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At least 307 records · Page 17

Advanced Serpentine Heat Exchangers to Minimize Number of Joints and Leakage in HVAC&R Systems

Refrigerant leakage has a significant impact on heating, ventilation, air conditioning and refrigeration (HVAC&R) industries in terms of both greenhouse gas (GHG) emissions and lost efficiency of the systems themselves. One of the major causes of refrigerant leakage is braze joints within a vapor compression system. The brazing process is often inconsistent and almost always imperfect. As a result, braze joints are left vulnerable to leaks and can be weaker than non-brazed tubing. Conventional tube-fin heat exchangers are manufactured using one brazed joint per tube. An alternative to the conventional approach is the use of a single continuous serpentine tube. An Advanced Serpentine Heat Exchanger was developed to provide a heat transfer solution that meets or exceeds performance while also significantly reducing the number of joints and, consequently, the potential for refrigerant leakage. The developed serpentine heat exchanger not only delivers on performance, but is also cost competitive with conventional heat exchangers on the market.

30 DIRECT ENERGY CONVERSION↗

Molybdenum-99 from Molten Salt Reactor as a Source of Technetium-99m for Nuclear Medicine: Past, Current, and Future of Molybdenum-99

Technitium-99m ( 99m Tc), a widely used radioisotope, is used in tens of millions of medical diagnostic procedures annually. However, it is hard to store and must be immediately used upon production due to its short half-life (i.e., 6 h); thus, it is currently produced from 99 Mo, which itself is a result of 235 U fission. The majority of 99 Mo supplies to U.S. patients are currently provided by foreign producers and produced using highly enriched uranium (HEU). In order to minimize the proliferation risks of HEU-based medical isotope production, the U.S. Department of Energy’s National Nuclear Security Administration has funded a program to accelerate the development of technologies to produce 99 Mo without the use of HEU. Today, the global supply of 99 Mo depends on a limited number of nuclear reactors, and production has been interrupted unexpectedly since 2009 due to the fleet’s advanced age. Herein, alternative options for 99 Mo production are discussed, and one potential option is to obtain 99m Tc from molten salt reactors (MSRs). A MSR is a nuclear fission reactor that can operate at or close to atmospheric pressure with liquid fuel, which allows for producing isotopes in a timely manner. In this paper, the past and current production of 99 Mo via nuclear reactors is described, and the future of 99 Mo production by MSRs is discussed. The behavior and chemical properties of molybdenum in fluoride salts in MSRs and the possible extraction methods are also examined in addition to the limitation of current studies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The decay of HIV under anti-retroviral therapy is biphasic even in humanized mice with just T cells

HIV-1 plasma viral load decays in a biphasic manner during antiretroviral therapy (ART). It was hypothesized that this is due to infection of different cell types, namely CD4+ T cells and macrophages. We studied this possibility directly by modeling the decay of HIV-1 in humanized mice. We utilized previously published data from humanized T-cell only mice (TOM) and myeloid-only mice (MOM) infected with HIV-1 and treated with a potent ART regimen. Viral load decay dynamics were modeled using either a single or a biexponential decay fitted using nonlinear mixed effects techniques. Fits were compared using the corrected Bayesian information criterion (BICc). In TOM, the biphasic model was significantly better than a single-phase decay model (ΔBICc ≈ 16) despite additional parameters. In MOM, the biphasic decay was statistically better, but there was substantial uncertainty because the virus goes below detection very fast. The first-phase half-life was consistent between groups (1.2 days in MOM and 1.3 days in TOM) and similar to the half-life estimated in human infection. The second-phase decay in these mice was minimal likely due to low initial viral loads. Additional analyses with mice containing both CD4+ T cells and macrophages or X4-tropic virus-infected MOM mice confirmed the biphasic pattern, demonstrating the robustness of this result. The biphasic decline in HIV-1 occurs, even with only CD4+ T cells, refuting the hypothesis that distinct cell populations (CD4+ T cells and macrophages) drive each decay phase. These findings support an alternative model in which the observed dynamics arise from intrinsic properties of the viral infection lifecycle rather than from cellular compartmentalization.

