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At least 91 records · Page 5

Pilot scale testing of an advanced solvent in a 0.7 MWe post-combustion CO 2 capture unit

An advanced Amine Promoted Buffer Solution (APBS), APBS-CDRMax® (CDRMax), developed by Carbon Clean Solutions Limited (CCSL), was tested at the 0.7 MWe CO 2 capture facility at Kentucky Utilities E.W. Brown Generation Station using a heat-integrated two-staged stripping CO 2 capture process. The performance of the solvent was evaluated to determine operating conditions that maximized the cyclic capacity of the solvent and results in energy savings. The regeneration energy ranged from 2.9 to 3.3 GJ/ton CO 2 with 14 vol % (dry) CO 2 inlet and approximately 90 % capture. The difference in the reboiler specific heat duty at stripper pressures of 1.7 and 2.1 bar was minimal as similar amounts of water vapor were observed in the CO 2 product stream at stripper outlet. Recycling of product CO 2 increased the inlet CO 2 concentration to the absorber from 14 to 16 vol% which enhanced mass transfer from the gas to the solvent resulting in about 5 % reduction in the energy of regeneration at the lower stripper pressure. The solvent circulation rate was reduced by about 30 % relative to previous 30 wt% MEA campaign for the CO 2 target capture of 90 %. Finally, the reduced solvent make-up rate of CDRMax shows promise for capital and operating cost savings for post-combustion CO 2 capture.

42 ENGINEERING↗

Design of closed-loop recycling production of a Diels–Alder polymer from a biomass-derived difuran as a functional additive for polyurethanes

Acetalization of biomass-derived 5-hydroxymethyl furfural (HMF) with pentaerythritol produced a difuran (HPH) monomer in the presence of an acid catalyst. A recyclable polymer was then synthesized by Diels–Alder reaction of bismaleimide and the HMF-derived difuran (HPH). A polyurethane, produced from the Diels–Alder polymer has a higher glass transition temperature than a polyurethane, produced from ethylene glycol. The polyurethane, containing Diels–Alder polymer also has a self-healing ability. The Diels–Alder polymer could be hydrolyzed in acidic acetate buffer at 60 °C to produce the monomers for recycling. Each produced monomer was separated by solvent extraction, and the extracted monomers were recovered in different solvent fractions, such as aqueous, ethyl acetate, and acetone fractions. Techno economic analysis was used to assess the minimum selling price ($\$14.1$ per kg) for the primary production of Diels–Alder polymer at a feed capacity of 400 tons per year. The economic viability of the primary recovery process for the most expensive recovered monomer, bismaleimide, was assessed by calculating the minimum selling price of the bismaleimide ($\$15.2$ per kg). In conclusion, a circular closed-loop recycling production process for the Diels–Alder polymer was developed and this approach can produce the Diels–Alder polymer at $8.2 per kg when the feed capacity was 40 ktons per year.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient I/O for Neural Network Training with Compressed Data

FanStore is a shared object store that enables efficient and scalable neural network training on supercomputers. By providing a global cache layer on node-local burst buffers using a compressed representation, it significantly enhances the processing capability of deep learning (DL) applications on existing hardware. In addition, FanStore allows POSIX-compliant file access to the compressed data in user space. We investigate the tradeoff between runtime overhead and data compression ratio using real-world datasets and applications, and propose a compressor selection algorithm to maximize storage capacity given performance constraints. We consider both asynchronous (i.e., with prefetching) and synchronous I/O strategies, and propose mechanisms for selecting compressors for both approaches. Using FanStore, the same storage hardware can host 2-13x more data for example applications without significant runtime overhead. Empirically, our experiments show that FanStore scales to 512 compute nodes with near linear performance scalability.

Zhang, Zhao↗

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) 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.

