Themes and Topics

Improved techniques for the surveillance and characterisation of plant, structures, waste, land and effluents for radiological and chemical contamination. Remote field sensing for contaminated land, buildings, effluents and waste/ residue packages. Improved detectors, such as solid-state alpha cameras for more rapid analysis/more flexible deployment/improved information content.

Innovative tools and techniques to reduce human exposure by enabling measurement or estimation of the radiological, chemical and physical properties of a material/ item/ waste which can be applied throughout a facility lifecycle i.e an operational plant, during Post Operational Clean Out, Deplanting and Demolition and in waste materials/packages. Approaches to ensure representative samples from heterogeneous ‘items’ and hard to reach/access areas (e.g. legacy ponds).

Specifically in the understanding of errors, accuracy and precision and in the confidence levels of ‘decision making’ and/or ‘acceptability criteria’ with respect to (correct) waste categorisation. Seeking pragmatic, implementable approaches to demonstrate confidence in decision making, which may include multiple data inputs (i.e. data fusion approaches to improve confidence).

For example, PFAs (Per- and polyfluoroalkyl compounds). There is particular interest in determining the concentrations of Persistent Organic Pollutants (POPs) in radiologically active samples.

More rapid analysis methodology to support automation, especially in labour-intensive areas of sample preparation and radionuclide separations. This is to improve analysis cost, reduce liquid waste arisings, improve turnaround time and improve supply-chain capacity. A key focus area is improved analysis/assay capabilities for alpha and beta radionuclides.

For example:

• Developments with ICPMS for elemental/radionuclide analysis [either on the front end i.e. (IC-ICPMS) or other chromatographic/resin pre-treatment, or measurement e.g. ICPMS CRIS developments with protocols e.g. tandem ICPMS.
• Developments with other Mass Spec technology e.g. use of AMS to analyse very active material at high dilution.
• Photonics – development of laser technology e.g. LIBS, RAMAN for in-cell or glovebox analysis.
• Novel gamma spectrometry techniques e.g. software or hardware for Compton suppression or coincidence counting, new gamma detection materials or advances with imaging.
• Microfluidics or automated/semi-automated process systems – for radionuclide separation in-lab (fume cupboard/cell/glovebox) or in-situ.
• Artificial intelligence and/ or machine learning – advances in software for improvements in resolving spectra and peak stripping.
• New gaseous sensors e.g. with lower limits of detection (LOD) and ability to identify radionuclides

Improvements in existing non-destructive assay methods e.g. for fuel/fissile material content in cans and other packages. In-line, real-time materials characterisation, e.g. fuel/fissile material content of sludge during transfer/pumping operations or SNM and uranic residues.

• Elemental analysis of highly active materials in sealed containers.Determining the contents of a concrete lined drum without opening it.

Developments in simple universal sampling tools to collect representative samples from solids, liquids or sludges that can be deployed in constrained spaces (e.g. through small apertures) or at height and potentially in high radiation areas.

This challenge explores sustainable strategies for land and groundwater remediation and the reuse of demolition arisings (inclusive of radioactive materials) to achieve a circular economy. It includes research into opportunities and challenges, environmental impacts, and innovative remediation techniques such as biotechnology, chemical treatments, and climate-resilient solutions to ensure long-term environmental protection.

This challenge focuses on understanding how contaminants move, transform, and persist in the environment. It includes research on contaminant migration, radioactive particle behaviour, and long-term environmental changes such as landscape evolution and climate change. Emphasis is placed on mechanisms like diffusion and desorption, and the development of tools to support robust environmental safety cases and development of the understanding to assert control over migrating contaminants.

This challenge focuses on enhancing environmental decision-making by integrating life cycle analysis, and advanced qualitative and quantitative data techniques. It includes the development of tools to manage accumulative uncertainty, improve long-term environmental assessments, and apply AI and machine learning for data interpretation, automation, and historical data analysis, to support land quality and remediation efforts.

1. The condition management of aging assets: material / structure degradation. Degradation of aging steelwork and reinforced concrete.
2. Asset management to support Decommissioning Strategies

1. There is an opportunity to maximise the segregation of waste which is done at the point of generation/ the workface.
2. Segregation of waste to achieve lower waste volumes for disposal e.g. brick contamination.
3. Use of automated systems e.g. conveyor belt systems which allow quicker identification of wastes.  Review the potential to use this technology across the wider NDA estate.

