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Synthesis and Thermophysical Property Determination of NaCl-PuCl3 Salts

Currently, a knowledge gap exists in the available data and understanding of thermophysical properties relating to fresh fuel salts, especially those containing plutonium. Determination of this data is necessary for the design and construction of test reactors, as well as the licensing of future commercial molten salt reactors. Thermophysical properties such as melting temperature, salt stability, density, and heat capacity were determined on synthesized eutectic NaCl-PuCl3 and a more sodium rich composition containing 25 mol% PuCl3. These measurements document the baseline properties of the salt as a function of temperature for future experiments on irradiated fuel salt which will provide a holistic perspective on the change of thermophysical properties during reactor operations. It was determined that the NaCl-PuCl3 ingot synthesized for this study contained 63.4 mol% NaCl, 36.3 mol% PuCl3, and was 99.7% pure. Upon heating it was shown that the NaCl- PuCl3 eutectic was stable at temperatures of 800°C. The onset of melting occurred at 541°C and the enthalpy of fusion was determined to be 140.7 ± 8.4 J/g. Specific heat capacity measurements showed a slightly decreasing trend with respect to temperature in the liquid phase ranging from 0.67 to 0.57 J/g·K, with an average value of 0.637 ± 0.03 J/g·K (104 ± 5 J/mol·K) between 500 to 720°C. Three independent trials of the molten NaCl-PuCl3 eutectic salt found the density to be ?(T) = 3.8589 – 9.5342·10-4 T(°C), validated between 500 to 800°C. In addition to salt synthesis and experimentally determining thermodynamic properties, Ab Initio molecular dynamic (AIMD) simulations were used to calculate density and heat capacity values.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydropower Value Drivers

Conventional hydro resources generate the majority of their value by providing energy under most conditions, but the relative fraction of value generated by providing ancillary services and capacity increases with increasing penetration of resources with zero fuel costs. Pumped storage hydropower resources generate the majority of their value by providing capacity under most conditions, but the relative fraction of value generated by providing energy increases with increasing penetration of resources with zero fuel costs. The total value of conventional hydropower generally decreases in systems with increasing penetration of resources with zero fuel costs; this is largely due to the associated decrease in average energy prices. The total value of pumped storage generally increases in systems with increasing penetration of resources with zero fuel costs, largely due to opportunities to operate in pumping mode when energy prices are low or even negative. Energy storage representation must be enhanced to ensure that models accurately capture system value streams for these resources. Current power system models have a limited ability to capture the price dynamics of ancillary services, and it is still challenging to assess the role and magnitude of ancillary service value streams in future systems. Power systems are currently in a state of rapid and dramatic evolution due to a number of different factors, including the increasing penetration of variable renewable energy (VRE) sources, such as wind and solar, and battery energy storage systems (BESS). This evolution will change the way power systems are fundamentally planned and operated. Some of these changes may be incremental, while others may be more significant, but the result will likely be parallel evolution in the definition and requirement of different grid services and therefore a subsequent shift in their relative values. This report presents a framework developed to identify such system value drivers and quantify their relative impact on several different value streams, with a specific focus on implications for conventional hydropower and pumped storage hydropower (PSH) resources. This value drivers framework (VDF) encompasses five core analytical steps: 1. Identify potential drivers and develop scenarios, 2. Execute production cost models, 3. Calibrate prices, 4. Optimize hydropower operations, and 5. Quantify value drivers.

13 HYDRO ENERGY↗

A simple method for obtaining heat capacity coefficients of minerals

Abstract Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation between, temperatures. This approach inevitably results in estimates for entropy and enthalpy values because the heat capacity coefficients required for optimal thermodynamic treatment are less frequently available. Here we propose a simple method for obtaining heat capacity coefficients of minerals. This method requires only the empirically measured temperature-specific heat capacity for calculation via a matrix algorithm. The system of equations solver is written in the Python computing language and has been made accessible in an online repository. Thermodynamically, the solution to a system of equations represents the heat capacity coefficients that satisfy the mineral-specific polynomial. Direct coefficient calculation will result in more robust thermodynamic data, which are not subject to fitting uncertainties. Using hematite as an example, this method provides results that are comparable to conventional means and is applicable to any solid material. Coefficients vary within the traditional large 950 K temperature interval, indicating that best results should instead utilize a smaller 400 K temperature interval. Examples of large-scale implications include the refinement of geothermal gradient estimation in rapidly subsiding sedimentary basins or metamorphic and hydrothermal evolution.

