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At least 37 records · Page 2

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗

The importance of delayed neutron precursors in gamma dose calculations for activated primary heat exchanger components in the Molten Salt Breeder Reactor

The Molten Salt Reactor (MSR) Multiphysics Applications technical area in the Nuclear Energy Advanced Modeling and Simulation program has supported the development of 3D Monte Carlo models of the Molten Salt Breeder Reactor (MSBR) over the last couple of years. This MSBR model was previously run with the Shift Monte Carlo code to perform radiation shielding calculations in the reactor cell area. The MSBR is a 2250 MWth (1000 MWe) liquid-fueled molten salt reactor design developed at Oak Ridge National Laboratory in the 1970s. Determining the source terms from activated primary heat exchanger (HX) components is important because delayed and prompt neutron fluxes incident on these components affect the dose rate in the primary HX maintenance areas. This information can be used in the development of remote handling procedures required during shutdown for maintenance. A methodology has been developed and is proposed in this paper to quantify the activated source term from the primary HX components as a result of the movement of the delayed neutron precursors in flowing primary fuel salt through the primary HXs in the MSBR. The goal of this research is to evaluate the gamma dose rates in the maintenance hatches above the primary HX using the activated HX source terms. The study showed that the gamma dose rates are approximately two orders of magnitudes higher when accounting for the neutron activation from the movement of delayed neutron precursors through the HXs than when flowing fuel is not considered. Thus, the movement of delayed neutron precursors must be taken into account for accurately predicting the neutron activation of primary loop components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Canopy responses of Swedish primary and secondary forests to the 2018 drought

Boreal forest ecosystems are predicted to experience more frequent summer droughts due to climate change, posing a threat to future forest health and carbon sequestration. Forestry is a regionally dominant land use where the managed secondary forests are typically even-aged forests with low structural and tree species diversity. It is not well known if managed secondary forests and unmanaged primary forests respond to drought differently in part because the location of primary, unmanaged, forests has remained largely unknown. Here we employed a unique map detailing over 300 primary forests in Sweden. We studied impacts of the 2018 nationwide drought by extracting and analyzing a high-resolution remote sensing vegetation index over the primary forests and over buffer zones around the primary forests representing secondary forests. We controlled for topographical variations linked to soil moisture, which was a strong determinant of drought responses, and analyzed Landsat-derived EVI2 anomalies during the drought year from a multiyear non-drought baseline. We found that primary forests were less affected by the drought compared to secondary forests. Our results indicate that forestry may exacerbate the impact of drought in a future climate with more frequent and extreme hydroclimatic events.

54 ENVIRONMENTAL SCIENCES↗

Dl-3-n-butylphthalide promotes neurite outgrowth of primary cortical neurons by Sonic Hedgehog signaling via upregulating Gap43

Highlights: • NBP promoted neurite outgrowth in immature primary cortical neurons. • NBP increased axon and dendrite extension in mature primary cortical neurons. • NBP promoted neuritogenesis and neuronal plasticity via Shh signaling pathway. • The Shh signaling pathway increased Gap43 expression in primary cortical neuron. • NBP promoted neurite outgrowth by Shh signaling via upregulating Gap43 expression. Neurite outgrowth is the basis for wiring during the development of the nervous system. Dl-3-n-butylphthalide (NBP) has been recognized as a promising treatment to improve behavioral, neurological and cognitive outcomes in ischemic stroke. However, little is known about the effect and mechanism of NBP on the neurite outgrowth. In this study, we used different methods to investigate the potential effects of NBP on the neurite extension and plasticity of immature and mature primary cortical neurons and explored the underlying mechanisms. Our results demonstrated that in immature and mature cortical neurons, NBP promoted the neurite length and intersections, increased neuritic arborization, elevated numbers of neurite branch and terminal points and improved neurite complexity and plasticity of neuronal development processes. Besides, our data revealed that NBP promoted neurite extension and branching partly by activating Shh signaling pathway via increasing Gap43 expression both in immature and mature primary cortical neurons. The present study provided new insights into the contribution of NBP in neuronal plasticity and unveiled a novel pathway to induce Gap43 expression in primary cortical neurons.

