universities and 3 research organizations that use these codes daily, ensuring broad compatibility with the major tools in the field.

Is there any regulatory or compliance advantage to using standardized materials data?

While no specific regulatory requirements are cited in the project data, having traceable computational data in a standardized format supports quality management and reproducibility requirements in regulated industries. The FAIR data principles underlying the platform align with increasing EU requirements for data transparency.

Consortium

Who built it

The NoMaD consortium is heavily research-oriented: 11 partners across 6 countries (Germany, Denmark, Spain, Finland, Ireland, UK), with 6 universities and 3 research organizations forming the core. Only 1 industry partner and 1 SME participated, giving a 9% industry ratio — quite low for direct commercial application. The coordinator, Max Planck Society, is one of Europe's most respected research institutions, which lends scientific credibility but signals this is infrastructure-grade research rather than a market-ready product. For a business looking to use this platform, the strong academic backing means the science is solid, but commercial support and integration services may require additional partnerships beyond the original consortium.

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EVCoordinator · DE
THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGEparticipant · UK
PINTAIL LTDparticipant · IE
AALTO KORKEAKOULUSAATIO SRparticipant · FI
BAYERISCHE AKADEMIE DER WISSENSCHAFTENparticipant · DE
UNIVERSITAT DE BARCELONAparticipant · ES
DANMARKS TEKNISKE UNIVERSITETparticipant · DK
HUMBOLDT-UNIVERSITAET ZU BERLINparticipant · DE
BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACIONparticipant · ES
KING'S COLLEGE LONDONparticipant · UK
CSC-TIETEEN TIETOTEKNIIKAN KESKUS OYparticipant · FI

How to reach the team

Max Planck Society, Germany — search for NoMaD project coordinator at Max Planck for the Fritz Haber Institute or contact via nomad-coe.eu

Order a report on this consortium See MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV profile →

Next steps

Talk to the team behind this work.

Want to explore how computational materials data from NoMaD could accelerate your R&D pipeline? SciTransfer can connect you with the right people on the research team and help translate the platform capabilities into your specific use case.

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