CERF↗

Heteroatom anchoring to enhance electrochemical reversibility for high-voltage P2-type oxide cathodes of sodium-ion batteries

P2-type cathode has received extensive attention due to its faster Na+ diffusion and a high theoretical capacity in sodium-ion batteries (SIBs). However, undesirable phase transformations have induced dramatic capacity decay of SIBs during the cycling process. In this study, heteroatom anchoring through Cu/Mg dual doping is introduced into P2-type Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode to enhance high-voltage electrochemical reversibility and modulate interfacial Na + kinetics. Further, the as-prepared Na 0.67 Ni 0.23 Mg 0.05 Cu 0.05 Mn 0.67 O 2 exhibits an outstanding capacity retention (83.4% after 2000 cycles at 10C) and rate performance (73 mAh g -1 at 10C, accounting for 58.7% of that at 0.1 C) over the voltage range of 2.5–4.4 V. Intensive explorations further manifest that the modified mechanism of dual-ion doping strategy is attributed to the synergistic coupling effect of a substantial change in Na occupancy distribution and an increase in oxygen vacancy buffer. Thus, the optimized cathode expedites Na + diffusion and reduces detrimental phase transformation, which favors high-rate performance and long-term cycling stability. This study develops a route to rationally design high-voltage cathode materials for SIBs.

25 ENERGY STORAGE↗

Unraveling electrochemo-mechanical aspects of core–shell composite cathode for sulfide based all-solid-state batteries

All-solid-state lithium batteries (ASSLBs) are emerging as promising next-generation batteries for electric vehicles owing to their high energy densities and safety features. However, challenges such as inadequate material percolation and low cathode utilization often hinder their potential. This paper presents a core–shell approach to optimize the cathode active material (CAM) utilization. The resultant CAM composite showed high ionic conductivity, a highly dense microstructure with <10% porosity, and minimal stack pressure changes during electrochemical cycling. The maximum CAM utilization was achieved while effectively mitigating electrochemo-mechanical side reactions by applying a uniformly coated Li 6 PS 5 Cl solid electrolyte layer (≈500 nm) and a LiNbO 3 buffer layer (≈10 nm) onto LiNi 0.8 Mn 0.1 Co 0.1 O 2 particles (LPSCl@LNO@NMC). The engineered LPSCl@LNO@NMC composites, which incorporated a 5 wt% LPSCl coating on LNO@NMC powders, exhibited a dense microstructure that enhanced the mechanical stability at the cathode. Sulfide-based solid electrolyte (SSE)/SSE contact provided better ionic pathways within the composite and increased CAM utilization. Thus, an enhanced reversible capacity (197 mA h g -1 ) and exceptional high-rate cycling performance (86.3% capacity retention after 1000 cycles at 2C) were observed. These findings pave the way for the advancement and commercialization of high-performance ASSLBs.

25 ENERGY STORAGE↗

Interface stability of LiCl-rich argyrodite Li 6 PS 5 Cl with propylene carbonate boosts high-performance lithium batteries

In solid-state lithium (Li)-metal batteries (SSLMBs), sulfide-based Li-ion conductors represent one of the most popular solid electrolytes (SEs). However, the development of sulfide-based SSLMBs is significantly hampered by interfacial issues including large solid-solid contact resistance and serious side reactions at the SE/electrode interface. To address these issues, here, we demonstrated a simple and efficient strategy by using LiCl-rich argyrodite Li 6 PS 5 Cl (Li 6 PS 5 Cl-LiCl) SE and trace amount of propylene carbonate (PC) at the SE/electrode interface to facilitate the formation of stable and robust solid electrolyte interphase (SEI). Additionally, the formed SEI not only serves as a buffer layer to passivate the interfacial reactions and suppress Li dendrite growth, but also acts as a bridge for Li-ion conduction to reduce the contact resistance. As a result, the Li||Li symmetric cell exhibited long-term electrochemical cycling stability over 1000 h at a current density of 0.2 mA cm -2 . Furthermore, the assembled Li||Li 4 Ti 5 O 12 (LTO) batteries delivered a specific capacity of 175 mAh g–1 at 0.2 C, and remained an excellent specific capacity of 116 mAh g –1 after 200 cycles at a high current rate of 1 C. These features indicate a feasible strategy to enhance the interfacial property of high-performance SSLMBs.

