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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Sustainability of water uses in managed hydrosystems: human- and climate-induced changes for the mid-21st century

This paper assesses the sustainability of planned water uses in mesoscale river basins under multiple climate change scenarios, and contributes to determining the possible causes of unsustainability. We propose an assessment grounded in real-world water management issues, with water management scenarios built in collaboration with local water agencies. Furthermore, we present an analysis through indicators that relate to management goals and present the implications of climate uncertainty for our results, furthering the significance of our study for water management. A modeling framework integrating hydro-climatic and human dynamics and accounting for interactions between resource and demand was applied in two basins of different scales and with contrasting water uses: the Herault (2500 km 2 , France) and the Ebro (85 000 km 2 , Spain) basins. Natural streamflow was evaluated using a conceptual hydrological model. A demand-driven reservoir management model was designed to account for streamflow regulations from the main dams. Human water demand was estimated from time series of demographic, socioeconomic and climatic data. Environmental flows were accounted for by defining streamflow thresholds under which withdrawals were strictly limited. Finally indicators comparing water availability to demand at strategic resource and demand nodes were computed. This framework was applied under different combinations of climatic and water use scenarios for the mid-21st to differentiate the impacts of climate- and human-induced changes on streamflow and water balance. Results showed that objective monthly environmental flows would be guaranteed in current climate conditions in both basins, yet in several areas this could imply limiting human water uses more than once every 5 years. The impact of the tested climate projections on both water availability and demand could question the water allocations and environmental requirements currently planned for the coming decades. Water shortages for human use could become more frequent and intense, and the pressure on water resources and aquatic ecosystems could intensify. Furthermore, the causes of unsustainability vary across sub-basins and scenarios, and in most areas results are highly dependent on the climate change scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

System and method for design and optimization of grid connected photovoltaic power plant with multiple photovoltaic module technologies

A system and method of using one or more DC-DC/DC-AC converters and/or alternative devices allows strings of multiple module technologies to coexist within the same PV power plant. A computing (optimization) framework estimates the percentage allocation of PV power plant capacity to selected PV module technologies. The framework and its supporting components considers irradiation, temperature, spectral profiles, cost and other practical constraints to achieve the lowest levelized cost of electricity, maximum output and minimum system cost. The system and method can function using any device enabling distributed maximum power point tracking at the module, string or combiner level.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessing VQLS for Fluid Dynamics on a Hybrid Quantum-HPC Stack

Recent advances in quantum linear solvers offer a promising direction for accelerating extreme scientific computations such as fluid dynamics. However, the deep and complex circuits required by many quantum algorithms limit their practical use on current quantum hardware. The Variational Quantum Linear Solver (VQLS) presents a viable alternative for near-term quantum devices (NISQ), and initial efforts have explored its application to select fluid dynamics problems. In this work, we evaluate the use of VQLS for canonical fluid dynamics problems, aiming to identify pathways for generalizing its implementation across a broader class of systems. We analyze the impact of various circuit ansatz and classical optimizers on solution quality and convergence behavior. Furthermore, we assess the algorithm's feasibility within a hybrid quantum–high-performance computing (HPC) framework by porting it to QFw, a state-of-the-art quantum-HPC software stack. 11This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US DOE under Contract No. DE-AC05-00OR22725.

Gopalakrishnan Meena, Murali [ORNL] (ORCID:0000000↗
DOE OSTI2025

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗
DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Density Functional Tight Binding Insights into Plasmonic Silver–Platinum Nanoparticles and Alloys for Enhanced Photocatalysis