1. Improving cost forecasting and opportunities for innovation to reduce decommissioning costs

1. Large number of tanks / vaults / tubes which are difficult to access and although bulk volumes can be removed there is a need for easy removal of any remaining heels and residues. 
2. The means to penetrate vessels and pipework simply, cheaper, faster and (E.g. From MSMs) in a secure manner

1. Looking at the skills, training and mindset of the people involved within decommissioning
2. Investigating the cultural shift and change in perception from operations to decommissioning.

NDA strategy will see Spent AGR fuel stored in fuel storage ponds for an interim period before final planned disposal in a GDF from 2075 onwards.  This will see interim storage of several decades for the fuel in wet storage.  Current monitoring approaches are based on a campaign of post storage examination where fuel is removed from pond and physically examined and routine monitoring of bulk pond water chemistry.  

The NDA is interested in exploring techniques to monitor and predict future behaviour of fuel cladding / pond infrastructure through a multi-disciplinary approach which would investigate how ROV and sensor advancements could be used to gather data on the physical condition of fuel in-situ during wet storage.  This should also consider how advances in AI and data analytics could be used to process the output from inspections and predict future performance.

Historically, the interaction between metallic uranium and water has been studied with a focus on the bulk metal. Methodologies have investigated the rate of corrosion of the material based upon weight differences, oxide layer growth, or volume / rate of hydrogen gas generation. Whilst these methods have been adequate to provide insight into the rate of change of the material, the quantity of radionuclides released into solution during this process have not been explored. 

There are two areas of interest related to this topic:

• Metallic U leachingTo safely dispose of these materials in a geological disposal facility, it is essential to understand the amounts and rates of radionuclide release during metallic U corrosion in water. To this end, this PhD aims to explore the leaching of metallic U, with a focus on the aqueous chemistry on the system. Ideally, aqueous chemical data will be produced in tandem with the previously established corrosion methods to identify a link between the rate at which radionuclides are released into solution, and the rate at which the bulk metal corrodes.
• Modelling release of C14 during pond storage and disposalCurrent disposal assumptions will assume that all Carbon-14 present in spent Magnox fuel will be released during disposal within a GDF.  To avoid an overly conservative approach to C-14 limits it is important to model where in the lifecycle the release of the radionuclide occurs to ensure that we can take credit for C-14 which is released during interim storage in fuel storage ponds. This project would seek to develop a modelling approach which could model the release of C-14 from uranic Magnox fuel during the lifecycle.    

A key criterion to allow spent nuclear fuel to be safely packaged for disposal is that is conditioned such that any free moisture is limited. Residual water that is carried over in the waste container is subject to radiolysis and excess water could potentially lead to flammable atmospheres and over-pressurisation of the waste package. In principle, this should be straight-forward for spent nuclear fuels that are intact (i.e. their zircaloy or stainless-steel cladding material has not breached); however, it is much less straight-forward for failed fuels, as it is currently not possible to predict how much water remains (i.e. how much is physically/chemically entrained, how does water vapour migrate in a semi-porous, drying environment).

Recent PhD work has looked to understand the drying processes for spent fuels from first principles [1]. Separate to this finite element-based nuclear fuel performance codes, such as BISON [2] have been developed that include modelling fission gas and material release from spent nuclear fuels in accident conditions [3]. This PhD project seeks to build on this experience by applying the fundamental modelling that can be applied to existing fuel performance codes to determine the migration of water in drying environments. 

[1] R. Ros Trujillo, Thermal Modelling of AGR Fuel Drying, University of Bristol, 2021–2025. 

[2] Idaho National Laboratory, BISON: https://mooseframework.inl.gov/bison/ 

[3] M.W.D. Cooper, C. Matthews, and D.A. Andersson, Development of bubble evolution model for new mechanistic transient fission gas release capability in BISON, LA-UR-23-24769, April 2023.

Development of optimised or innovative processes for immobilisation of radioactive wastes for storage and disposal, including use of encapsulants.  Such processes should be selected based upon candidate wastes, availability of encapsulant material (where appropriate), sustainability, feasibility of application at full scale (including identification of secondary wastes) and compatibility of wasteform properties with waste containers and disposal concepts (including effect of evolution of wasteform properties).