Geochemistry & Geophysics↗

Property Measurements of NaCl-UCl 3 and LiF-NaF-KF Molten Salts Doped with Surrogate Fission Products

Knowing thermophysical and thermochemical property values of salts over the expected range of operating temperatures is essential to modeling and simulation efforts that support the commercialization of molten salt reactor (MSR) technologies. Salt properties being measured at Argonne include thermal transitions, phase behavior, heat capacity, density, surface tension, volumetric thermal expansion, thermal diffusivity, thermal conductivity, and viscosity. The properties of several salts of interest including NaCl-UCl 3 and LiF-NaF-KF (FLiNaK) have been measured at Argonne and reported previously. These property measurements are suitable for use in evaluating reactor performance during startup and the early operating life of the reactor. The physical and chemical behavior of the fuel salt is altered by the buildup of fission products and the resulting changes in heat transfer and other properties must be understood by reactor developers. This report summarizes melting behavior, heat capacity, and thermal diffusivity values that were measured for mixtures of FLiNaK and NaCl-UCl 3 salts that have been doped with surrogate fission products. Additional heat capacity measurements were also performed on a separate mixture of FLiNaK without dopants. Measured properties are suitable for incorporation into the Molten Salt Thermal Properties Database–Thermochemical (MSTDB–TC) and the Molten Salt Thermal Properties Database–Thermophysical (MSTDB–TP) to support the development of MSRs. Salts were prepared by doping eutectic mixtures of NaCl-UCl 3 and FLiNaK with surrogate fission products. These salts were prepared for use in salt spill experiments being performed at Argonne and were subsequently used for thermal property measurements. Thermal transitions and heat capacities were measured by using differential scanning calorimetry (DSC) and thermal diffusivity was measured by using laser flash analysis (LFA) at temperatures spanning the typical MSR operating range. The measured property values of the doped salts were compared to measured property values of salts without fission products to quantify the effects of the doped fission products.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Remarkably coherent population structure for a dominant Antarctic Chlorobium species

Background: In Antarctica, summer sunlight enables phototrophic microorganisms to drive primary production, thereby “feeding” ecosystems to enable their persistence through the long, dark winter months. In Ace Lake, a stratified marine-derived system in the Vestfold Hills of East Antarctica, a Chlorobium species of green sulphur bacteria (GSB) is the dominant phototroph, although its seasonal abundance changes more than 100-fold. Here, we analysed 413 Gb of Antarctic metagenome data including 59 Chlorobium metagenome-assembled genomes (MAGs) from Ace Lake and nearby stratified marine basins to determine how genome variation and population structure across a 7-year period impacted ecosystem function. Results: A single species, Candidatus Chlorobium antarcticum (most similar to Chlorobium phaeovibrioides DSM265) prevails in all three aquatic systems and harbours very little genomic variation (≥ 99% average nucleotide identity). A notable feature of variation that did exist related to the genomic capacity to biosynthesize cobalamin. The abundance of phylotypes with this capacity changed seasonally ~ 2-fold, consistent with the population balancing the value of a bolstered photosynthetic capacity in summer against an energetic cost in winter. The very high GSB concentration (> 10 8 cells ml –1 in Ace Lake) and seasonal cycle of cell lysis likely make Ca. Chlorobium antarcticum a major provider of cobalamin to the food web. Analysis of Ca. Chlorobium antarcticum viruses revealed the species to be infected by generalist (rather than specialist) viruses with a broad host range (e.g., infecting Gammaproteobacteria) that were present in diverse Antarctic lakes. The marked seasonal decrease in Ca. Chlorobium antarcticum abundance may restrict specialist viruses from establishing effective lifecycles, whereas generalist viruses may augment their proliferation using other hosts. Conclusion: The factors shaping Antarctic microbial communities are gradually being defined. In addition to the cold, the annual variation in sunlight hours dictates which phototrophic species can grow and the extent to which they contribute to ecosystem processes. The Chlorobium population studied was inferred to provide cobalamin, in addition to carbon, nitrogen, hydrogen, and sulphur cycling, as critical ecosystem services. The specific Antarctic environmental factors and major ecosystem benefits afforded by this GSB likely explain why such a coherent population structure has developed in this Chlorobium species.

