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At least 343 records · Page 19

Electrochemical Corrosion of SIMFUEL: Effects of dissolved H2 and noble metal particles

This report describes the results from electrochemical corrosion tests that were conducted using simulated spent fuel (SIMFUEL) materials comprised of UO2 and surrogate fission products. Two SIMFUEL compositions were tested to quantify the effect of noble metal inclusions and dissolved H2 on the UO2 dissolution rate. One material consisted of UO2 with added lanthanide oxides (UO2 N) and the other consisted of UO2 with added lanthanide oxides and noble metals (UO2-H) at concentrations to simulate high burnup fuel. The electrochemical corrosion tests on the SIMFUEL materials were conducted in aqueous electrolyte solutions (pH 10) that were either saturated with air or purged with a H2/Ar gas mixture to maintain a constant dissolved H2 concentration. The results from electrochemical corrosion tests on SIMFUEL can be applied to qualitatively understand and also quantify the separate effects of water chemistry and fuel composition on the degradation behavior of the UO2 matrix. Open circuit potential (OCP) measurements on a SIMFUEL material of known composition (i.e., known fraction of NMPs at the fuel surface) immersed in a known solution chemistry (i.e., pH, Eh, [O2], [H2]) at known temperature provide qualitative insight into the degradation behavior of the UO2 matrix. If the OCP is above the threshold potential at which the oxidative dissolution of U(IV) to U(VI) occurs, the SNF is expected to degrade by oxidative processes under the experimental conditions. The net currents that are measured during potentiostatic tests, during which the surface potential of the SIMFUEL material is fixed by a potentiostat, can be used to quantify the UO2 degradation rate and optimize the rate constant values used in the Fuel Matrix Degradation Model (FMDM) for half reactions that occur on the SNF surface. Specifically, electrochemical measurements enable the estimation of the total anodic current at ECORR–which is the surface potential at which the total anodic and total cathodic currents are equal–so that the rate constant values for key reactions can be calculated. The open circuit potential measurements, potentiostatic tests, surface property measurements (scanning electron microscopy images and electrochemical impedence spectroscopy plots), and solution elemental composition analyses are being performed to update and optimize the FMDM. A case study is presented herein to show how electrochemical corrosion test results and accompanying characterization results for the UO2 N material in air-saturated solution can be used to validate the SNF surface reaction module of the FMDM. Future electrochemical tests will be conducted to provide quantitative information on the effects of NM content (burnup), H2 concentration, water chemistry, temperature, and galvanic couples with cladding and EBS alloys on UO2 degradation that can be used to improve the accuracy and functionality of the FMDM.

Thomas, Sara↗

Enhanced HLW glass property-composition models - phase 3

During the present phase (Phase 3) of work to enhance and expand the HLW glass property-composition models, test data for 137 glasses were collected and incorporated into the combined WTP/ORP database. The new data include those collected on glasses from two statistically designed matrices to augment the moderate alumina region (the HLW16-MA matrix covering the region of 9 wt% < Al2O3 < 12 wt% with 16 glasses) and the ultra-high alumina region (the HLW16-UHA matrix covering the region of 26 wt% < Al2O3 < 29 wt% with 29 glasses). The addition of ORP glasses over the different phases of testing has significantly expanded the combined WTP/ORP database. The compiled data include glass compositions, PCT (B, Li and Na) releases, spinel T1%, electrical conductivity, viscosity, TCLP-Cd releases, and nepheline formation upon CCC. With the exception of the CCC spinel formation data – the CCC data will be used to support the further development of nepheline models for Hanford HLW glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Matrix Multiply Performance of GPUs on Exascale-class HPE/Cray Systems

The computation of dense matrix-matrix products (GEMMs) is central to many modeling and simulation workloads as well as AI/ML deep learning campaigns. In fact, millions of dollars are spent annually on computing GEMMs, and large model training demands are increasing exponentially. Specialized processors such as GPUs are designed to perform well for these operations. However, the performance of GEMMs on GPUs can exhibit complex behaviors depending on many factors, making it challenging to optimize the performance of GEMMs on these processors. In this study we undertake an examination of GEMM performance on several leading GPU models taken from product lines of GPUs to be deployed in forthcoming exascale computing systems. We show results to illustrate the many factors that can affect performance of GEMMs on GPUs. We then present data collected from a large number of test runs for an example GEMM operation to show the dependence behaviors of GEMM rate on matrix dimensions. Finally, we show results from machine learning-based performance models using novel feature engineering methods to fit the measured performance, providing a potential basis for GEMM performance tuning and autotuning methods for GPUs. Recommendations are also given for how to achieve high GEMM performance on modern GPUs.