Development of optimised or innovative materials for the construction of waste containers for packaging of radioactive waste for storage and disposal.  Such materials should be selected based upon candidate wasteforms, availability of material, sustainability, feasibility of application at full scale, compatibility with interim storage concepts (where applicable) and compatibility with disposal concepts (including requirements for durability of integrity).

Development of optimised or innovative techniques to monitor radioactive waste packages during interim storage.  Such techniques should be selected based upon candidate waste package types (including evolution processes to be monitored that may represent a threat to disposability), feasibility of application at full scale, compatibility with storage concepts (including prevailing levels of radiation where applicable), and feasibility of data acquisition, analysis and retention.

Focused on climate risks and resilience for the NDA group. This model should support collaborative decision-making within the group and serve as a foundation for targeted research into how various choices and external factors influence system-wide climate resilience. Relevant regulation and standards should be considered in the development.

Some civil decommissioning activities will require the construction of substantial infrastructure such as new intermediate storage facilities and eventual disposal facilities. Research is required into how to minimise the carbon footprint of these structures. This must be done while maintaining the necessary engineering assurance for their operational lifespan.

Nuclear waste packages often have a high CO2e either through the use of energy intensive construction materials for the outer packaging (e.g. steel) or via the waste matrix itself (e.g. grout). These materials are likely to become more expensive or less freely available in the future, as well as contributing to the carbon footprint of the NDA group and our supply chain. Research is required into alternative, low CO2e materials for use in waste packaging that can meet the necessary storage and disposal requirements. This research should consider how to maximise recycling into the process, e.g. through the use of recycled concrete or additives such as graphite.

Aligned with the characterisation theme, the NDA is considering the management of waste packages in storage. There is an interest understanding the feasibility of novel methods that other industries are exploring that could be used to detect, quantify, and manage the contents of cementitious waste packages in storage.

Creating a psychologically safe environment within complex organisations is essential for continued success, and this is further enhanced within the context of complex nuclear decommissioning activities.

The extent to which organisational members feel psychologically able to speak up, express their views and challenge the status quo can impact safety related decision making and levels of participation. Research is sought into the mechanisms involved in the creation of high levels of psychological safety and how that influences the way that individuals frame, carry out and respond to organisational requirements. (For example, carrying out safety investigations, reporting of near misses, developing a culture of innovation and the psychological safety barrier to collaboration.)

Being a ‘Learning Organisation’ informs how a business continually improves itself through using its own experiences and those of others to create its own meaningful knowledge. This is transferred across the organisation to positively impact safety and delivery performance. Further study is required into the attributes and requirements needed in order to install a strong learning organisation, specifically within the high hazard, high reliability context of nuclear decommissioning.

Nuclear decommissioning environments are characterised by inherently subtractive processes, where success is measured by dismantling, reduction, and remediation rather than construction or expansion. These activities frequently occur in physically demanding and high-hazard settings.

Given these unique operational conditions, is there a need for distinct cultural frameworks to support effective performance and organisational resilience? Furthermore, what are the implications for leadership strategies, the articulation of expectations, and the implicit dimensions of the psychological contract between employers and employees within the decommissioning context?

Working in a nuclear decommissioning environment is a unique experience where success is linked to subtractive rather than additive activities, often within physically challenging work environments. When working in challenging nuclear decommissioning and remediation environments, what are the specific elements that organisations need to be mindful of when planning and implementing cultural and behavioural strategies? This may include potential impact on morale, recruitment & retention, leadership style and levels of compliance.

The nuclear industry faces a huge loss of knowledge as the workforce ages and retires, each taking decades of knowledge and experience with them. NDA are interested in research addressing how this technical information is best captured, stored and made readily accessible to those who may find it useful. How can the information augment existing resources such as the nuclear archive, and possible future object collection?

Furthermore, can this structure be used to capture oral histories of the people and communities affected by the civil nuclear industry? How is this ethnographic information best captured, recorded and made available to those who want to access it, and how can we apply this methodology to legacy audio-visual collections?

