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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 OSTI2025

Direct Feed High-Level Waste APPS Model Glass Testing (DFHLW APPS) Matrix, Phase 2

This report summarizes the data collected during the batching and melting of a second matrix of Direct Feed High-Level Waste (DFHLW) glasses generated using the preliminary enhanced waste glass models (EWG2.5) and the Britton and Anderson (2024) preliminary DFHLW feed vector. The purpose of these glasses is two-fold: 1. Validate EWG2.5 glass calculations being used in the Aspen Process Performance Simulation (APPS) model. 2. Evaluate and ultimately improve the glass property models and formulation methods used for design of DFHLW glasses as part of an iterative process of data collection and model refinement. Some of the 16 APPS2 glasses tested did not satisfy all target property constraints due to the limited data on DFHLW glass supporting the EWG2.5 models. • One glass, APPS2-10, formed nepheline on canister centerline cooling (CCC) heat-treatment and failed the product consistency test (PCT) response limits. This glass also had high B and Cr release rates for the toxicity characteristic leaching procedure (TCLP). All other glasses were found to satisfy the PCT and TCLP constraints for both quenched and CCC samples. • One glass, APPS2-08, had higher than acceptable viscosity due to magnetite crystallization. • One glass, APPS2-09, formed greater than 2 vol% crystals at 950 °C. As the glass design criterion was that the temperature at 2 vol% crystal (T 2% ) be less than 950 °C, only one glass failed the criteria. However, this criterion is being reevaluated. Four additional glasses formed crystal fractions between 1 and 2 vol% at 950 °C (APPS2-03, -08, -12, and -14). • Four glasses – APPS2-01, -02, -04, and -16 – failed the Monofrax K-3 refractory neck corrosion (k neck ) design limit of 0.04 in. at 1208 °C for 6 d. This is another criterion being reevaluated. Four additional glasses (APPS2-05, -06, -11, and -13) exhibited 0.025 = k neck = 0.04 in. • All 16 glasses passed the sulfur solubility and TCLP constraints. The measured property values were compared to predicted values using EWG2.5 and a selection of other existing models. A few models (e.g., electrical conductivity, TCLP) were found to be adequate for designing DFHLW glasses in the near future, while others require refits or offsets. It is recommended that new property models be developed for EWG3.0, as a large amount of DFHLW glass property data (> 14 × existing data) is expected to be collected in the compositional spaces where no data was previously available. To enable near-term calculations and formulations for designing DFHLW glasses and processing rate estimations, a formulation algorithm with minor modifications will be developed, EWG2.6.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Laboratory Experiments and Instrument Intercomparison Studies of Carbonaceous Aerosol Particles

Aerosols containing black carbon (and some specific types of organic particulate matter) directly absorb incoming light, heating the atmosphere. In addition, all aerosol particles backscatter solar light, leading to a net-cooling effect. Indirect effects involve hydrophilic aerosols, which serve as cloud condensation nuclei (CCN) that affect cloud cover and cloud stability, impacting both atmospheric radiation balance and precipitation patterns. At night, all clouds produce local warming, but overall clouds exert a net-cooling effect on the Earth. The effect of aerosol radiative forcing on climate may be as large as that of the greenhouse gases, but predominantly opposite in sign and much more uncertain. The uncertainties in the representation of aerosol interactions in climate models makes it problematic to use model projections to guide energy policy. The objective of our program is to reduce the uncertainties in the aerosol radiative forcing in the two areas highlighted in the ASR Science and Program Plan. That is, (1) addressing the direct effect by correlating particle chemistry and morphology with particle optical properties (i.e. absorption, scattering, extinction), and (2) addressing the indirect effect by correlating particle hygroscopicity and CCN activity with particle size, chemistry, and morphology. In this connection we are systematically studying particle formation, oxidation, and the effects of particle coating. The work is specifically focused on carbonaceous particles where the uncertainties in the climate relevant properties are the highest. The ongoing work consists of laboratory experiments and related instrument inter-comparison studies both coordinated with field and modeling studies, with the aim of providing reliable data to represent aerosol processes in climate models. The work is performed in the aerosol laboratory at Boston College. At the center of our laboratory setup are two main sources for the production of aerosol particles: (a) two well-characterized source of soot particles and (b) a flow reactor for controlled OH and/or O3 oxidation of relevant gas phase species to produce well-characterized SOA particles. After formation, the aerosol particles are subjected to physical and chemical processes that simulate aerosol growth and aging. A suite of instruments in our laboratory is used to characterize the physical and chemical properties of aerosol particles before and after processing. The Time of Flight Aerosol Mass Spectrometer (ToF-AMS) together with a Scanning Mobility Particle Sizer (SMPS) measures particle mass, volume, density, composition (including black carbon content), dynamic shape factor, and fractal dimension. The–ToF-AMS was developed at ARI with Boston College participation. About 120 AMS instruments are now in service (including 5 built for DOE laboratories) performing field and laboratory studies world-wide. Other major instruments include a thermal denuder, two Differential Mobility Analyzers (DMA), a Cloud Condensation Nuclei Counter (CCN), a Thermal desorption Aerosol GC/MS (TAG) and the new Soot Particle Aerosol Mass Spectrometer (SP-AMS). Optical instrumentation required for the studies have been brought to our laboratory as part of ongoing and planned collaborative projects with colleagues from DOE, NOAA and university laboratories. Optical instruments that will be utilized include a Photoacoustic Spectrometer (PAS), a Cavity Ring Down Aerosol Extinction Spectrometer (CRD-AES), a Photo Thermal Interferometer (PTI), a new 7-wavelength Aethalometer and a Cavity Attenuated Phase Shift Extinction Monitor (CAPS). These instruments are providing aerosol absorption, extinction and scattering coefficients at a range of atmospherically relevant wavelengths. During the past two years our work has continued along the lines of our original proposal. We report on 12 completed and/or continuing projects conducted during the period 08/14 to 0814/2015. These projects are described in 17 manuscripts published in refereed journals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multi-scale Coupled Processes Modeling of Fractures as Porous, Interfacial and Granular Systems from Rock Images with the Numerical Manifold Method