25 ENERGY STORAGE↗

Cathode-Confined Polysulfide Retention-Release Reprograms Li 2 S Deposition in High-Loading Li–S Batteries

High-loading lithium-sulfur (Li-S) cells operated with lean electrolyte are limited by polysulfide crossover to Li metal and by transport-limited liquid-solid conversion that forms passivating Li 2 S films. Here, we show that a cathode-facing separator coating of carboxylated multiwalled carbon nanotubes acts as a cathode-confined polysulfide reservoir with intermediate binding. Early in discharge it captures newly generated polysulfides at the separator interface, suppressing shuttle reactions. As polysulfides are consumed, the reservoir buffers concentration gradients and feeds reactants back to the cathode, shifting Li 2 S deposition from burst-like film growth to progressive, three-dimensional, porous formation. Synchrotron XRD and S K-edge XANES, together with Scharifker–Hills nucleation analysis and depth-of-discharge EIS/DRT, substantiate this coupled transport–reaction control. With 4.3 mg S cm -2 and E/S = 5, cells reach 4.2 mAh cm -2 and retain 90% capacity over 100 cycles at 20 °C.

25 ENERGY STORAGE↗

Buffering the impacts of extreme climate variability in the highly engineered Tigris Euphrates river system

More extreme and prolonged floods and droughts, commonly attributed to global warming, are affecting the livelihood of major sectors of the world’s population in many basins worldwide. While these events could introduce devastating socioeconomic impacts, highly engineered systems are better prepared for modulating these extreme climatic variabilities. Herein, we provide methodologies to assess the effectiveness of reservoirs in managing extreme floods and droughts and modulating their impacts in data-scarce river basins. Our analysis of multiple satellite missions and global land surface models over the Tigris-Euphrates Watershed (TEW; 30 dams; storage capacity: 250 km 3 ), showed a prolonged (2007–2018) and intense drought (Average Annual Precipitation [AAP]: < 400 km 3 ) with no parallels in the past 100 years (AAP during 1920–2020: 538 km 3 ) followed by 1-in-100-year extensive precipitation event (726 km 3 ) and an impressive recovery (113 ± 11 km 3 ) in 2019 amounting to 50% of losses endured during drought years. Dam reservoirs captured water equivalent to 40% of those losses in that year. Additional studies are required to investigate whether similar highly engineered watersheds with multi-year, high storage capacity can potentially modulate the impact of projected global warming-related increases in the frequency and intensity of extreme rainfall and drought events in the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗

Resource Adequacy and Capital Cost Considerations Pertaining to Large Electric Grids Powered by Wind, Solar, Storage, Gas, and Nuclear

The capacity and generation of wind, solar, storage, nuclear, and gas are estimated for large, idealized copper-plate electric grids. Wind and solar penetrations of 30% to 80% are considered together with different storage systems such as vanadium and lithium-ion batteries, pumped hydroelectric, compressed air, and hydrogen. In addition to a baseline dispatchable fleet without wind/solar, two bounding cases with wind/solar are analyzed: one without storage and one where the whole wind/solar fleet is connected to the storage system, hence providing a buffer between the wind/solar fleet and the grid. The reality will likely be somewhere between these bounding cases. The viability of a power grid with a large wind/solar penetration and no storage is not guaranteed but was nonetheless considered to provide a lower-bound capital cost estimate. Overall, the options that rely strongly on wind, solar, and storage could be significantly more capital-intensive than those that rely strongly on nuclear, depending on the amount of storage necessary to ensure grid stability. This is especially true in the long run because wind, solar, and storage assets have shorter lifetimes than nuclear plants and, consequently, need to be replaced more frequently. More analyses (e.g., grid stability and public acceptance) are necessary to determine which option is most likely to provide the path of least resistance to powering a clean, affordable, and reliable grid in a timely manner. Depending on the priorities, the path of least resistance may not necessarily be the one that is less capital intensive.