Seek to integrate the full range of future decommissioning costs into business case development. Traditional financial models often underestimate or exclude critical long-term factors such as the cost of carbon emissions, social value impacts, asset care obligations, environmental remediation and enhancement, and heritage preservation. By integrating these dimensions, the study aims to develop a more holistic and ethically grounded valuation methodology that supports sustainable decision-making. The research will draw on interdisciplinary approaches from environmental economics, systems engineering, and public policy to propose tools and metrics that reflect the true legacy costs of nuclear infrastructure.

Explore innovative filtration techniques, including novel media for the selective removal of particulate including radionuclides from aqueous radioactive waste streams, and modelling of filtration efficacy (e.g. sand bed filters).

Study the application of ion exchange materials for the removal of specific radionuclides from active effluent, including optimisation of Ion Exchange performance and regeneration processes. Consider disposal implications, e.g., for streams with competing ions , bespoke pre-treatments or materials. Consider future changing streams and radionuclide demands including effluents arising from Remediation. Removal of non-radionuclides of environmental concern.

Develop sensor technologies and remote monitoring systems for real time monitoring of radioactive effluent streams, including in-line monitoring of chemical properties (pH, oxidation potential, etc.) and consider including self-monitoring/calibrating systems.

Investigate methods for recovering resources such as energy, water contributing to a circular economy concept.

Explore and optimise AOPs like UV, ozone etc. to enhance their efficiency in breaking down pollutants in effluent streams. The engineering of the technology has previously been a barrier to application so innovation in this area would be useful.

Explore the use of nanomaterials such as nanocomposites for targeted removal of specific pollutants enhancing the treatment efficiency. 

Develop and optimise membrane separation processes such as reverse osmosis, nanofiltration for selective removal of contaminants from effluents.

Develop and optimise innovative techniques for tritium abatement.

Explore by what mechanisms does the fouling of pipes arise in active effluent treatment systems and methods to remediate them. Develop designs to prevent pipe fouling. Traditionally pipe fouling has been separated into two categories (1) chemical deposition and (2) biofilms. These have historically been treated as separate problems however, chemical deposition may lead to biofilm formation and vice versa and these are not fully understood currently. How do they interact.

Potential for DNA characterisation to improve understanding.

At Sellafield site, there are alpha-contaminated environments which require decommissioning. The current baseline approach for this involves cell entries by human operators, in order to take characterisation measurements, perform decontamination operations, dismantling work, and waste handling & export. These are manually-intensive tasks with people working in Air-Fed Suits / respirators. New robotic technologies could improve on this decommissioning work – this could be via solutions which enhance the capabilities of the operator (enabling their activities to be safer), or to allow the operator to control the decommissioning from outside of the contaminated area.

With over 100km of pipelines across the Sellafield site there is an increasing need to routinely inspect these assets. It is important to understand their condition, identify any defects, and manage the risk of failure. Internal inspection of narrow pipework can be particularly challenging due to bends, corrosion debris, lack of lighting, and the length of pipes. The ability to get high-quality images of the pipework supports Sellafield Ltd’s mission to manage assets and decommission the site safely and cost-effectively.

This covers a range of areas but fundamentally comes down to substantiation. Includes elements like:

Certainty over robot positioning (e.g. where the robot thinks it is, where it wants to be and where it actually is). 

Confidence in decision making (operator out of loop, operator oversight of suggested actions, operator driven actions).

How do we make robots that are safe around people/vulnerable items of plant (e.g. degraded gloveboxes).

We know a number of our gloveboxes are simply too large to transport and will need to be decommissioning in-situ. Past attempts to do this have resulting in significant contamination of surrounding areas. This is not an option going forward.

Most effective decontamination agents include complexing or chelating agents, which bond to metal ions and make them good at removing uranium/plutonium from surfaces. However, these agents also increase radionuclide mobility in a repository environment and hence raise challenges about waste stream acceptance which prevents us from using them. We are interested if these are approaches that could render these agents inactive and therefore more suitable for disposal.

Robotic techniques for the application of said agents

Potentially extension of above, linking into practically of application and removal of agents –

Decontam agents are key to allowing hands on decommissioning so interested in anything that supports it.

The process of moving waste materials from source to endpoint can often be highly repetitive. The logistics of moving the materials may mean that the reach of quadrupedal and tracked robotic platforms cannot reach sufficient high to retrieve or deposit waste materials in containers. High accuracy and repeatability bipedal robots may hold a specific niche area in nuclear decommissioning in the future.