Developing accurate and efficient Slater-Koster (SK) tight-binding parameter sets is essential for quantum plasmonic studies of alloyed metal nanoparticles, as conventional time dependent density functional theory (TD-DFT) calculations are computationally prohibitive for larger clusters. In this work, we develop and validate density functional tight binding (DFTB) parameter sets for both ground state (GS-SK) and excited state (ES-SK) calculations to study the structural, electronic, and optical properties of silver (Ag), platinum (Pt), and Ag–Pt nanoalloys. Our investigation of the ground state properties demonstrates that the GS-SK parameters enable DFTB to closely reproduce the electronic structures of platinum clusters with diverse sizes and geometries – showing qualitative agreement with DFT for density of states (DOS) profiles and energy levels. The ES-SK parameters accurately describe excited-state properties compared to TD-DFT reference calculations, including the broad, featureless absorption profiles of Pt that are dominated by interband transitions. Using the ES-SK parameters within a real-time TD-DFTB framework, we compute size-dependent optical absorption spectra of Ag, Pt and Ag-Pt nanocubes containing up to 1099 atoms (size ∼4.18 nm). A detailed study of Ag–Pt and Pt-Ag core–shell nanoparticles shows quenching of the Ag plasmon resonance even at monolayer coverage for Ag-Pt, but not for Pt-Ag. We also show how to define submonolayer Ag-core Pt-shell cubic structures that have similar optical properties to those generated experimentally for much larger particles, which offers potential for describing plasmon-enhanced photocatalysis. Collectively, the GS-SK and ES-SK parameter sets provide an accurate, computationally efficient approach for modeling the complex optical and electronic behavior of noble–transition metal nanostructures and their alloys.

SPR↗
DOE OSTI2026

Computational Design of Interlayers for Thermally Stable Compositionally Graded Coatings on Nickel Alloys

To extend the service life of Ni-based superalloys, refractory metal coatings are often used. However, direct bonding between metals with dissimilar crystal structure promotes brittle intermetallic phase formation. This work presents a computational thermodynamic framework for high throughput design of functionally graded interlayers to suppress deleterious phases that may form at the interlayer. The Thermo-Calc software package was used to screen candidate metallic interlayer elements based on stability of solid-solution phases. Vanadium was identified as a promising interlayer due to its consistent suppression of intermetallic phases. Temperature-dependent phase diagram mapping between 600 and 1000 °C guided selection of a compositional pathway that significantly reduced intermetallic formation compared to directly joining the Ni-based and Nb refractory alloys. Time–temperature–transformation analysis was performed to assess whether equilibrium-predicted phases are kinetically accessible along regions of the graded path where non-solid-solution phases are not fully suppressed. The methodology was further applied to additional Ni-based alloy and coating systems, illustrating its transferability as an approach for rapid computational design of graded interlayers in dissimilar high-temperature materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Bismuth Metal–Organic Framework as a Contrast Agent for X-ray Computed Tomography

A new bismuth metal–organic framework (MOF), bismuth-NU901 (Bi-NU-901), featuring the scu topology and a pore with a diameter of ~11 Å, was solvothermally synthesized, and its use as an X-ray computed tomography (CT) contrast agent was tested. X-ray CT is a common diagnostic method used in the medical field. Inside the body, contrast media enhance the distinction between tissues and organs of similar density. Bi-NU-901 consists of eight connected Bi 6 nodes and tetratopic 1,3,5,8-( p -benzoate)pyrene linkers (TBAPy). Numerous material characterization studies including powder X-ray diffraction (PXRD), scanning transmission electron microscopy (STEM), and DFT pore size distribution support the scu structure. Additionally, given the framework’s high density of nontoxic heavy atoms, Bi-NU-901 was evaluated as an X-ray computed tomography (CT) agent. Importantly, in vitro studies revealed this new bismuth MOF demonstrates p7 times better contrast intensity compared to a zirconium MOF featuring the same topology and ~14 times better contrast than a commercially available CT contrast agent. Furthermore these results suggest bismuth MOFs may be promising CT contrast agents.

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

Energy-efficient scientific computing using chemical reservoirs

The rapid growth of computing demands driven by scientific computing, data analytics, and artificial intelligence (AI) advancements has exposed the limitations of traditional digital processing systems. These systems are nearing physical energy barriers, making significant gains in energy efficiency increasingly unattainable. As we advance toward post-exascale computing, disruptive approaches are critical to overcoming these limitations. Among emerging analog solutions, biochemical computing offers a transformative path for achieving orders-of-magnitude improvements in energy efficiency. By leveraging the natural optimization capabilities of chemical reaction networks (CRNs), biochemical systems have the potential to meet high-performance computing needs through natural scalability. However, numerous challenges remain, including theoretical limitations in mapping computational problems to CRNs and practical barriers in implementing biochemical computing devices. In this paper, we present a framework for chemical computation using biochemical systems and introduce key components of our approach for energy-efficient scientific computing. We showcase the feasibility of this framework by solving a system of ordinary differential equations by emulating a chemical reservoir device, demonstrating its potential for addressing modern computing challenges. This work lays a foundational step toward harnessing the computational power of chemistry to design energy-efficient, scalable, high-performance next-generation computing systems.