59 BASIC BIOLOGICAL SCIENCES↗

Heat capacity of URu 2 - x Os x Si 2 at low temperatures

Here we perform measurements of the heat capacity as a function of temperature on URu 2-x Os x Si 2 alloys. Our experimental results show that the critical temperature of the second-order phase transition increases while the value of the Sommerfeld coefficient in the ordered state decreases with an increase in osmium concentration. We also observe an increase in the values of the heat capacity at the critical temperature as well as a broadening of the critical fluctuation region with an increase in x. We analyze the experimental data using the Haule-Kotliar model which, in particular, identifies the “hidden order” transition in the parent material UR u2 Si 2 as a transition to a state with a nonzero hexadecapole moment. We demonstrate that our experimental results are consistent with the predictions of that model.

36 MATERIALS SCIENCE↗

Factors Impacting Nuclear Energy Share in U.S. Energy Markets

The purpose of this report is to collate information and findings from recent studies conducted by national and international bodies/institutes to identify approaches for maintaining/enhancing the role of nuclear energy in the current and future energy mix of the United States. This report shows how nuclear generation grew quickly to provide 20% of U.S. electricity, sustaining that level for three decades without the benefit of new construction, but is now projected to decline going forward. Nuclear construction costs in the U.S. spiraled out of control, ending construction for two decades and the recent resumption of construction has continued the pattern of schedule delays and cost overruns. However, nuclear operations exhibited strong learning, achieving and sustaining the highest capacity factor of any electricity generation technology and license extensions and uprates have sustained nuclear market share. The share of nuclear energy in the U.S. electricity market is projected to decline by ~1/3rd over the next 30 years The report provides an overview of how the markets work in theory and in practice. It indicates how market deregulation and clean energy policies have created conditions where nuclear plants are being retired for economic rather than technical reasons. The report also shows how many of the markets do not in practice have free competition but instead have outcomes that are being determined more and more by policy instead of market forces. While electricity costs from existing nuclear plants are low, electricity from new builds is projected to be too expensive to be competitive head-to-head with natural gas, even for nth-of-a-kind costs. Wind and solar energy have enjoyed an extended period of sustained subsidy. This protected environment has resulted in a sustained reduction in plant level costs to the point that some of these Variable Renewable Energy (VRE) technologies are becoming competitive even if their direct subsidies are removed. But plant level costs underestimate total VRE costs which include a number of system-level externalities. The incremental system value of additional VRE capacity was shown to decline as market share increases, with solar value declining more quickly than wind. The report closes with examination of a possible future for nuclear generation as part of deep decarbonization of the electricity sector. This approach avoids direct competition with natural gas. The two options for achieving 100% decarbonization are to use only renewables or to use all zero emissions technologies, and the report shows the second approach is much less expensive than the first.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Heat capacity of microgram oxide samples by fast scanning calorimetry

Quantitative scanning calorimetry on microgram-sized samples opens a broad, new range of opportunities for studying the thermodynamic properties of quantity-limited materials, including those produced under extreme conditions or found as rare accessory minerals in nature. We calibrated the Mettler Toledo Flash DSC 2+ calorimeter to obtain quantitative heat capacities in the range 200–350 °C, using samples weighing between 2 and 11.5 μg. Our technique is applied to a new set of oxide materials to which it has never been used before, without the need for melting, glass transitions, or phase transformations. Heat capacity data were obtained for silica in the high pressure stishovite (rutile) structure, dense post-stishovite glass, standard fused quartz, and for TiO2 rutile. These heat capacities agree within 5%–15% with the literature values reported for rutile, stishovite, and fused SiO2 glass. The heat capacity of post-stishovite glass, made by heating stishovite to 1000 °C, is a newly reported value. After accurate calibrations, measured heat capacities were then used to calculate masses for samples in the microgram range, a substantial improvement over measurement in conventional microbalances, which have uncertainties approaching 50%–100% for such small samples. Since the typical uncertainty of heat capacities measured on 10–100 mg samples in conventional differential scanning calorimetry is typically 7% (1%–5% with careful work), flash differential scanning calorimetry, using samples a factor of 1000 smaller, increases the uncertainty of heat capacity measurements by a factor of <3, opening the door for meaningful measurements on ultra-small, high-pressure samples and other quantity-limited materials.