The NDA wants to ensure that our mission outcomes and the journey to deliver them are sustainable. Different decommissioning sectors share this objective. Research is required to understand how the concepts of reuse and recycling can be applied to waste streams, particularly those that are shared across different industries, such that the interplay between sustainability benefits and the economic case is understood.

Recognising the cross-industry similarities between the decommissioning missions of the NDA and the oil and gas community, we would be interested to receive research proposals that build on these synergies and address common challenges. More information on the challenges surrounding decommissioning in oil and gas can be found here:

Research – The National Decommissioning Centre (ukndc.com)

Whilst this element of call has not been formulated in conjunction with the Net Zero Technology Centre or the National Decommissioning Centre, any relevant proposals will be shared and assessed together with these organisations.

Reducing both hazard and risk are core drivers in NDA’s mission. Developing improved models to utilise the power of Artificial Intelligence (AI) in accessing, understanding and running multiple scenarios to potentially output suggestions for risk predictions is an incredible opportunity. The research may cover the data types and values of human created archived data and how AI can deeply analyse the outputs over many decades in the past. Research across many industries on how predictive analytics are being enabled would also be of great value. Also, understanding the leading AI data models and how AI can learn from other AI deployments across aligned organisations and the implications of those outputs. The outputs would also be interesting across the ever-increasing horizon scanning predictive data processing.

For projects relating to applications of artificial intelligence, please refer to and consider the sub-section entitled: “Artificial Intelligence and Other Projects Requiring Access to NDA Owned or Managed Data” under the “Additional Considerations” tab when applying to the call.

One of the impacts of policy responses to the Covid-19 pandemic has been the increased level economic uncertainty about the future. For all sectors there is a large increase in uncertainty, particularly around spending plans and revenue projections. Research into new models and how we exploit data to help show long term future risk exposures and areas for management are needed. How multiple models could be created to give various confidence level aligned outputs coupled with new analytics platforms would be of great interest. Developing new innovative quantitative models to estimate the likelihood and potential impact of long-term future risks in new ways would add great value to the planning we have in the nuclear industry which is mapping out activities over 100+ years into the future.

Asset interventions and investments are critical to the overall timeline and cost of NDA mission.  NDA are interested to identify better ways to consistently understand key facets that contribute to the overall planning process, recognising the role of aging assets and the challenges presented from nuclear facilities.  Further research is required to identify opportunities for:

• Effective Estimating of Asset Interventions – in particular generation of cost &/or schedule estimates for common/standard asset interventions across the group.
• Asset Degradation Modelling – targeted modelling specific to NDA group assets, their environment and use.
• Cross-industry learning of typical asset interventions (for nuclear and non-nuclear assets), including application on heavily regulated environments/sites.
• Innovative solutions to address key and systematic challenges from life extension of ageing nuclear assets.

For this research, the PhD researcher could be seconded into the NDA Asset Management & Continuous Improvement (AMCI) team to allow access to real data and real problems and help identify solutions this will include working with Operating Companies on specific and target issues and solutions.

When mission delivery targets are missed by the NDA Group of Operating Companies, costs and risks can increase. Focus and culture within the industry can negatively impact the required performance  where nuclear is perceived as uniquely complex, despite similarities with other sectors (such as oil and gas). The NDA would like to identify better ways to achieve a performance focused culture for mission delivery improvement.

For this research, the PhD researcher could be seconded into the NDA Asset Management & Continuous Improvement (AMCI) team to allow access to real data and real problems and help identify solutions.

Metal-Organic Frameworks (MOFs) and Covalent-Organic Frameworks (COFs) have recently been identified as materials of interest for nuclear decommissioning due to their ability to target and sequester a wide range of radionuclides in both liquid and gaseous media. They could offer alternatives to traditional methods of radionuclide capture and storage which can face limitations in efficiency, selectivity, and cost.

Potential MOF/COF use cases identified in previous research include:

1. Pertechnetate Sequestration: ability to sequester pertechnetate ions from contaminated groundwater.
2. Gas Abatement and Recovery: capture and recovery of fission product inert gases and gaseous iodine isotopes.
3. Switchable Properties for Waste Processing: the potential of MOFs with switchable adsorption properties for enhanced waste processing and radionuclide separation.
4. Tritium Separation and Storage: the feasibility of using MOFs for the efficient separation and storage of tritium.