60 APPLIED LIFE SCIENCES↗

Insights into the year-round vertical distribution of chlorophyll concentration in high-latitude Arctic Ocean: implications for primary production

Climate-induced rapid changes in the Arctic Ocean, such as decreasing sea ice extent and increasing water temperature, are altering nutrient and light availability, profoundly impacting primary producer growth. However, access to the high-latitude Arctic Ocean is limited, and satellite data are primarily available only during summer, making continuous in-situ data collection challenging. We collected year-round chlorophyll-a (Chl-a) concentration data in high-latitude regions using a mooring system and performed a comparative analysis with reanalysis data. Unlike previous satellite-based studies, which typically rely on surface measurements, we used the annual vertical distribution of Chl-a. These data were applied to the vertically generalized production model to accurately estimate annual primary production. The moored Chl-a concentration data showed that phytoplankton exhibited a typical subsurface chlorophyll maximum (SCM) layer as sea ice retreated in June. Contrary to the gradually deepening SCM distribution predicted by model-based reanalysis data, the SCM layer persisted for approximately 4 months. This indicates that light and nutrient conditions within the SCM layer remained stable, sustaining continuous phytoplankton growth. Annual primary production, reflecting this vertical distribution of Chl-a concentration, was 6.85 gC m −2 yr −1 . This exceeded satellite-based estimates by at least two-fold, highlighting the significant underestimation of primary production by satellite approaches. Estimating primary production while accounting for the vertical distribution of phytoplankton and light is essential for improving ecological models to better understand carbon cycle and food web changes in the Arctic Ocean, with important implications for climate change predictions.

Arctic Ocean↗

Structural complexity and primary production resistance are coupled in a temperate forest

The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.

lidar—remote sensing↗

Achieving Flat-on Primary Crystals by Nanoconfined Crystallization in High-Temperature Polycarbonate/Poly(vinylidene fluoride) Multilayer Films and Its Effect on Dielectric Insulation

To meet the stringent requirements of next-generation film capacitors for power electronics, multilayer films (MLFs) are fabricated with the advantage of achieving high temperature rating, high energy density, and reasonably low loss simultaneously. In this study, a high permittivity polar polymer, poly(vinylidene fluoride) (PVDF), is multilayered with a linear, low loss dielectric polymer such as high-temperature polycarbonate (HTPC). However, the dielectric loss of these MLFs was still high as compared with current state-of-the-art biaxially oriented polypropylene (BOPP) films. The goal of this work is to decrease the dielectric loss and enhance dielectric insulation by achieving flat-on primary PVDF crystals in MLFs via nanoconfined melt-recrystallization. Based on simultaneous small- and wide-angle X-ray scattering experiments, edge-on lamellar crystals were observed for all as-extruded MLFs, regardless of different PVDF layer thicknesses. However, after melting at 180 °C followed by recrystallization, flat-on primary crystals were successfully achieved when the PVDF layer thickness was below 39 nm. Above 78 nm for the PVDF layer, major edge-on primary crystals with minor flat-on secondary crystals were observed. Furthermore, from leakage current, breakdown, lifetime, and electric displacement-electric field loop studies, MLFs with the flat-on primary crystals exhibited reduced loss and enhanced dielectric insulation as compared to as-extruded MLFs and those with edge-on primary/flat-on secondary crystals. This was attributed to the effective blockage of charge carriers by the flat-on PVDF primary crystals and their reduced ferroelectric switching.

36 MATERIALS SCIENCE↗

Perturbation of soil organic carbon induced by land-use change from primary forest

Abstract The impact of land-use change (LUC) on soil organic carbon (SOC) has been a wide concern of land management policymakers because CO 2 emissions induced by LUC have been the second largest carbon source worldwide. However, due to insufficient data quality and limited biome coverage, a global big picture of the impact of LUC on SOC is still not clear. This study conducted a meta-analysis on 288 independent observations sourced from 62 peer-reviewed papers to provide a global summary of the change in SOC after the conversion of primary forests into other land-use types. The conversion of primary forest to cropland resulted in the most severe SOC loss (−33.2%), followed by conversion into plantation forests (−22.3%) and secondary forests (−19.1%). Nonetheless, SOC increased by 9.1% after a conversion from primary forests into pasture. More SOC loss was found at sites with lower precipitation for primary forests converted to cropland and plantation forests. The SOC loss decreased consistently with increasing mean annual temperature (MAT) for all four types of LUC. Moreover, the loss of SOC tended to worsen over time when primary forests are converted to cropland or plantation forests. In contrast, SOC loss recovered over time following conversion to secondary forests. The gain of SOC gradually increased over time after conversion to pastures. To conclude, the changes in SOC are related not only to the land-use type but also to precipitation, temperature and turn years after LUC. Due to limited data, this study focuses on soil profiles within 30 cm depth, and future research should explore SOC dynamics induced by LUC at greater depths. Overall, cases of SOC loss of approximately 30% following deforestation were very common (except for conversion to pasture), and the results of this study show that the loss of SOC following LUC should be carefully considered and monitored in land management.

