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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Composition, Activity, and Stability of IrO x Oxygen Evolution Reaction Electrocatalysts

The oxygen evolution reaction (OER) is integral to several electrochemical energy conversion and storage technologies, including carbon dioxide reduction to value added fuels, nitrogen reduction to ammonia, reversible fuel cells, rechargeable metal−air batteries, and water electrolysis to produce hydrogen. Iridium oxide (IrO x ) is widely recognized as the benchmark OER catalyst for acidic environments. Despite widespread use of IrO x catalysts, most notably in proton-exchange membrane water electrolyzers (PEMWEs), a comprehensive understanding of the physicochemical properties of commercial catalysts and the impact of these properties on both the activity and stability of these catalysts is lacking. Here, we study commercial IrO x catalysts with different physicochemical properties, three nominally considered amorphous and three rutile, to elucidate how structural and compositional variations affect OER activity and stability. Utilizing standardized aqueous electrochemical protocols, time-resolved dissolution quantification using inductively-coupled plasma mass spectrometry, and physicochemical characterization, including multiple synchrotron X-ray techniques, we systematically correlate catalyst properties with OER performance and degradation behavior aided by principal component analysis (PCA). Our results demonstrate the general trend of amorphous IrO x having higher intrinsic activity but limited stability and crystalline rutile IrO 2 having lower activity but enhanced stability against dissolution. The trends within the amorphous and rutile catalyst groups correlate with inherent material properties, including phase composition and structure, crystallinity, particle size, surface area, and surface structure/chemistry. Notably, we identify a rutile catalyst with the largest crystallite/ domain sizes, moderate surface area, a small fraction of hydrous phase, and a favorable pore structure (trimodal distributions of pore sizes ranging from 2−5 nm) that exhibits the best balance between activity and stability among the six catalysts studied here. These findings illustrate a fundamental structure-governed trade-off between activity and stability and highlight the critical role of surface chemistry modification and structure engineering in IrO x catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ternary Phosphides Ba M 2 P 2 : Tailoring Crystal and Electronic Structures Enables Highly Efficient HER Electrocatalysis

Binary transition metal phosphides and their solid solutions have emerged as promising hydrogen evolution reaction (HER) catalysts. Although many research endeavors have adopted strategies to vary compositions to optimize catalytic performance, they mainly focus on binary structures, which represent only a small fraction of the abundant phase space of structure types among transition metal phosphides. Here, the largely unexplored class of ternary and multinary ordered phosphides in catalysis comprises two or more metals with quite different chemical nature, concealing the structure–property relationships essential for advancing catalyst design. Here, we explored phosphides crystallizing in one of the most abundant ordered intermetallic structure types, —the ThCr 2 Si 2 type, —where square nets of 3d transition metal M and P atoms are separated by layers of electropositive Ba cations. Four ternary BaM 2 P 2 (M = Fe, Fe/Cu, Fe/Ni, Ni) catalysts were synthesized and characterized. BaNi 2 P 2 showed high HER activity in acidic electrolyte, which required an overpotential, η 10 , of only 62 mV to drive current density j = –10 mA/cm 2 and high stability with a potential drop rate of 0.25 mV/h. BaNi 2 P 2 outperformed other Ni-based catalysts, such as Ni 2 P and Ni 5 P 4 . Notably, at current densities above –170 mA/cm 2 , BaNi 2 P 2 outperformed the standard Pt electrode measured under identical conditions. Electronic structure analysis revealed a volcano-type activity trend among the four BaM 2 P 2 catalysts based on their d-band center positions, highlighting the role of electropositive Ba cations in shifting the Ni-3d orbitals into an optimal position.

BaNi2P2↗
DOE OSTI2023

A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

High Entropy Alloys (HEAs) are composed of more than one principal element and constitute a major paradigm in metals research. The HEA space is vast and an exhaustive exploration is improbable. Therefore, a thorough estimation of the phases present in the HEA is of paramount importance for alloy design. Machine Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly. A deep neural network (DNN) model for the elemental system of: Mn, Ni, Fe, Al, Cr, Nb, and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using Thermo-Calc. The features list used for the neural network is developed based on literature and freely available databases. A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked features. The final regressor has a coefficient of determination ( r 2 ) greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy design. The DNN developed constitutes an example of an emulator that can be used in fast, real-time materials discovery/design tasks.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Long-term multi-wavelength study of 1ES 0647+250