Melesse Vergara, Veronica↗

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.

97 MATHEMATICS AND COMPUTING↗

Laboratory testing methods to evaluate the reliability of occupancy sensors for commercial building applications

The energy performance of commercial buildings is greatly influenced by occupants which are highly variable and among the most unpredictable components of a building's operation. While most building control systems use fixed, predetermined occupancy schedules, these fixed occupancy levels can be quite different from actual occupancy. This can cause unnecessary energy consumption, particularly from heating, ventilation, and air conditioning (HVAC) and lighting systems which are responsible for approximately 60% of commercial buildings' energy use. The use of occupancy counting sensor systems integrated with building management system controls is one method that can be used to improve the energy-consuming performance of buildings. However, there is no standardized universal methodology and metrics to evaluate their reliability. The aim of this research is to develop a uniform evaluation methodology to assess the reliability of occupancy counting sensor systems in a controlled laboratory environment. The developed testing methodology includes both “typical” scenarios representing the occupancy scenarios of a typical commercial building, and “failure” testing scenarios which represent a range of potential scenarios that may impact a sensor system's reliability. These methods were then implemented in a case study to evaluate the performance of two novel occupancy counting sensor systems (i.e., door-centric, and camera-based). Results suggest that typical testing results can be used to compare the overall performance of the occupancy counting sensor systems; however, failure testing is also important to understand the weaknesses of the sensor system in order to select the suitable one for the intended use of the commercial building. In addition, the proposed methodology includes a modified confusion matrix which enables the ability to identify if failures are caused by over or under counting occupants and to what extent this occurs over the testing period.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Parametric Study of Used Nuclear Oxide Fuel Constituent Dissolution in Molten LiCl-KCl-UCl 3

Prior work identified dissolution of used nuclear oxide fuel constituents from a uranium oxide matrix into molten LiCl-KCl-UCl 3 at 500°C, prompting a subsequent series of three progressive studies (including an initial scoping study, an electrolytic dissolution study, and a chemical-seeded dissolution study) to further investigate associated parameters and mechanisms. Thermodynamic calculations were performed to identify possible reaction mechanisms and their propensities in used oxide fuel constituent dissolution. Used nuclear oxide fuels with varying preconditions from fast and thermal test reactors were separately immersed in the subject salt system to assess fuel constituent migration from the bulk fuel matrix to the salt phase in an initial scoping study. Dissolution of expected fuel constituents, including alkali, alkaline earth, lanthanide, and transuranium oxides, into the chloride salt phase varied widely, ranging from 12% to 99% in the initial study. Uranium isotope blending between the salt phase and bulk fuel matrix was also observed, which was attributed to reducing conditions in the fuel matrix. Electrolytic and chemical-seeded dissolution studies were subsequently performed to effect reducing conditions in the fuel. Other parameters, including temperature (at 500°C, 650°C, 725°C, and 800°C) and uranium trichloride concentrations (at 6, 9, and 19 wt% uranium), were investigated in the latter two studies, resulting in fuel constituent dissolution above 90%. Extents of dissolution were based on initial and final fuel constituent concentrations in the oxide fuels following operations in the salt and subsequent removal of the salt via distillation. Finally, in this series of progressive studies, oxide fuel preconditioning and in situ reducing conditions, along with elevated temperature and uranium trichloride concentrations, were the primary parameters promoting used nuclear oxide fuel constituent dissolution in accordance with identified reaction mechanisms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Next-generation anion exchange membrane water electrolyzers operating for commercially relevant lifetimes

Alkaline anion exchange membrane (AEM) water electrolysis has gained increasing attention due to its potential to achieve low-cost, high performance hydrogen production. However, most existing membranes are not durable in industrial settings. In this work, we demonstrate good performance relative to industrial parameters using Sustainion® anion exchange membranes. Long-duration tests showed stable performance of 1 A/cm 2 at 1.85 V with a degradation rate of less than 1 μV/h over 10,000 h. The projected lifetime is thus over 20 years. Daily on/off cycling performance over the course of 30 years was simulated experimentally through accelerated voltage shock tests, resulting in a performance loss of only 0.15 μV/cycle over 11,000 cycles. As shown through impact and crossover testing, an improvement in performance is achieved by the addition of zirconia to the polymer matrix and mechanically reinforcing the membrane.