Instruments & Instrumentation↗

Elucidating the mechanism underlying the augmented capacity of MoO 2 as an anode material in Li-ion batteries

Transition-metal oxide anode materials have been observed to possess an intriguing surplus of capacity beyond the expected values based on conversion reaction. However, the mechanisms behind this phenomenon have remained contentious and elusive. Here, this study focuses on synthesized nanosized molybdenum dioxide and its electrochemical performance as an anode material for Li-ion batteries. Our findings reveal a substantial increase in capacity upon cycling, achieving approximately 1688 mA h g -1 , nearly double the theoretical capacity, after 700 cycles at a 1C rate. To elucidate the mechanisms underlying this augmented capacity, a comprehensive analysis employing in situ and ex situ X-ray diffraction, X-ray absorption spectroscopy, scanning electron microscopy, and transmission electron microscopy was conducted at various stages of the Li-ion cell cycling. Our results indicate that no conversion reaction occurs during the initial discharge phase, with Li 2 O and Mo remaining undetected. Instead, Li 0.98 MoO 2 is generated upon lithiation. Further materials characterization employing electron energy loss spectroscopy and energy-dispersive X-ray spectroscopy on the cycled electrode suggests the potential formation of a metallic Li-rich layer at the interface of the Li-ion intercalated phase subsequent to the formation of Li 0.98 MoO 2 , contributing to the surplus Li storage. Moreover, electrochemical impedance spectroscopy coupled with ex situ SEM and TEM analyses reveals that alterations in particle size and morphology, along with changes in the solid electrolyte interphase (SEI) resistance, are instrumental in the capacity variation observed upon cycling.

25 ENERGY STORAGE↗

Opportunities for Hybrid Wind and Solar PV Plants in India

The share of variable renewable energy (VRE) on India's grid has surpassed 100 GW, and the government has ambitious plans reach 450 GW by 2030. One strategy to increase wind and solar PV deployment is through the co-location of wind and solar PV plants to form a single hybrid power plant. Hybrid plants have the potential to reduce transmission infrastructure costs and variability in the output power profile compared to a standalone plant with a single technology, and this resource analysis aims to take a first step towards quantifying the potential savings from hybridizing wind and solar PV plants in India and the size of this opportunity. We utilize a brute-force optimization to minimize the levelized cost of energy (LCOE) for standalone wind, standalone solar PV, and hybrid wind/solar PV plants across all of India. By comparing these LCOEs, we determine that locations where hybrid plants exhibit potential cost savings and grid benefits exhibit both; a high interconnection cost and; a wind capacity factor between roughly 34% and 38%. However, because our work does not capture the value of the electricity generated by looking at energy prices, nor does it quantify the potential of hybrids to provide other value streams such as firm capacity and reserves. Further, because the work does not compare solar PV and wind hybrids to alternative generation technologies or storage systems, it cannot be considered a holistic cost-benefit analysis.

14 SOLAR ENERGY↗

Hybrid power plants: An effective way of decreasing loss-of-load expectation

Diversifying variable renewable resources by combining wind, solar photovoltaic, and battery assets in a hybrid power plant can increase renewable energy usage efficiency and improve system flexibility, particularly in distributed energy systems. However, the resilience impact of these systems, particularly outage mitigation, can be difficult to quantify due to uncertainty in resource, energy demand, and outage occurrence. Here, this study outlines a framework to quantify the incremental benefit of hybrid power plant assets for reducing loss-of-load expectation during random outage events. Hybrid power plant performance during outages (considering varying duration and severity) is simulated using a Monte Carlo methodology to reflect uncertainty associated with renewable resource, load demand, and outage timing. Results demonstrate the additional incremental value from increasingly hybrid designs, in which relative capacities of wind, solar photovoltaic, and storage assets contribute to lower loss-of-load expectation than the constituent technologies would alone. The value of added wind or solar capacity increases as the plant composition approaches an equal split. The value of added battery capacity depends on the outage duration and severity, but the first 50 MWh of added storage capacity is the most valuable for reducing the loss-of-load expectation for all plant designs.