The BL Lac object 1ES 0647+250 is one of the few distant γ-ray emitting blazars detected at very high energies (VHEs; &100 GeV) during a non-flaring state. It was detected with the MAGIC telescopes during a period of low activity in the years 2009-2011 as well as during three flaring activities in the years 2014, 2019, and 2020, with the highest VHE flux in the last epoch. An extensive multi-instrument data set was collected as part of several coordinated observing campaigns over these years. We aim to characterise the long-term multi-band flux variability of 1ES 0647+250, as well as its broadband spectral energy distribution (SED) during four distinct activity states selected in four different epochs, in order to constrain the physical parameters of the blazar emission region under certain assumptions. We evaluated the variability and correlation of the emission in the different energy bands with the fractional variability and the Z transformed discrete correlation function, as well as its spectral evolution in X-rays and γ rays. Owing to the controversy in the redshift measurements of 1ES 0647+250 reported in the literature, we also estimated its distance in an indirect manner through a comparison of the GeV and TeV spectra from simultaneous observations with Fermi-LAT and MAGIC during the strongest flaring activity detected to date. Moreover, we interpret the SEDs from the four distinct activity states within the framework of one-component and two-component leptonic models, proposing specific scenarios that are able to reproduce the available multi-instrument data. We find significant long-term variability, especially in X-rays and VHE γ rays. Furthermore, significant (3-4σ) correlations were found between the radio, optical, and high-energy (HE) γ-ray fluxes, with the radio emission delayed by about ~400 days with respect to the optical and γ-ray bands. The spectral analysis reveals a harder-when-brighter trend during the non-flaring state in the X-ray domain. However, no clear patterns were observed for either the enhanced states or the HE (30 MeV < E < 100 GeV) and VHE γ-ray emission of the source. The indirect estimation of the redshift yielded a value of z = 0.45 ± 0.05, which is compatible with some of the values reported in the literature. The SEDs related to the low-activity state and the three flaring states of 1ES 0647+250 can be described reasonably well with the both one-component and two-component leptonic scenarios. However, the long-term correlations indicate the need for an additional radio-producing region located about 3.6 pc downstream from the gamma-ray producing region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗
DOE OSTI2021

Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Platooning has the potential to reduce greenhouse gas missions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. For real world application and accurate return on investment for potential adopters, non-uniform platoons and the impacts of grade and disturbances on a platoon’s fuel economy must also be characterized. This study investigates the fuel economy of a heterogeneous four-truck platoon on a closed test track. Tests were run for one hour at a speed of 45 mph. The trucks used for this study are two 2015 Peterbilt 579’s with a Cummins ISX15 and a Paccar MX-13, and two 2009 Freightliner M915A5’s, one armored and the other unarmored. Many analysis methodologies were leveraged to describe and compare the fuel data, including lap-wise and track-segment analysis. The methodology for dividing the data into laps is described in detail. The influence of other factors beyond the aerodynamics of platooning is discussed. CAN fuel rate analysis showed excellent agreement with previous experimental trends for two and three-truck platoons. In general, the indicated fuel economy benefits in this study were 5-11% for following vehicles and 0-4% for the lead vehicle in platoon relative to their baseline fuel consumption. On a cumulative basis, all platoons saved fuel, ranging from 6% to 8% versus the sum of the standalone trucks’ fuel consumption. The practical implications of the fuel economy results are discussed, as well as avenues for future research. Introduction and Motivation platooning is controlled coordination of two or more vehicles in a convoy, sometimes called CACC (Coordinated or Cooperative Adaptive Cruise Control). The distance between vehicles in a platoon can be controlled tightly at no additional fatigue to the driver. Platooning vehicles can also respond quickly to braking events of the leader, much more quickly than the typical human driver’s reaction time of 1-1.5 s. Therefore, vehicles in a platoon can follow each other much more closely than would usually be considered a safe following distance under human operation. It is implied that under very close following conditions, platooning technology must be extremely robust before it is safe for wide-scale implementation. Platooning is under investigation as a fuel-saving technology. Close-following significantly reduces aerodynamic drag for both leading and trailing vehicles. According to the NRC in 2010, aerodynamic drag represents roughly half of a Class-8 truck’s on-highway fuel usage, meaning a 20% reduction in drag roughly equals a 10% reduction in fuel usage, if all other sources of energy loss remain equal (i.e. accessory, rolling resistance, drivetrain, braking). It is by aerodynamics that platooning saves fuel. At risk of oversimplifying the aerodynamics, following (or trailing) vehicles experience reduced wind velocity due to shielding, and the leading vehicles experience an increased aft pressure, especially at distances closer than 75’ (23 m).