08 HYDROGEN↗

Scalable Fabrication of a Fibrous Amine-functionalized Matrix (FAM) Sorbent for Critical Mineral Recovery

We report a novel flat sheet Fibrous Amine-functionalized Matrix (FAM) sorbent platform designed for efficient and selective capture of CM from dilute solutions. The FAM sorbent features crosslinked amine microfilms coated onto/within a glass fiber matrix, providing fast mass transfer and excellent mechanical stability. Systematic batch and flow-through tests with FAM revealed rapid metal uptake kinetics and high capacity for representative species, achieving ~90 mg/g of Gallium, ~100 mg/g of Cobalt, and ~90 mg/g for Neodymium. Moreover, multiple eluents, including mineral acids and complexing agents, enabled highly effective desorption of adsorbed metals, demonstrating the feasibility of regenerating FAM sorbents. Importantly, tests with authentic coal ash leachate demonstrated strong selectivity toward U.S. Department of Energy (DOE)-listed CM and rare earth elements over abundant base cations, confirming the robustness of FAM in realistic complex solutions. The flat sheet geometry was amenable to scaling into durable spiral wound modules, highlighting the potential for future regeneration and reuse. This work establishes FAM sorbents as a promising platform for the recovery of CM from wastewaters, advancing both resource sustainability and environmental stewardship.

critical mineral recovery↗

NEAMS Technical Area Support in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and other new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities outlined in this report include implementing hash table matrix assembly for efficient sparsity pattern construction for contact in BISON, developing re-step testing infrastructure for ensuring the viability of overlapping domain coupling between SAM and Pronghorn, allowing unique preconditioners for single-input multi-system solves, supporting multi-system in MOOSE’s workhorse executioners, and many more smaller feature enhancements and bug fixes.

97 - MATHEMATICS AND COMPUTING↗

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

This document presents a master–slave methodology for solving the problem of optimal operation of photovoltaic (PV) distributed generators (DGs) in direct current (DC) networks. This problem was modeled using a nonlinear programming model (NLP) that considers the minimization of three different objective functions in a daily operation of the system. The first one corresponds to the minimization of the total operational cost of the system, including the energy purchasing cost to the conventional generators and maintenance costs of the PV sources; the second objective function corresponds to the reduction of the energy losses associated with the transport of energy in the network, and the third objective function is related to the minimization of the total emissions of CO2 by the conventional generators installed on the DC grid. The minimization of these objective functions is achieved by using a master–slave optimization approach through the application of the Vortex Search algorithm combined with a matrix hourly power flow. To evaluate the effectiveness and robustness of the proposed approach, two test scenarios were used, which correspond to a grid-connected and a standalone network located in two different regions of Colombia. The grid-connected system emulates the behavior of the solar resource and power demand of the city of Medellín-Antioquia, and the standalone network corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá-Choco. A numerical comparison was performed with four optimization methodologies reported in the literature: particle swarm optimization, multiverse optimizer, crow search algorithm, and salp swarm algorithm. The results obtained demonstrate that the proposed optimization approach achieved excellent solutions in terms of response quality, repeatability, and processing times.

14 SOLAR ENERGY↗

AGR TRISO Fuel Fission Product Release Data Summary

Knowledge of fission product retention in and release from TRISO fuel under normal and off-normal conditions is needed for reactor safety analyses. This is important for coated-particle fuel used in high-temperature reactors relying on the functional containment strategy. Data on the release and retention of key fission products (e.g., Ag-110m, Cs-134, Eu-154, and Sr-90) in AGR UCO TRISO fuels have been summarized in this report, and empirical relationships with respect to time and temperature were developed. This included fission product accumulation in the OPyC and compact graphitic matrix during irradiation, release from compacts during irradiation, and release during post-irradiation safety testing at temperatures from 1600-1800°C. The frequencies of SiC failure and TRISO coating failure from irradiation and post-irradiation safety testing were also summarized as they have bearing on the quantities of Cs release from the fuel. In a forthcoming publication, a framework for combining and using these empirical relationships as part of a source term analysis will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An Advanced Meso-Scale Peridynamic Modeling Technology using High-Performance Computing for Cost-Effective Product Design and Testing of Carbon Fiber Reinforced Polymer Composites in Light-weight Vehicles

We study a peridynamic composite modeling technology based on the discontinuous Galerkin finite element method, implemented in the commercial LS-DYNA software, for modeling and prediction of failure in carbon fiber reinforced polymer composites. The proposed technology is developed for the material failure analysis at the meso-scale, which provides the prevailing fiber-matrix interaction mechanism, without adoption of the representative volume element method and thus avoiding complicated numerical calibration procedures. Three types of experimental tests—in-plane coupon test, out-of-plane coupon test, and a component crash test—are simulated in a high-performance computing environment to assess the performance of the proposed peridynamic composite modeling technology.