Zhang, Zhiyuan (ORCID:0000000223407001)↗

Primary $\gamma$-ray intensities and $\gamma$-strength functions from discrete two-step $\gamma$-ray cascades in radiative proton-capture experiments

Background: Reaction rates of radiative capture reactions can play a crucial role in the nucleosynthesis of heavy nuclei in explosive stellar environments. These reaction rates depend strongly on $\gamma$-ray decay widths in the reaction products, which are, for nonresonant capture reactions at high excitation energies, derived from the $\gamma$-ray strength function and the nuclear level density. Recently, the ratio method was applied to primary $\gamma$ rays observed from ($\textit{d, p}$) reactions and nuclear resonance fluorescence measurements to extract the dipole strength in atomic nuclei and to test the generalized Brink-Axel hypothesis. Purpose: The purpose of this work is to apply the ratio method to primary $\gamma$-ray intensities of the 63,65 Cu($\textit{p},\gamma$) reactions to extract $\gamma$-ray strength information on the nuclei 64,66 Zn. Here, the impact of spin distribution, total $\gamma$-ray decay widths, level densities, and width fluctuations on the application of the ratio method will be discussed. Additionally, by comparing the relative $\gamma$-ray strength at different excitation energies, conclusions on the validity of the generalized Brink-Axel hypothesis can be made. Method: The radiative proton capture reaction measurements have been performed at the HORUS $\gamma$-ray spectrometer of the University of Cologne at one excitation energy for each reaction. Primary $\gamma$-ray intensities have been determined by normalizing secondary $\gamma$-ray transitions in two-step cascades using their absolute branching ratio. The ratio method was applied to the measured primary $\gamma$-ray intensities as well as to previous measurements by Erlandsson et al. at different excitation energies. Results: The relative strength function curve for 64 Zn from our measurement shows no significant deviation from the previous measurement at a different excitation energy. The same is true for 66 Zn where both measurements were at almost the same excitation energy. Absolute $\gamma$-strength function values have been obtained by normalizing the relative curves to quasiparticle random phase approximation calculations because of the absence of experimental data in the respective energy region. Conclusion: The generalized Brink-Axel hypothesis, i.e., the independence of the strength function on the excitation energy, seems to hold in the studied energy region and nuclei. The method to obtain primary $\gamma$-ray intensities from two-step cascade spectra was shown to be a valuable and sensitive tool although its uncertainties are connected to the knowledge of the low-energy level scheme of the investigated nucleus. The scaling in the ratio method should be taken with care, because the relative strength is not a simple sum of $f_{E1}$ and $f_{M1}$ but a somewhat complex linear combination dependent on the excitation energy of the nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗

Dual-mode fiber-optic refractive-index gas thermometry with primary anchoring and continuous temperature tracking

Extending fiber-optic refractive-index gas thermometry beyond primary-only operation, we report a dual-mode argon-filled Fabry-Perot thermometer in which the same cavity first establishes a primary temperature anchor and then performs continuous secondary-mode tracking. The primary anchor is obtained from two-pressure fringe shifts using a virial-coefficient refractivity model. During secondary operation, pressure cycling is stopped, and temperature is recovered from the monitored fringe wavelength and gas pressure using a model that includes argon refractivity, pressure-induced cavity strain, and fused-silica thermal expansion. From 310 to 1013 K, secondary-mode temperatures agreed with a reference thermocouple with 0.21 K RMSE and 0.47 K maximum error; 45-min natural furnace cooldowns were also tracked from nearby anchors with close agreement. The dual-mode method retains the empirical-calibration-free primary measurement as an in-situ reference while enabling simpler continuous tracking between anchors, addressing a practical limitation of primary-only fiberoptic refractive-index gas thermometry for hightemperature applications.

Syed, Musaddeque [Michigan State University, East ↗

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops an approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurements. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements: Preprint

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops an approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurements. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Improvement of the NOvA Near Detector Event Reconstruction and Primary Vertexing through the Application of Machine Learning Methods

The purpose of this work is to examine the application of a deep learning model in event reconstruction of neutrino interactions. The challenges faced in event reconstruction include the placement of an accurate primary neutrino interaction vertex which is used to support the particle track and prong algorithms. The result of accurate primary vertex ensures all particles involved in a neutrino interaction are included. We propose a regression-based Convolutional Neural Network (CNN) method to predict the primary vertex of a particle interaction. We show that with raw two-dimensional pixel map views as input, the regression-based CNN can predict the primary vertex in all three coordinates. This work is applied as part of the NOvA (NuMI Off-axis $\nu_e$ Appearance) near detector reconstruction efforts. The primary vertex predicted by the regression-based CNN model shows promising results for future applications. This deep learning method can be extended to secondary vertexing through a Kernel Density Estimate algorithm discussed in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Integrating Reservoirs into the Dissolved Organic Matter Versus Primary Production Paradigm: How Does Chlorophyll-$a$ Change Across Dissolved Organic Carbon Concentrations in Reservoirs?