Abstract The greatest challenges of rigorously modeling coupled hydro-mechanical processes in fractured rocks at different scales are associated with computational geometry. In addition, selections of continuous or discontinuous models, physical laws, and coupling priorities at different scales based on different geometric features determine the applicability of a numerical model for a certain type of problem. In this study, we present our multi-scale modeling capabilities that have been developed based on the numerical manifold method for analyzing coupled hydro-mechanical processes in fractured rocks. Based on their geometric features, the fractures are modeled as continua—finite-thickness porous zones, and discontinua—discontinuous interfaces and microscale asperities and granular systems. Different governing equations, physical laws, coupling priorities, and approaches for addressing fracture intersections and shearing are then applied to describe these. We applied these models to simulate coupled processes in fractured rocks using realistic geometry obtained from rock images at different scales. We first calculated shearing of a single fracture with different models and demonstrated the impacts of asperities on shearing. We then applied the continuous and discontinuous models to simulate a network of rough fractures, demonstrating that contact dynamics contribute significantly to the geometric, multi-physical evolution of systems where rough fractures are not mineral filled. For a discrete fracture network, our coupled processes modeling demonstrates that shearing of the discrete fractures can have a major impact on stress and pore pressure distribution. Lastly, we applied the discontinuous granular model to simulate evolution of a complex granular system with a deformation band, demonstrating that the deformation band can dominate contact dynamics, the structural and the stress evolution of the granular system.

58 GEOSCIENCES↗
DOE OSTI2022

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

1D model of tokamak scrape-off layer and divertor plasmas: Dimensionless parameters and the results of numerical simulations

Solutions of a 1D model of the scrape-off layer and a divertor plasma in a tokamak are analyzed on the basis of dimensionless parameters governing the physics of both plasma and neutral transport and atomic physics processes. Numerical simulations based on fluid plasma and Monte Carlo neutral modeling confirm earlier results obtained with simplified analytic considerations and numerical simulations performed with fluid neutral description and demonstrate bifurcation of plasma parameters. Further, these simulations also confirm that the major physical reasons for the rollover of the plasma flux to the target, which is the key feature of the phenomenon of divertor plasma detachment, are the impurity radiation loss and plasma recombination. It is suggested that simulations of the edge plasma based on dimensionless parameters provide a powerful tool for checking the consistency of the physics incorporated in existing complex 2D codes used for edge plasma modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Solvated Nuclear–Electronic Orbital Structure and Dynamics