Johnson, Connah G. M. [Pacific Northwest National ↗
DOE OSTI2013

Simulating Collisions for Hydrokinetic Turbines

Evaluations of blade-strike on an axial-flow Marine Hydrokinetic turbine were conducted using a conventional methodology as well as an alternative modeling approach proposed in the present document. The proposed methodology integrates the following components into a Computational Fluid Dynamics (CFD) model: (i) advanced eddy-resolving flow simulations, (ii) ambient turbulence based on field data, (iii) moving turbine blades in highly transient flows, and (iv) Lagrangian particles to mimic the potential fish pathways. The sensitivity of blade-strike prob- ability to the following conditions was also evaluated: (i) to the turbulent environment, (ii) to fish size and (iii) to mean stream flow velocity. The proposed methodology provided fraction of collisions and offered the capability of analyzing the causal relationships between the flow environment and resulting strikes on rotating blades. Overall, the conventional methodology largely overestimates the probability of strike, and lacks the ability to produce potential fish and aquatic biota trajectories as they interact with the rotating turbine. By using a set of experimental correlations of exposure-response of living fish colliding on moving blades, the occurrence, frequency and intensity of the particle collisions was next used to calculate the survival rate of fish crossing the MHK turbine. This step indicated survival rates always greater than 98%. Although the proposed CFD framework is computationally more expensive, it provides the advantage of evaluating multiple mechanisms of stress and injury of hydrokinetic turbine devices on fish.

CFD↗
DOE OSTI2021

Mechanical analysis of heterogeneous materials with higher-order parameters

Abstract Even though heterogeneous porous materials are widely used in a variety of engineering and scientific fields, such as aerospace, energy-storage technology, and bio-engineering, the relationship between effective material properties of porous materials and their underlying morphology is still not fully understood. To contribute to this knowledge gap, this paper adopts a higher-order asymptotic homogenization method to numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. Specifically, we use the second-order scheme that is an extension of the first-order computational homogenization framework, where a generalized continuum enables us to introduce length scale into the material constitutive law and capture both pore size and pore distribution. Through several numerical case studies with different combinations of porosity, pore shapes, and distributions, we systematically studied the relationship between the underlying morphology and effective mechanical properties. The results highlight the necessity of higher-order homogenization in understanding the mechanical properties and reveal that higher-order parameters are required to capture the role of realistic pore morphologies on effective mechanical properties. Furthermore, for specific pore shapes, higher-order parameters exhibit dominant influence over the first-order continuum.

42 ENGINEERING↗
DOE OSTI2017

Worldline construction of a covariant chiral kinetic theory

Here, we discuss a novel worldline framework for computations of the chiral magnetic effect (CME) in ultrarelativistic heavy-ion collisions. Starting from the fermion determinant in the QCD effective action, we show explicitly how its real part can be expressed as a supersymmetric worldline action of spinning, colored, Grassmannian particles in background fields. Restricting ourselves for simplicity to spinning particles, we demonstrate how their constrained Hamiltonian dynamics arises for both massless and massive particles. In a semiclassical limit, this gives rise to the covariant generalization of the Bargmann-Michel-Telegdi equation; the derivation of the corresponding Wong equations for colored particles is straightforward. In a previous paper [N. Mueller and R. Venugopalan, arXiv:1701.03331.], we outlined how Berry’s phase arises in a nonrelativistic adiabatic limit for massive particles. We extend the discussion here to systems with a finite chemical potential. We discuss a path integral formulation of the relative phase in the fermion determinant that places it on the same footing as the real part. We construct the corresponding anomalous worldline axial-vector current and show in detail how the chiral anomaly appears. Our work provides a systematic framework for a relativistic kinetic theory of chiral fermions in the fluctuating topological backgrounds that generate the CME in a deconfined quark-gluon plasma. Finally, we outline some further applications of this framework in many-body systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