adequacy↗

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

Solution scattering at the Life Science X-ray Scattering (LiX) beamline

This work reports the instrumentation and software implementation at the Life Science X-ray Scattering (LiX) beamline at NSLS-II in support of biomolecular solution scattering. For automated static measurements, samples are stored in PCR tubes and grouped in 18-position sample holders. Unattended operations are enabled using a six-axis robot that exchanges sample holders between a storage box and a sample handler, transporting samples from the PCR tubes to the X-ray beam for scattering measurements. The storage box has a capacity of 20 sample holders. At full capacity, the measurements on all samples last for ∼9 h. For in-line size-exclusion chromatography, the beamline-control software coordinates with a commercial high-performance liquid chromatography (HPLC) system to measure multiple samples in batch mode. The beamline can switch between static and HPLC measurements instantaneously. In all measurements, the scattering data span a wide q -range of typically 0.006–3.2 Å −1 . Functionalities in the Python package py4xs have been developed to support automated data processing, including azimuthal averaging, merging data from multiple detectors, buffer scattering subtraction, data storage in HDF5 format and exporting the final data in a three-column text format that is acceptable by most data analysis tools. These functionalities have been integrated into graphical user interfaces that run in Jupyter notebooks, with hooks for external data analysis software.

60 APPLIED LIFE SCIENCES↗

Low Melting Temperature Gallium–Indium Liquid Metal Anode for Solid-State Li-Ion Batteries

Solid-state Li-ion batteries are attracting attention for their enhanced safety features, higher energy density, and broader operational temperature range compared to systems based on liquid electrolytes. However, current solid-state Li-ion batteries face performance challenges, such as suboptimal cycling and poor rate capabilities, often due to inadequate interfacial contact between the solid electrolyte and electrodes. To address this issue, we incorporated a gallium–indium (Ga–In) liquid metal as the anode in a solid-state Li-ion battery setup, employing Li 6 PS 5 Cl as the solid electrolyte. Operating at room temperature, this configuration achieved an initial capacity of 389 mAh g –1 and maintained 88% of this capacity after 30 cycles at a 0.05 C rate. It also demonstrated a capacity retention of 66% after 500 cycles at a 0.5 C rate. In comparison to solid anode materials, such as tin, the Ga–In liquid metal exhibited superior cycling stability and rate capacity, which is due to the self-healing and fluid properties of the alloy that ensure stable interfacial contact with solid electrolytes. In situ X-ray diffraction (XRD) and ex situ scanning electron microscope (SEM) analyses revealed that indium does not directly participate in the lithiation/delithiation process. Instead, it helps maintain the alloy’s low melting point, facilitating its return to a liquid state after delithiation. In a comparative analysis of stack pressure during cycling in cells utilizing Ga–In liquid metal and tin, the Ga–In liquid metal cell demonstrated an ability to buffer pressure increases associated with deformation. In conclusion, these findings suggest a promising approach for enhancing solid-state batteries by integrating liquid metal anodes, which improve interfacial contact and stability.

Alloys↗

A control oriented comprehensive degradation model for battery energy storage system life prediction

In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.