Nonadiabatic dynamical processes such as proton-coupled electron transfer and excited state intramolecular proton transfer have been the subject of much research. One of the promising theoretical methods to describe these processes is the nuclear–electronic orbital (NEO) approach. This approach inherently accounts for nuclear quantum effects within quantum chemistry calculations, and it has recently been extended to directly simulate nonadiabatic processes with the development of real-time NEO methods. These processes can also be significantly dependent on the surrounding chemical environment, however, and capturing the effects of the environment is often necessary for analyzing experimentally relevant systems. This work couples the NEO density functional theory and real-time time-dependent density functional theory approaches with solvation through the polarizable continuum model. Here, the effects of this coupling are investigated for ground state properties, solvent-dependent vibrational frequencies, and direct excited state intramolecular proton transfer dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Numerical Mixing Suppresses Submesoscale Baroclinic Instabilities Over Sloping Bathymetry

Abstract The impacts of spurious numerical salinity mixing on the larger‐scale flow and tracer fields are characterized using idealized simulations. The idealized model is motivated by realistic simulations of the Texas‐Louisiana shelf and features oscillatory near‐inertial wind forcing. can exceed the physical mixing from the turbulence closure in frontal zones and within the mixed layer. This suggests that simulated mixing processes in frontal zones are driven largely by . Near‐inertial alongshore wind stress amplitude is varied to identify a base case that maximizes the ratio of to in simulations with no prescribed horizontal mixing. We then test the sensitivity of the base case with three tracer advection schemes (MPDATA, U3HC4, and HSIMT) and conduct ensemble runs with perturbed bathymetry. Instability growth is evaluated using the volume‐integrated eddy kinetic energy and available potential energy . While all schemes have similar total mixing, the HSIMT simulations have over double the volume‐integrated and 20% less relative to other schemes, which suppresses the release of and reduces the by roughly 25%. This results in reduced isohaline variability and steeper isopycnals, evidence that enhanced suppresses instability growth. Differences in and between the MPDATA and U3HC4 simulations are marginal. However, the U3HC4 simulations have 25% more . Experiments with variable horizontal viscosity and diffusivity coefficients show that small amounts of prescribed horizontal mixing improve the representation of the ocean state for all advection schemes by reducing the and increasing the .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Simulation of wellbore construction in offshore unconsolidated methane hydrate-bearing formation

The unconsolidated nature of offshore methane hydrate-bearing formation poses concerns for sustainable methane gas production as the weak formation is susceptible to disturbance during wellbore construction. Furthermore, this could contribute to loss of well integrity which could manifest as sand production and error in the interpretation of downhole tests such as mini-frac tests. In this study, a simulation methodology of wellbore construction process is proposed. A finite element model adopting this methodology is developed in order to assess the effect of wellbore construction process on the integrity of the unconsolidated methane hydrate-bearing formation in the Nankai Trough, Japan. The primary objectives are (i) to develop a modelling methodology of well construction process for numerical simulations, (ii) to assess the zone and magnitude of well construction-induced stress/strain disturbance in the formation and (iii) to evaluate relative impact of each well construction stage on the integrity of the formation. The results from this study show that the zone of horizontal stress disturbance from the geostatic state due to wellbore construction could extend to more than three times the radius of the wellbore. Following the wellbore construction, the deviator stress is concentrated in the hydrate reservoir sublayers with high hydrate saturation while plastic deviatoric strain has accumulated in the sublayers with low hydrate saturation. The results also show that modelling of cement shrinkage process is crucial in predicting the concentration of deviator stress in the high hydrate saturation layers.

03 NATURAL GAS↗
DOE OSTI2023

Joint Geophysical and Numerical Insights of the Coupled Thermal‐Hydro‐Mechanical Processes During Heating in Salt

Abstract Salt offers an optimal medium for the permanent isolation of heat‐producing radioactive waste due to its impermeability, high thermal conductivity, and ability to close fractures through creep. A thorough understanding of the thermal‐hydrological‐mechanical (THM) processes, encompassing brine migration, is fundamental for secure radioactive waste disposal within salt formations. At the Waste Isolation Pilot Plant (WIPP), we conducted joint in situ geophysical monitoring experiments during active heating to investigate brine migration near excavations. This experiment incorporated electrical resistivity tomography (ERT) alongside high‐resolution fiber‐optic‐based distributed temperature sensing within a controlled heating experiment. Additionally, discrete element model (DEM) based numerical simulations were conducted to simulate THM processes during heating, providing a more mechanistic understanding of the coupled processes leading to the observed changes in geophysical measurements. During heating, resistivity shifts near the heater were reasonably explained by temperature effects. However, in more distant, cooler regions, the resistivity decrease exceeded predictions based solely on temperature. DEM simulations highlighted brine migration, propelled by pore pressure gradients, as the likely primary factor contributing to the additional resistivity decline beyond temperature effects. The comparison between the predicted ERT responses and observations was much improved when considering the effects of brine migration based on the DEM simulations. These geophysical and simulation findings shed light on brine migration in response to salt heating, enhancing our understanding of the coupled THM processes in salt for safe radioactive waste disposal.