The Lorenzo–Hartley’s function for fractional calculus and its applications pertaining to fractional order modelling of anomalous relaxation in dielectrics

Considering the applications and a great significance of the study pertaining to generalized functions in applied sciences, the author investigated the Lorenzo–Hartley’s function which is a generalization of classical functions widely used in fractional calculus. The Laplace transform pairs are derived and the requirements for the Lorenzo–Hartley’s function G{sub ν,μ,δ}(a,c,t) to be completely monotonic (for t>0) are investigated. The author has shown the applications of this generalized function to describe the relaxation models, particularly in dielectrics. The Lorenzo–Hartley’s function G{sub ν,μ,δ}(a,c,t) of a real variable t is considered to investigate a computable mathematical framework for standard Debye and non-Debye relaxation processes in dielectric materials. The non-negative spectral distribution function is obtained for the corresponding response function. It is also demonstrated that the classical models like Cole–Cole (C–C), Davidson–Cole (D–C), and Havriliak–Negami (H–N) for non-Debye relaxation and standard Debye relaxation are the particular cases of the Lorenzo–Hartley’s function. Some of the study cases are also worked out to visualize the effects of variations of parameters on the response function and corresponding spectral distribution function. A generalized and unified fractional relaxation differential equation which governs response functions for classical dielectrics models pertaining to non-Debye relaxation (C–C, D–C, and H–N) is also established in the present investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Panda: A Compiler Framework for Concurrent CPU $+$ GPU Execution of 3D Stencil Computations on GPU-accelerated Supercomputers

We present a new compiler framework for truly heterogeneous 3D stencil computation on GPU clusters. Our framework consists of a simple directive-based programming model and a tightly integrated source-to-source compiler. Annotated with a small number of directives, sequential stencil C codes can be automatically parallelized for large-scale GPU clusters. The most distinctive feature of the compiler is its capability to generate hybrid MPI$+$ CUDA$+$ OpenMP code that uses concurrent CPU$+$ GPU computing to unleash the full potential of powerful GPU clusters. The auto-generated hybrid codes hide the overhead of various data motion by overlapping them with computation. Test results on the Titan supercomputer and the Wilkes cluster show that auto-translated codes can achieve about 90 % of the performance of highly optimized handwritten codes, for both a simple stencil benchmark and a real-world application in cardiac modeling. The user-friendliness and performance of our domain-specific compiler framework allow harnessing the full power of GPU-accelerated supercomputing without painstaking coding effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Monte Carlo Hauser-Feshbach computer code system to model nuclear reactions: YAHFC

A computer program framework, YAHFC, to model low-energy nuclear reactions is presented. The framework allows for reactions with incident particles ranging from protons/neutrons to alphas and is designed to address reactions that ultimately lead to the formation of compound nuclear systems that then decay statistically as outlined in concepts of Hauser and Feshbach. Additionally, instead of a reaction, it is also possible to model the decay of a nuclear system with an initial excitation and population. The code models nuclear decays with a Monte Carlo process that tracks the decay of each state. This allows for an exact representation of the spectra for all emitted particles in each of the final exit channels and the possibility of generating reaction data for simulation purposes. The program is interfaced with the optical model code system FRESCOX to calculate transmission coefficients as well as the effects of coupled channels and other direct excitations via the distorted wave Born approximation (DWBA). Modules are included to account for nuclear processes such as width corrections, pre-equilibrium emission, and fission. The program is controlled by a series of input commands and while a set of input parameters exists for each projectile and target, the input commands allow for complete control over each input parameter. Extensive data files are produced and a program is provided that converts YAHFC data files into nuclear data library entries in the generalized nuclear data structure (GNDS).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Exploring the impacts of physics and resolution on aqua-planet simulations from a nonhydrostatic global variable-resolution modeling framework