25 ENERGY STORAGE↗

Thermal Charging Rate of Composite Wax-Expanded Graphite Phase Change Materials

Phase change materials (PCMs) are valuable for their ability to store heat nearly isothermally around their phase transition temperature. PCMs are at the core of latent heat thermal energy storage (LHTES) systems, which provide the ability to buffer high thermal loads or decouple the time when heating or cooling is needed from when it is produced. Thermal charging and discharging of LHTES systems often employ a constant temperature source, and the rate at which heat can be exchanged is dependent on the thermophysical properties of the PCM. For graphite composite PCMs, the high thermal conductivity of the graphite enables an increased heat transfer rate through the material, but its presence displaces PCM which reduces the effective volumetric latent heat of the composite relative to the pure PCM. This results in a tradeoff between thermal power and volumetric energy storage capacity. The thermal charging rate is the average thermal energy stored in the material for some elapsed time. In this study, composite PCMs of compressed expanded natural graphite (CENG) and n-Octadecane are studied. Samples with varying CENG mass fractions were synthesized and the thermal charging rate was measured under a constant temperature boundary condition. For evaluation of the expanded graphite-PCM composite, one boundary of the material was exposed to a 50°C constant temperature plate, above the 27.5°C melting temperature of the PCM. The melting front progression [mm-s-1] and the thermal charging rate [W-cm-2] of the PCM were determined, and the results were compared with analytical predictions for the 1-D semi-infinite phase change. For CENG addition up to 5.75% mass fraction, a 450% thermal conductivity increase was observed with a 5% decrease in volumetric energy density as compared to pure octadecane. The average thermal charging rate was increased by over 430% for the melt to penetrate a depth of 22 mm. The experimental results matched analytical predictions, indicating that higher CENG fractions can be evaluated using analytical approaches.

Hirschey, Jason↗

Nanotubes Growth by Self-Assembly of DNA Strands at Room Temperature

Artificial biomolecular nanotubes are a promising approach to building materials mimicking the capacity of the cellular cytoskeleton to grow and self-organize dynamically. Nucleic acid nanotechnology has demonstrated a variety of self-assembling nanotubes with programmable, robust features and morphological similarities to actual cytoskeleton components. However, their production typically requires thermal annealing, which not only poses a general constraint on their potential applications but is also incompatible with physiological conditions. Here, we demonstrate that DNA nanotubes can self-assemble from a simple mixture of five short DNA strands at constant room temperature, growing for extended periods of time in bulk conditions as well as under confinement. Assembly is achieved using a monovalent salt buffer, which ensures a faithful nanoscale arrangement and avoids nanotube aggregation. We observe the formation of individual nanotubes up to 20 days with a diameter of 22 ± 4 nm and length of several tens of micrometers. We finally encapsulate the strands in microsized compartments, such as water-in-oil microdroplets and giant unilamellar vesicles serving as simple cell models. Notably, nanotubes not only isothermally self-assemble directly inside the microcompartments but also self-organize into dynamic higher-order structures resembling rings and dynamic networks. Our study provides an advantageous method for in situ assembly of programmable biomolecular scaffolds and materials using synthetic DNA strands without requirements of thermal treatment.

Chemistry↗

Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration

Abstract. Future global changes will impact carbon (C) fluxes and pools in most terrestrial ecosystems and the feedback of terrestrial carbon cycling to atmospheric CO2. Determining the vulnerability of C in ecosystems to future environmental change is thus vital for targeted land management and policy. The C capacity of an ecosystem is a function of its C inputs (e.g., net primary productivity – NPP) and how long C remains in the system before being respired back to the atmosphere. The proportion of C capacity currently stored by an ecosystem (i.e., its C saturation) provides information about the potential for long-term C pools to be altered by environmental and land management regimes. We estimated C capacity, C saturation, NPP, and ecosystem C residence time in six US grasslands spanning temperature and precipitation gradients by integrating high temporal resolution C pool and flux data with a process-based C model. As expected, NPP across grasslands was strongly correlated with mean annual precipitation (MAP), yet C residence time was not related to MAP or mean annual temperature (MAT). We link soil temperature, soil moisture, and inherent C turnover rates (potentially due to microbial function and tissue quality) as determinants of carbon residence time. Overall, we found that intermediates between extremes in moisture and temperature had low C saturation, indicating that C in these grasslands may trend upwards and be buffered against global change impacts. Hot and dry grasslands had greatest C saturation due to both small C inputs through NPP and high C turnover rates during soil moisture conditions favorable for microbial activity. Additionally, leaching of soil C during monsoon events may lead to C loss. C saturation was also high in tallgrass prairie due to frequent fire that reduced inputs of aboveground plant material. Accordingly, we suggest that both hot, dry ecosystems and those frequently disturbed should be subject to careful land management and policy decisions to prevent losses of C stored in these systems.

58 GEOSCIENCES↗