SciTransfer
Organization

AACHEN INSTITUTE FOR NUCLEAR TRAINING GMBH (AINT)

German nuclear measurement SME specialising in decommissioning instrumentation, radiological sensing, and radiation safety for hazardous nuclear environments.

Technology SMEenergyDESMENo active H2020 projectsThin data (2/5)
H2020 projects
2
As coordinator
1
Total EC funding
€139K
Unique partners
10
What they do

Their core work

AINT is a small German private company focused on nuclear measurement technology, radiation safety, and nuclear decommissioning support. Their work sits at the intersection of practical nuclear operations and instrumentation — developing and applying measurement tools for radiological environments, including neutron-based elemental analysis and optically stimulated luminescence (OSL) dosimetry. They bring hands-on nuclear expertise to both instrument development projects and larger robotic decommissioning initiatives, where their knowledge of radiation worker safety (ALARA principles) and radiological detection informs system design. The "Training" in their name signals a core competency in translating complex nuclear physics into operational practice for radiation workers and field engineers.

Core expertise

What they specialise in

Nuclear measurement instrumentationprimary
2 projects

NEAT (coordinated, 2018) focused on neutron-based elemental analysis technology; CLEANDEM (2021) involved radiological sensors, nuclear measurements, and OSL detectors in a decommissioning context.

Nuclear decommissioning and dismantling (D&D)primary
1 project

CLEANDEM directly targets unmanned nuclear decommissioning measurements, with AINT contributing radiological detection expertise to a cyber-physical robotic platform.

Radiation worker safety and ALARA compliancesecondary
1 project

CLEANDEM keywords include 'radiation workers exposure' and 'ALARA', indicating AINT's role in minimising human dose during decommissioning operations.

Autonomous and robotic systems for nuclear environmentsemerging
1 project

CLEANDEM introduced cyber-physical systems, digital twin, UGV (unmanned ground vehicle), and robotic arm concepts into AINT's project portfolio for the first time.

Evolution & trajectory

How they've shifted over time

Early focus
Neutron elemental analysis technology
Recent focus
Robotic autonomous nuclear decommissioning

AINT's first H2020 project (NEAT, 2018–2019) was a small SME Phase 1 feasibility study on neutron-based elemental analysis — a classical nuclear measurement technology with applications in materials identification and non-destructive testing. By their second project (CLEANDEM, 2021–2024), the focus had shifted substantially toward autonomous robotic systems for nuclear decommissioning, incorporating digital twins, unmanned ground vehicles, and cyber-physical sensing architectures. This suggests AINT is repositioning from traditional nuclear instrumentation toward the integration of their measurement know-how into remotely operated platforms designed to keep human workers out of high-radiation zones.

AINT is moving toward providing radiation measurement expertise as a module within larger autonomous systems — a direction aligned with the growing need to decommission ageing nuclear facilities across Europe without exposing workers to dose.

Collaboration profile

How they like to work

Role: specialist_contributorReach: regional3 countries collaborated

AINT has both led a project (NEAT, as SME Phase 1 coordinator) and joined as a participant (CLEANDEM), suggesting flexibility in how they engage depending on project scope. With 10 unique partners across only 2 projects, they engage in moderately sized consortia rather than isolated bilateral work. As a small specialist SME, they most likely serve as the nuclear measurement domain expert within larger consortia that provide the systems integration and robotics engineering around them.

AINT has collaborated with 10 unique partners across 3 countries in just two projects — a relatively broad reach for a company of this size and portfolio depth. Their network is European in scope but concentrated, likely reflecting close ties within the nuclear decommissioning and instrumentation community.

Why partner with them

What sets them apart

AINT occupies a rare niche: a private SME that combines nuclear training and operational safety knowledge with active instrument development — a combination more commonly found in large nuclear utilities or national labs. Based near Aachen in the former German industrial heartland, they are well-positioned to serve the European nuclear decommissioning market, which is growing as older reactors reach end-of-life. For consortium builders, AINT offers what large partners often lack: practical field credibility in radiation environments and a direct line to radiation worker safety requirements.

Notable projects

Highlights from their portfolio

  • CLEANDEM
    Their largest and most technically ambitious project — a multi-year Innovation Action combining autonomous robotics, digital twins, and radiological sensing to replace human workers in nuclear decommissioning measurements, signalling a major capability expansion for the company.
  • NEAT
    AINT's only coordinator role in H2020, a SME Phase 1 feasibility study on neutron-based elemental analysis that established their credentials as an instrument development company, not merely a training provider.
Cross-sector capabilities
Security and border control (neutron-based elemental analysis has direct applications in contraband and explosives detection)Manufacturing quality control (non-destructive testing using nuclear measurement methods)Digital and cyber-physical systems (digital twin integration for hazardous environment monitoring)Environmental monitoring (radiological sensing and contamination measurement in post-accident or legacy sites)
Analysis note: Only 2 projects with limited metadata — NEAT carried no keywords, so the early/recent keyword split is entirely one-sided. The profile is plausible but relies partly on reading the organisation name and project titles rather than rich descriptive data. Treat expertise claims as indicative, not confirmed. A third project or access to deliverable abstracts would substantially improve confidence.