36 MATERIALS SCIENCE↗

Accelerated Fuel Qualification of Fast Modular Reactor Fuel in a Thermal Reactor: Modeling and Simulation Paired with Irradiation Testing

The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.

Advanced test reactor (ATR)↗

Post-irradiation examination of the Sirius-1 nuclear thermal propulsion fuel test

Nuclear Thermal Propulsion (NTP) systems hold promise in reducing transit times for exploration of the solar system by both crewed and uncrewed missions. NTP systems currently under investigation include a once-through high-temperature gas-cooled fission reactor to provide thermal energy to heat the coolant, which also serves as the propellant. The fuel system consists of angular UN fuel particles dispersed in a matrix of W/Re, creating a ceramic and metallic composite or cermet, which has been irradiated in Idaho National Laboratory's (INL) Transient Reactor Test Facility (TREAT). This enabled evaluation of these materials under representative nuclear heating rates (~95 K/s) and peak surface temperatures (~2527 K). Further, these surface conditions were indicative of achievement of the target peak internal temperature of approximately 2850 K. These tests named Sirius-1 (UN–W/Re), have been irradiated and this paper will present post-irradiation examination results. The Sirius-1 test produced minor, stable cracks in the fuel specimen and spalling of surface material. Volatilized uranium ‘soot’ was found deposited on the inner wall of the irradiation capsule indicating loss of some fissile material from the fuel specimen. Spalling from the surfaces was also noted upon visual inspection. Uranium diffusion from the fuel particles resulted in the formation of U/Re phases and the production of a laminar microstructure on the edge of the fuel system. Overall, the specimen was stable and remained within a coolable geometry upon conclusion of multiple thermal cycles to prototypical operating temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Sorption Enhanced Mixed Matrix Membranes for Hydrogen (H 2 ) Purification and Carbon Dioxide (CO 2 ) Capture

The technical objective of this project was to develop sorption enhanced mixed matrix membranes with H 2 permeance of 500 gas permeance units (GPU) and H 2 /CO 2 selectivity of 30 at 150-200 °C. These membranes will be the central component in the design of membrane based systems for 90% capture of CO 2 from coal-derived syngas, with 95% CO 2 purity at a cost of electricity 30% less than baseline capture approaches. The unique approach in this proposal is to design crosslinked polymers containing Pd-based nanoparticles achieving strong H 2 sorption and size sieving ability and thus H 2 /CO 2 selectivity. The specific objectives for each budget period (BP) are described below. BP 1: Identify polymer matrix with strong size sieving ability and palladium (Pd)-containing nanomaterials to prepare freestanding mixed matrix films with H 2 permeability of 50 Barrer and H 2 /CO 2 selectivity of 30 at 150-200°C with simulated syngas. BP 2: Prepare and optimize thin film mixed matrix composite membranes materials with H 2 permeance of 500 GPU and H 2 /CO 2 selectivity of 30 at 150-200 °C, and complete the modification of the membrane test unit for the field test in the BP 3. BP 3: Conduct a 20-day field test of the membranes with real syngas at Center for Advanced Energy Research (CAER) of the University of Kentucky (UKy). During the BP2, we have successfully prepared thin-film composite (TFC) membranes based on mixed matrix materials (MMMs) containing Pd nanoparticles in polymers, and demonstrated their superior and robust performance for H 2 /CO 2 separation at 150 – 225 °C. (1) Production of the Pd based nanoparticles with a diameter of 4 nm has been scaled up to 200 mg/day. (2) We have prepared TFC membranes with H 2 permeance above 500 GPU and H 2 /CO 2 selectivity above 30 at temperatures up to 225 °C, which meet the targets for the BP2. (3) We have conducted parametric studies of TFC membranes with a mixed gas containing H 2 S and H 2 O and demonstrated the stability of the membranes. (4) We have established a new testing plan at the Center for Advanced Energy Studies (CAER) at the University of Kentucky because NCCC decided to shut down their gasifier. During this project, four Ph.D. students received the inter-disciplinary training and graduated, including Shailesh Konda, Maryam Omidvar, Deqiang Yin, and Lingxiang Zhu. One postdoctoral researcher (Dr. Liang Huang) and two Ph.D. students (Abhishek Kumar and Hien Nguyen) are involved in this project. The project leads to one provisional patent application, eight peer-reviewed articles, and one manuscript in preparation. The details are shown below.

01 COAL, LIGNITE, AND PEAT↗