greenhouse gas emissions, truck platoon, heavy-dut↗
DOE OSTI2026

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessment of the Pan-Arctic Accelerated Rate of Sea Ice Decline in CMIP6 Historical Simulations

Abstract Arctic sea ice loss in response to a warming climate is assessed in 42 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Sea ice observations show a significant acceleration in the rate of decline commencing near the turn of the twenty-first century. It is our assertion that state-of-the-art climate models should qualitatively reflect this accelerated trend within the limitations of internal variability and observational uncertainty. Our analysis shows that individual CMIP6 simulations of sea ice depict a wide range of model spread on biases and anomaly trends both across models and among their ensemble members. While the CMIP6 multimodel mean captures the observed sea ice area (SIA) decline relatively well, an individual model’s ability to represent the acceleration in sea ice decline remains a challenge. Seventeen (40%) out of 42 CMIP6 models and 37 (13%) out of the total 286 ensemble members reasonably capture the observed trends and acceleration in SIA decline. In addition, a larger ensemble size appears to increase the odds for a model to include at least one ensemble member skillfully representing the accelerated SIA trends. Simulations of sea ice volume (SIV) show much larger spread and uncertainty than SIA; however, due to limited availability of sea ice thickness data, these are not as well constrained by observations. Finally, we find that models with more ocean heat transport simulate larger sea ice declines, which suggests an emergent constraint in CMIP6 ensembles. This relationship points to the need for better understanding and modeling of ice–ocean interactions, especially with respect to frazil ice growth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Time–series Analysis of Volume Change at Brady Hot Springs, Nevada, USA using Geodetic Data from 2003 – 2018

Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time–series analysis of each of the 1656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time–series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. Here, the rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.

58 GEOSCIENCES↗
DOE OSTI2023

Analysis of human invasive cytotrophoblasts demonstrates mosaic aneuploidy

A total of 24 chromosome-specific fluorescence in situ hybridization probes for interphase nucleus analysis were developed to determine the chromosomal content of individual human invasive cytotrophoblasts derived from in vitro cultured assays. At least 75% of invasive cytotrophoblasts were hyperdiploid and the total number of chromosomes ranged from 47 to 61. The results also demonstrated that these hyperdiploid invasive cytotrophoblasts showed significant heterogeneity. The most copy number gains were observed for chromosomes 13, 14, 15, 19, 21, and 22 with average copy number greater than 2.3. A parallel study using primary invasive cytotrophoblasts also showed a similar trend of copy number changes. Conclusively, 24-chromosome analysis of human non-proliferating cytotrophoblasts (interphase nuclei) was achieved. Hyperdiploidy and chromosomal heterogeneity without endoduplication in invasive cytotrophoblasts may suggest a selective advantage for invasion and short lifespan during normal placental development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A meta-evaluation of the quality of reporting and execution in ecological meta-analyses

Quantitatively summarizing results from a collection of primary studies with meta-analysis can help answer ecological questions and identify knowledge gaps. The accuracy of the answers depends on the quality of the meta-analysis. We reviewed the literature assessing the quality of ecological meta-analyses to evaluate current practices and highlight areas that need improvement. From each of the 18 review papers that evaluated the quality of meta-analyses, we calculated the percentage of meta-analyses that met criteria related to specific steps taken in the meta-analysis process (i.e., execution) and the clarity with which those steps were articulated (i.e., reporting). We also re-evaluated all the meta-analyses available from Pappalardo et al. to extract new information on ten additional criteria and to assess how the meta-analyses recognized and addressed non-independence. In general, we observed better performance for criteria related to reporting than for criteria related to execution; however, there was a wide variation among criteria and meta-analyses. Meta-analyses had low compliance with regard to correcting for phylogenetic non-independence, exploring temporal trends in effect sizes, and conducting a multifactorial analysis of moderators (i.e., explanatory variables). In addition, although most meta-analyses included multiple effect sizes per study, only 66% acknowledged some type of non-independence. The types of non-independence reported were most often related to the design of the original experiment (e.g., the use of a shared control) than to other sources (e.g., phylogeny). We suggest that providing specific training and encouraging authors to follow the PRISMA EcoEvo checklist recently developed by O’Dea et al. can improve the quality of ecological meta-analyses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Technoeconomic Analysis (TEA)

Techno-economic analysis (TEA) for the DuraMAT Consortium includes the following areas: linking solar photovoltaic (PV) technology trends to reliability implications; providing a framework to calculate technology costs, yielding insights useful for research decision-making, proposals, technology selection, and publications; and examining technology tradeoffs considering lifecycle project economics. This poster highlights results from the first and second iterations of the DuraMAT Technology Scouting reports as well as the updated Simplified PV Levelized Cost of Energy (LCOE) Calculator.

