The growing performances of digital systems, combined with the success of data-driven algorithms, are enormously improving the potential of imaging technologies. That offers new perspectives on nuclear materials safeguards, especially in light of the challenges that future generation reactors will pose.
In recent years, the application of imaging technologies as a powerful asset in the context of international nuclear safeguards is increasing.
The JRC and the scientific community are working to adapt and develop novel techniques for nuclear materials safeguards, tackling the peculiar experimental and algorithmic challenges these applications entail. A multidisciplinary approach is indeed required, merging numerical modeling, data science, and experimental engineering.

Passive gamma emission tomography
One example is the Passive Gamma Emission Tomography (PGET) device, which allows nuclear inspectors to directly image the spatial distribution of active materials in spent fuel assemblies, aiming at detecting potential nuclear material diversion.
The analysis of PGET measurements and the evaluation of its applicability rely on the availability of comprehensive datasets. However, experimental data are expensive and limited: that is why Monte Carlo simulations are used to complement them. However, the computational cost is high (several days for simulating a single acquisition). JRC developed a physics-informed limited-data framework, able to produce high-fidelity PGET simulated data at a fraction of the computational cost, paying a sparing error penalty.

Multi-probe imaging
In the context of active interrogation of materials, multi-probe imaging is revealing as a powerful technique to characterize nuclear materials, even in dynamic conditions. Indeed, due to the different radiation-matter interaction properties, different probes can highlight different materials’ properties.
The JRC is exploring the combination of X-ray and neutron tomography to characterize the spatial distribution of light elements, especially when they are embedded in heavy-closed metallic environments. Here, the experimental work meets the conceptualization and implementation of cutting-edge algorithms to tackle image processing, data merging, and scarce data reconstruction, raising many spin-off applications that find ground beyond safeguards.
Indeed, these approaches proved to be valuable in many civil and industrial applications: one example is the in-situ and in-operando investigation of materials for energy supply, being the electrochemical properties often connected to the distribution and movement of light elements, such as hydrogen and lithium.

Future objectives
Among the ongoing activities, the JRC is studying the feasibility of muon tomography for the reverification of dry casks for long-term storage of nuclear materials. Here, a non-destructive method is mandatory, and the high-energy cosmic muons represent a suitable probe to penetrate the thick and strongly absorbing materials casks are made of, leveraging the deeply penetrating properties of these particles. However, the atmospheric muon flux is such that a single muon passes through an area the size of a human hand per second: again, low-statistics and scarce data reconstruction algorithms will play a crucial role.