Primary production in freshwater ecosystems is largely a function of light and nutrient availability, both of which have been changing in many lakes and reservoirs in response to anthropogenic pressures. Recent studies focusing on natural lakes have found a hump-shaped response of primary production (sometimes measured as chlorophyll-$a$) to dissolved organic matter (DOM, measured as dissolved organic carbon, DOC), which has both light-absorbing chromophoric properties and DOM-bound nutrients. We used the United States National Lakes Assessment dataset to integrate reservoirs into this paradigm in comparison with natural lakes and assessed the relative differences in the predicted response’s model structure, regression parameter values, and drivers of the chlorophyll-$a$ residuals. We found that chlorophyll-$a$ in reservoirs exhibited a hump-shaped response to DOC, while natural lakes from this dataset were better fit with a linear response, differing from previous studies focused on boreal lakes. Despite this, reservoirs had a greater maximum chlorophyll-a response compared to natural lakes in this study (45.5 versus 33.8 μg L -1 ), which occurred at a lower DOC concentration threshold (18.3 versus 26.4 mg L -1 ) when compared using quadratic models. Reservoirs had lower median light:nutrient values compared to natural lakes, and greater median surface area and total phosphorus (TP), that can all influence the light environment and the peak chlorophyll-a responses. In both reservoirs and natural lakes, chlorophyll-$a$ residuals were most strongly influenced by TP, where TP < 25-30 µg L -1 suppressed chlorophyll-a residuals and higher TP amplified them. Light:nutrient values were somewhat important predictors, and patterns with chlorophyll-$a$ residuals supported previous work showing low light:nutrient values amplified chlorophyll-$a$ responses and higher values suppressed them. In conclusion, quantifying the shape of the response of primary production to DOM quantity and quality as well as the drivers of the residuals, namely TP for lakes and reservoirs in this dataset, will be important for understanding the effects that changes in water quality may have on primary production and freshwater ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. In this work, ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Genotoxicity evaluation using primary hepatocytes isolated from rhesus macaque ( Macaca mulatta )

Non-human primates (NHPs) have played a vital role in fundamental, pre-clinical, and translational studies because of their high physiological and genetic similarity to humans. We report a method to isolate primary hepatocytes from the livers of rhesus macaques (Macaca mulatta) after in situ whole liver perfusion. Isolated primary macaque hepatocytes (PMHs) were treated with various compounds known to have different pathways of genotoxicity/carcinogenicity and the resulting DNA damage was evaluated using the high-throughput CometChip assay. The comet data were quantified using benchmark dose (BMD) modeling and the BMD50 values for treatments of PMHs were compared with those generated from primary human hepatocytes (PHHs) in our previous study. The results showed that despite varying CYP450 enzyme activities, PMHs had the same sensitivity and specificity as PHHs in detecting four indirect-acting (i.e., requiring metabolic activation) and seven direct-acting genotoxicants/carcinogens, as well as five non-carcinogens that are negative or equivocal for genotoxicity in vivo. The BMD50 estimates and their confidence intervals revealed species differences for DNA damage potency, especially for direct-acting compounds. The present study provides a practical method for maximizing the use of animal tissues by isolating primary hepatocytes from NHPs. Our data support the use of PMHs as a reliable surrogate of PHHs for evaluating the genotoxic hazards of chemical substances for humans.

59 BASIC BIOLOGICAL SCIENCES↗

Printed circuit primary heat exchanger for power conversion in heat pipe microreactor applications

Here, in the present study, a model was developed for a recuperated air Brayton cycle for heat pipe microreactors, and the effect of the primary heat exchanger type assessed. An annular flow heat exchanger and a printed circuit heat exchanger (PCHE) were evaluated. A sub-sized diffusion bonded, PCHE test specimen was manufactured and tested with nitrogen as the working fluid to validate and improve the PCHE model. A comparison of the thermal cycle efficiency for the Brayton cycle coupled to a heat pipe microreactor using each of the two primary heat exchangers showed competitive performance for both options, with achievable cycle efficiencies of 34 % and 35 % for the annular and printed circuit heat exchangers, respectively. The impact of heat pipe length and additional reheating stages on cycle efficiency was studied. Increasing the heat pipe condenser length from 0.8 to 2.0 m resulted in an increase in cycle efficiency of 3.5 % and 3.2 % for the annular and printed circuit heat exchangers, respectively. The use of additional reheating stages showed a reduction in cycle efficiency since the heat pipe surface area limits the primary heat exchanger size and effectiveness. These results highlight the importance of the primary heat exchanger on the performance of a heat pipe microreactor. Overall, the cycle model, testing, and heat exchanger model showed the potential for the PCHE to improve the economics of a heat pipe microreactor relative to the annular flow heat exchanger, which also opens the possibility to use different heat transfer fluids such as supercritical CO 2 .

PCHE↗