14 SOLAR ENERGY↗
DOE OSTI2022

Statistics on magnetic properties of Co compounds: A database-driven method for discovering Co-based ferromagnets

The search for new ferromagnetic compounds is often targeted at known structure families, particularly those containing iron, cobalt, and manganese. Here, we propose a method to expand this search to lesser-known structure types, using a database of experimental Curie and Néel temperatures. This study, in particular, illustrates the case of compounds containing the element cobalt, and we demonstrate how the use of such a database can lead to the discovery of ferromagnetic materials that had previously been overlooked. We report statistics from a literature survey of the magnetic properties of Co-based compounds with more than 33 at. % Co. We classify more than 13 000 compounds by structure type, cobalt content, and magnetic ground state. From these data, compounds TaCo 2 Ga, La 6 Co 13 Bi, and Nd 2 Co 3 were identified as potential ferromagnets, and we confirm their ferromagnetic ordering theoretically via first-principles calculations and experimentally via synthesis and characterization measurements. In addition, the analysis is focused on the collection of data trends and discovery of ferromagnetic materials with easy-axis magnetic anisotropy. Both known ferromagnetic materials with unknown magnetic anisotropy, and unstudied compounds were considered. From the subset of known ferromagnets with unknown anisotropy, the compound Co 2 Mg was synthesized, characterized, and determined to have easy-axis magnetic anisotropy at room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermodynamic Trends for Reduction of CO by Molecular Complexes

Selective reduction of CO 2 into fuels and chemical feedstocks is highly desirable to reduce our dependence on fossil fuels. Most molecular catalysts afford 2e – reduction products, such as CO or HCO 2 – , as opposed to more reduced products. Here we present an analysis of the thermodynamic limitations for reduction of the CO ligand in the form of a series of isostructural group 6 carbonyl complexes, Cp*M(CO) 3 (P(OMe) 3 ) + (M = Cr, Mo, and W). Additionally, the free energy for stepwise transfer of a hydride (H – ) and a proton (H + ) to the CO ligand, resulting in a hydroxycarbene (CHOH) complex, was measured by equilibration with H – /H + donors and acceptors with known hydricity or acidity. Together, these two reaction steps are equivalent to a net addition of H 2 across the CO ligand. A large and unfavorable free energy for H 2 addition (Δ G ° H2 ) was measured for all three complexes and decreases in the order Cr > Mo > W. The trend for these complexes is opposite to the trend previously reported for group 7 carbonyl complexes, for which Δ G ° H2 decreases moving up the group, Re > Mn. Computational analysis indicates the trends can be described in terms of electrostatic effects, where a low Δ G ° H2 is obtained in complexes that balance the atomic charges of the M–C≡O fragment of the complex. These findings can be used to design metal carbonyl complexes with a more energetically accessible H 2 addition, which will facilitate the development of molecular catalysts for reduction of CO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

ILLICIT TRANSIT INTERDICTION GLOBAL ANALYSIS

This study aims to enhance the security of radioactive materials during transport by analyzing commonalities in cargo thefts conducted by non-state groups such as thieves and terrorists. This research focuses on identifying patterns and trends in the methods used to steal high-value cargo, with the goal of applying these insights to improve transport security of radioactive materials. Key questions addressed include the frequency of specific tools, techniques, and insider involvement in thefts, as well as the use of weapons, electronic jamming equipment, and specialized tools. Findings will inform security design improvements and industry practices to mitigate vulnerabilities. The study involves a comprehensive review of literature and case studies, utilizing data sources from 2018 to 2023. Articles will be selected based on their relevance to thefts of valuable cargo in transit, with a focus on incidents involving non-state actors. The methodology will include statistical and inferential analysis to identify trends, with results visualized through pie charts, frequency analyses, and terrain maps. The discussion will highlight the implications of findings and provide actionable recommendations for strengthening security measures. Limitations such as data availability and reporting inconsistencies will be acknowledged. Suggestions for future improvements will be constructed using existing case studies and expert feedback. The study’s outcomes aim to raise awareness within the industry, inform policy decisions, and enhance security protocols for radioactive material transport. Metrics for impact include the potential publication of findings, presentations at conferences to raise awareness, and the subsequent actions taken by stakeholders based on the research. By identifying trends and vulnerabilities and suggesting improvements, this research contributes to preventing the illicit use of nuclear and radiological materials.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