58 GEOSCIENCES↗
DOE OSTI2016

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemble forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.

58 GEOSCIENCES↗
DOE OSTI2025

A Versatile Simulated Data Transport Layer for in Situ Workflows Performance Evaluation

In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2025

Effect of toolpath in large-format additive manufacturing with bio-derived composites

There has been growing interest in integrating bio-derived composites into Large-format additive manufacturing (LFAM) feedstocks to reduce the use of petroleum-derived materials and reduce the overall carbon footprint of LFAM. However, these materials present unique challenges during manufacturing due to their variability, which can lead to unintended deformations and failures attributable to suboptimal process conditions. While numerical modelling has been extensively employed to simulate numerous manufacturing processes, its application in LFAM with bio-derived composites remains limited. This study addresses this gap by systematically developing a numerical model to simulate the LFAM process using bio-based materials, specifically wood fiber-reinforced polylactic acid (PLA/WF). Experimental investigations were conducted to characterise the thermal and mechanical properties of additively manufactured PLA/WF specimens. Numerical simulations were performed to predict temperature profiles and deformations during LFAM. The effect of varying infill patterns, internal structures, and tool paths on the temperature distribution and deformation of printed parts was explored using the developed model. This article aims to advance the utilisation of bio-derived composites in LFAM systems and provide a comprehensive understanding of the LFAM process. The findings offer valuable insights for optimising process parameters and enhancing the performance of LFAM with bio-based composites.

Large-format additive manufacturing↗
DOE OSTI2026

Accelerating laser ray tracing in high fidelity physics simulations of laser melting using squeeze U-net

Laser melting is a core component of the ongoing industrial revolution, dubbed Industry 4.0, as lasers facilitate fast and precise melting and fusion in advanced manufacturing. There is a strong need to optimize the laser process using simulations. However, this has proven challenging as high fidelity simulations are needed for predictive modeling and this is currently prohibitively expensive even when run on hundreds of processors on high performance computers. The challenge is capturing complex physics of laser material interaction, fluid dynamics, thermal physics and material phase transformations at various length and time scales. To close this technological gap, we modified a squeeze U-net to accelerate the laser ray tracing component of such high fidelity models by ~4x–40x while preserving the core physics principle of conservation of energy with 97% accuracy. This approach enables the accurate modeling of global laser energy absorption as a function of local surface temperatures and complex surface topologies, which govern the reflection directions and energy losses of laser rays upon interacting with the material surface.

Computer science↗
DOE OSTI2026

Dynamic evolution of ultracold electron beams from nanostructured cathodes

Dynamic Coulomb expansion of dense, nonuniform particle beamlets can lead to causticlike formations in the charge density profile of the resultant beam. Such features only occur for cold beams where thermal diffusion of the particles is minimized. These phenomena have been observed experimentally for select cases with ion beams but not yet for electron beams as the electron dynamics occur over far faster timescales. We simulate the interaction of electron bunches while varying the initial transverse temperature and density profiles to determine the thresholds that characterize this pattern formation. Furthermore, we extend the simulations to geometric arrangements that are more pertinent to the nanotip cathode application and consider the effects of asymmetries and the impact of a low-density halo on the overall process. The simulations are conducted using a previously documented high-fidelity algorithm for collisional particle dynamics. These studies identify the temperature and density thresholds required for caustic formation and provide guidance for optimizing the design of nanoscale structured cathodes. We also demonstrate that the correlation between the final density patterns and the underlying beam parameters enables a virtual diagnostic tool for measuring ultralow emittance beams solely based on a transverse charge density profile.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Effect of Magnetic Field on the Dynamics of Movement of Charged Particles in Cluster Systems

The results of numerical and analytical studies of the influence of a constant magnetic field on the dynamics of the thermal motion of charged particles in an isotropic electrostatic trap are presented. Simulations were performed for cluster systems of particles with Coulomb interaction in a wide range of their parameters. The analysis of the spectral density of displacement of particles and mass transfer processes in simulated ensembles is performed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Multiphysics Modeling of Nuclear Materials