We are interested in receiving proposals that build on these options, examine other potential use cases, investigate the applications of MOFs or COFs with the highest potential impact and explore potential challenges to MOF stability.

Due to the vast parameter space associated with Metal-Organic Frameworks (MOFs), computational approaches are an essential aspect of MOF design, performance prediction and screening. We are interested in receiving proposals that develop computational approaches to analyse MOF compositions with the aim of discovering those with enhanced stability and performance for nuclear applications such as radionuclide capture and separation.

Areas of potential research focus include:

1. High-Throughput Screening: Development and use of high-throughput computational screening methods to identify promising MOF candidates for specific nuclear applications.
2. Machine Learning Models: Creation and training of machine learning models to predict the stability and adsorption properties of MOFs under different conditions relevant to nuclear waste management.
3. Quantum Mechanical Methods: Application of density functional theory (DFT) and other quantum mechanical methods to fine-tune the properties of MOFs for enhanced radionuclide adsorption.
4. Simulation of Environmental Conditions: Use of molecular dynamics (MD) and Monte Carlo (MC) simulations to assess the performance of MOFs under various environmental conditions, including radiation and chemical exposure.

Artificial intelligence (AI) is a growing topic in the nuclear sector and research into its application within NDA’s decommissioning mission requires special consideration when applying to the NDA bursary call.

• Access to NDA owned data must be identified as a risk within proposals. Applicants are expected to engage with potential sponsors to ensure that either data can be provided or that secondments into NDA group can be established to facilitate access.
• Where a secondment is required, please ensure this is correctly costed for within the proposal including travel and subsistence, security clearances and hosting/ sponsorship. Please also consider what facilities/ equipment/ software may be required as these may not be available within the NDA SLC or host organisation.
• There is currently no agreed approach to regulate AI within the nuclear sector, although ONR have done some exploratory work. Applicants may wish to consider how their solution could contribute to regulator acceptance. This could include engaging publicly with organisations and regulators in nuclear.
• Applicants should consider where the PhD can go beyond the state of the art. There have been several examples where AI has either been implemented or demonstrated by consultants or the supply chain within SLC’s. It is important that any application focused on AI is aware of this research and that engagement with NDA during the call process is essential to understand this landscape.

If there are further questions on this section applicants are advised to contact nda_phd@uknnl.com who will then facilitate discussions with the appropriate sponsor within NDA group.

Applicants will have the opportunity to include an element of collaboration with research institutions in the United States in their research proposals on topics of mutual interest to NDA and US DoE. The Project Lead for the proposal should be a UK academic and will need to have an established relationship with the US academic/research institution with whom the collaboration is proposed. The proposal should include separate costs for any secondments and/or work in the US, and any associated supervision costs. It should also indicate how overseas working would be managed. It should indicate whether the collaboration is essential or desirable to the proposal and the associated benefit of the collaboration. If work in the proposal is deemed relevant to US nuclear decommissioning challenges, the US DoE may fund part of the proposal.

The NDA would welcome proposals where a PhD project would benefit from gaining access to UK research facilities for handling radioactive material. Applicants should include the estimated costs associated with undertaking R&D using radioactive materials in the proposal where a realistic estimate can be made (e.g. based on previous experience, or through discussion with the facility operator), or alternatively to state the nature and likely duration of the work they would like to undertake highlighting whether the active work would be essential to the success of the project or would just add value. If the proposed work involving radioactive materials is judged to bring significant benefits to the project, then the NDA will consider funding this work in addition to the PhD project scope. Details of the proposed active work and information about costings and/or duration can be submitted as part of the “Project Management” section in the application form.

For specific guidance, please contact nda_phd@uknnl.com.

Recognising the cross-industry similarities between the decommissioning missions of the NDA and the oil and gas community, NDA would be interested to receive research proposals that build on these synergies and address common challenges. More information on the challenges surrounding decommissioning in oil and gas can be found here:

Research – The National Decommissioning Centre (ukndc.com)

Whilst this element of call has not been formulated in conjunction with the Oil and Gas Technology Centre or the National Decommissioning Centre, any relevant proposals will be shared and assessed together with these organisations.