Advances in computing resources are gradually moving regional and global numerical forecasting simulations towards sub-10 km resolution, but global high resolution climate simulations remain a challenge. The non-hydrostatic Model for Prediction Across Scales (MPAS) provides a global framework to achieve very high resolution using regional mesh refinement. Previous studies using the hydrostatic version of MPAS (H-MPAS) with the physics parameterizations of Community Atmosphere Model version 4 (CAM4) found notable resolution dependent behaviors. This study revisits the resolution sensitivity using the non-hydrostatic version of MPAS (NH-MPAS) with both CAM4 and CAM5 physics. A series of aqua-planet simulations at global quasi-uniform resolutions ranging from 240 km to 30 km and global variable resolution simulations with a regional mesh refinement of 30 km resolution over the tropics are analyzed, with a primary focus on the distinct characteristics of NH-MPAS in simulating precipitation, clouds, and large-scale circulation features compared to H-MPAS-CAM4. The resolution sensitivity of total precipitation and column integrated moisture in NH-MPAS is smaller than that in H-MPAS-CAM4. This contributes importantly to the reduced resolution sensitivity of large-scale circulation features such as the inter-tropical convergence zone and Hadley circulation in NH-MPAS compared to H-MPAS. In addition, NH-MPAS shows almost no resolution sensitivity in the simulated westerly jet, in contrast to the obvious poleward shift in H-MPAS with increasing resolution, which is partly explained by differences in the hyperdiffusion coefficients used in the two models that influence wave activity. With the reduced resolution sensitivity, simulations in the refined region of the NH-MPAS global variable resolution configuration exhibit zonally symmetric features that are more comparable to the quasi-uniform high-resolution simulations than those from H-MPAS that displays zonal asymmetry in simulations inside the refined region. Overall, NH-MPAS with CAM5 physics shows less resolution sensitivity compared to CAM4. These results provide a reference for future studies to further explore the use of NH-MPAS for high-resolution climate simulations in idealized and realistic configurations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

WE-H-207A-01: Computational Evaluation of High-Resolution 18F Positron Imaging Using Radioluminescence Microscopy with Lu2O3: Eu Thin-Film Scintillator

Purpose: Radioluminescence microscopy, an emerging and powerful tool for high resolution beta imaging, has been applied to molecular imaging of cellular metabolism to understand tumor biology. A novel thin-film (10 µm thickness) scintillator made of Lu{sub 2}O{sub 3}: Eu has been developed to enhance the system performance. However the advances of radioluminescence imaging with Lu{sub 2}O{sub 3}scintillator compared with that using conventional scintillator have not been explored theoretically to date. To validate the advantages of the thin-film scintillator, this study uses a novel computational simulation framework to evaluate the performance of radioluminescence microscopy using both conventional and thin-film scintillators. Methods: Numerical models for different stages of positron imaging are established. Positron from {sup 18}F passing through the scintillator and its neighbor structures are modeled by Monte-Carlo simulation using Geant4. The propagation and focus of photons by the microscope are modeled by convolution with a depth-varying point spread function generated by the Gibson-Lanni model. Photons focused on the detector plane are then captured and converted into electronic signals by an electron multiplication (EM) CCD camera, which is described by a photosensor model considering various noises and charge amplification. Results: The performance metrics of radioluminescence imaging with a thin-film Lu{sub 2}O{sub 3} and conventional CdWO{sub 4} scintillator are compared, including spatial resolution, sensitivity, positron track area and intensity. The spatial resolution of Lu{sub 2}O{sub 3} system can achieve 10 µm maximally, a 12 µm enhancement from that obtained from CdWO{sub 4} system. Meanwhile, the system with Lu{sub 2}O{sub 3} scintillator can provide a higher mean sensitivity: 40% compared with that (21.5%) obtained from CdWO{sub 4} system. Moreover, the simulation results are in good agreement with previous experimental measurements. Conclusion: This study provides a new theoretical understanding of our imaging system and has the potential to promote the development of radioluminescence microscopy for more reliable and robust application on the functional imaging of delicate biological structures. The authors acknowledge funding from NIH grant R01CA186275 and SBIR grant 1R43GM110888-01.

60 APPLIED LIFE SCIENCES↗