14 SOLAR ENERGY↗

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Strong magnetocaloric effect induced by spin reorientation transitions in epitaxial Ho thin films

In this work, magnetocaloric effect (MCE) in an antiferromagnetic holmium (Ho) film is studied near the spin reorientation temperatures. A series of magnetization isotherms from 60 to 150 K around the Néel temperature, $T_N$ ≈ 130 K were recorded for both in-plane and out-of-plane magnetic field orientations. A change in entropy, Δ$S_M$ of –5 J/kgK was found near $T_N$ for an in-plane field orientation. A large change in Δ$S_M$ of –11.8 J/kg K due to a fan-helix spin transition at $\textit{T}$ = 90 K is observed for an in-plane field orientation. Spin transition at both $T_N$ and at the fan-helix transition exhibit larger MCE in the in-plane field orientations in comparison with the perpendicular orientation. The value of the refrigerant capacity extracted from the temperature dependence of Δ$S_M(T)$ is found to be larger for the “in- plane” orientation by a factor of two.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Predicting partner fitness based on spatial structuring in a light-driven microbial community

Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology ( e . g ., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function.

59 BASIC BIOLOGICAL SCIENCES↗

Technology Feasibility of High-Temperature Heat Pumps for Industrial Drying Process in the US

High-temperature heat pumps are a prospective technology for electrifying and decarbonizing industrial drying processes. This study investigates the technological potential of HTHPs in replacing fossil-fuel burners or steam boilers in industrial spray dryers. The performance of HTHPs with three configurations was investigated, including high high-temperature heat pump boosted with an electric air heater, a steam-generating high-temperature heat pump with multi-stage mechanical vapor compressions, and transcritical high-temperature heat pumps. R1336mzz(Z) is used as the refrigerant in both subcritical and transcritical high-temperature heat pumps, and R717 is used as the working fluid in the mechanical vapor recompression and the heat transfer fluids. Thermodynamic models are built to evaluate the energy efficiency of HTHPs. A case study was carried out on an industrial spray dryer integrated with a waste heat recuperator, where the HTHPs are used to recover precooled air with a dew point of 40℃ and supply heat for drying air at 200℃. For a high-temperature heat pump boosted with an electric air heater, a higher system-level COP is achieved with a high supply temperature from high-temperature heat pump. For a high-temperature heat pump with mechanical vapor recompressions, larger temperature drops in the flashing tank provide higher heat capacities but almost constant values of the coefficient of performance. For a transcritical high-temperature heat pump, an optimum discharge pressure exists for the temperature profiles within the gas cooler and the coefficient of performance. The transcritical high-temperature heat pump provides the best energy efficiency among the three configurations. The theoretical results prove the technical feasibility of high-temperature heat pumps in industrial air-drying applications. .

Wang, Pengtao↗

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene↗

Capacity and Coulombic Efficiency Measurements Underestimate the Rate of SEI Growth in Silicon Anodes

Capacity measurements and related quantities are the first layer of information acquired during testing of Li-ion cells. It is generally considered that elevated values of coulombic efficiency and capacity retention are absolute indicators of the existence of a stable solid electrolyte interphase (SEI). Here, we challenge this notion by analyzing how the effect of side reactions on cell capacity depends on the choice of electrodes. More specifically, we demonstrate that the extent of measurable capacity fade due to SEI growth is modulated by the shape of the voltage profile of the cathode and anode at the end of charge and discharge half-cycles. This shape-dependency creates a mismatch between SEI growth and cell capacity loss, which is relatively small for graphite anodes but sizable for silicon-containing electrodes. We illustrate this point by showing that, at the same coulombic efficiency and capacity retention, cells containing silicon-based materials could actually exhibit rates of SEI growth that are as much as ≥ 40% higher than graphite cells. The main implication of this behavior is that, for certain systems, capacity measurements may be an unreliable source of information about the extent of reactions at the SEI, allowing other consequences of these side reactions (such as electrolyte depletion) to proceed unchecked while the cell appears to be stable.

25 ENERGY STORAGE↗