The operating environment of nuclear reactors presents many unique challenges both for the materials comprising fuel elements and other structural components within and surrounding the reactor. These environmental challenges are due to the simultaneous exposure to conditions from multiple physical systems, including high temperatures, high radiation fluxes, aggressive chemical environments, and mechanical loading. Numerical simulation has been used for decades as a tool for understanding the behavior of various components in this environment. As these tools have been developed to increasing levels of sophistication, they have been used increasingly both for engineering analysis of components, as well as for simulating the processes of microstructure evolution, which lead to changes in the engineering properties of interest in the materials used in these components. This document provides an overview of the methods used for multiphysics simulation of nuclear materials, and provides examples of the application of these techniques.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Improved Performance of Cu(InGa)(SeS) 2 PV Modules Using the Reaction of Metal Precursors. Final Report

This project “Improved Performance of Cu(InGa)(SeS) 2 PV Modules using the Reaction of Metal Precursors” was a partnership led by the Institute of Energy Conversion (IEC) at the University of Delaware with Columbia University and the Molecular Foundry at the Lawrence Berkeley National Laboratory. The aim was to develop pathways to improve Cu(InGa)(SeS) 2 (CIGSS) thin film photovoltaic modules using processes compatible with low manufacturing cost. The CIGSS approach investigated was a two-step process including deposition of metal precursor films following by reaction in hydride gases utilizing IEC’s novel reactor. The process was similar to that under commercial development by the project’s industry partner Stion. When Stion went out of business mid-project the focus changed to a rapid thermal process considered more commercially viable. Approaches to improve the performance of solar cells using the reacted films focused on two material innovations. First, the overall Ga content was increased to increase the operating voltage, which is desirable for scale-up to commercial modules. Second, the processing and performance advantages arising from Ag alloying were investigated. Advanced characterization guided process and material development including control of relative composition gradients. Research on the formation of Cu-Ga-In metal precursors utilized sputtering deposition which is normally used in commercial applications. The work resulted in processes for deposition of precursor stacks with increased relative Ga content and effects of deposition parameters on morphology and phase composition were established. It was shown that the metal precursor films have comparable phase composition and morphology so subsequent reaction follows from the same starting point. The addition of Ag to the metal precursors gave more uniform morphology and improved adhesion of reacted films which enable higher reaction temperature for faster processing. A novel outcome was the discovery of a previously undocumented material phase in sputter-deposited and evaporated Ag-Cu-In-Ga thin films. Hydride gas reaction processes including time-temperature-concentration profiles were developed for different precursor compositions. This enables control of composition profiles to engineer through-film gradients for solar cell optimization with characterization and simulations used to correlate measured film composition profiles to measurements of devices. In particular, the gradient of sulfur at the front of the CIGSS film was found to be critical. The simulations guided process development leading to improved reproducibility of devices improved performance with higher Ga content and higher voltage. With Ag-alloyed precursors, the reaction pathways leading were determined. A significant finding was that Ag-alloying increases the reaction rate to completely convert precursor films to the final chalcopyrite which could enable reduced reaction time to benefit manufacturability. To maintain potential commercial viability, the process under investigation was refocused to a rapid thermal process that could potentially be incorporated into an in-line process for manufacturing. Precursors with different composition were capped with an extra selenium layer and reacted in hydrogen sulfide 5-15 minutes, compared to typically 2 hours in the previous multi-step batch process. Critical RTP parameters were identified to control the reaction. Further optimization would be needed for high efficiency solar cells but pathways to high quality devices with further optimization and improved heating uniformity were developed. The project also developed new optoelectronic characterization approaches with a focus on development and application of spatial- and time-resolved photoluminescence and a custom mapping photoluminescence microscope built. It was shown how critical electronic transport properties strongly depend on the chemical composition of the material and that a wide range of samples show inhomogeneity on a length scale larger than the grains in the films. Additionally, two-photon excitation capability was developed to distinguish bulk vs surface losses. The project advances the state-of-the -art for precursor reaction processes in several ways that could impact manufacturing. This includes validation of approaches to increase voltage and establishment of model-guided control to form optimal composition profiles. The application of process control approaches with knowledge of phase formation and reaction pathways can be critically valuable in designing a large-scale process.

14 SOLAR ENERGY↗