59 BASIC BIOLOGICAL SCIENCES↗

Enabling Industrial Re-Use of Large-Format Additive Manufacturing Molding and Tooling

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications.

additive manufacturing↗

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mode connectivity in the loss landscape of parameterized quantum circuits

Variational training of parameterized quantum circuits (PQCs) underpins many workflows employed on near-term noisy intermediate scale quantum (NISQ) devices. It is a hybrid quantum-classical approach that minimizes an associated cost function in order to train a parameterized ansatz. In this work we adapt the qualitative loss landscape characterization for neural networks introduced in Goodfellow et al. (2014); Li et al. (2017) and tests for connectivity used in Draxler et al. (2018) to study the loss landscape features in PQC training. We present results for PQCs trained on a simple regression task, using the bilayer circuit ansatz, which consists of alternating layers of parameterized rotation gates and entangling gates. Multiple circuits are trained with 3 different batch gradient optimizers: stochastic gradient descent, the quantum natural gradient, and Adam. We identify large features in the landscape that can lead to faster convergence in training workflows.

97 MATHEMATICS AND COMPUTING↗

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗

Solid State Ionics: Materials Development by Multiscale Modeling and Advanced Manufacturing Techniques

Solid-state ionic materials are an important enabling technology for energy conversion and storage. Solid-state batteries would be a safer and higher energy density alternative to commercially available lithium ion batteries (LIB), however their implementation requires ion conduction in solids at room temperature to occur on the same level as the current generation of liquid electrolytes. Microstructural modifications have been demonstrated to play a major role on ion transport through the control of grain boundary interfaces, which traditionally serve as “blocking” layers. Ultimately, these materials will be fabricated in thin films form as electrolytes in order to minimize ohmic losses in electrochemical devices. This work uses advanced manufacturing techniques in combination with theoretical modeling to implement a science-based approach in the deposition of thin films ion conductors with controlled microstructures used in ceramic energy conversion and storage devices.

25 ENERGY STORAGE↗

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗

Spatiotemporal quenches for efficient critical ground state preparation in the two-dimensional transverse field Ising model

Quantum simulators have the potential to shed light on the study of quantum many-body systems and materials, offering unique insights into various quantum phenomena. Although adiabatic evolution has been conventionally employed for state preparation, it faces challenges when the system evolves too quickly or the coherence time is limited. In such cases, shortcuts to adiabaticity, such as spatiotemporal quenches, provide a promising alternative. This paper numerically investigates the application of spatiotemporal quenches in the two-dimensional transverse field Ising model with ferromagnetic interactions, focusing on the emergence of the ground state and its correlation properties at criticality when the gap vanishes. We demonstrate the effectiveness of these quenches in rapidly preparing ground states in critical systems. Our simulations reveal the existence of an optimal quench front velocity at the emergent speed of light, leading to minimal excitation energy density and correlation lengths of the order of finite system sizes we can simulate. These findings emphasize the potential of spatiotemporal quenches for efficient ground state preparation in quantum systems, with implications for the exploration of strongly correlated phases and programmable quantum computing.

2-dimensional systems↗

Mobilizing mine lands for biobased decarbonization strategies

Over 163 000 ha of mine lands in Pennsylvania (PA) have the potential to produce willow as a feedstock for renewable energy generation. Each year these lands could produce between 454 000 and 907 000 dry Mg of willow, which can be a feedstock for bioenergy (i.e., biopower) with carbon capture and sequestration (BECCS) or sustainable aviation fuel (SAF) production. We used a spatially explicit model to explore cost-minimized allocation of willow biomass from abandoned mine lands (AML) to be used for BECCS or SAF production and to abate carbon dioxide. The results suggest that between 454 000 and 907 000 dry Mg of biomass can be produced on AML in PA at costs from $94 to $250 per dry Mg. This AML willow biomass could be combined with other available biomass and aggregated to ten facilities to produce 17.9 TWh of power; alternatively, it could produce 958 million liters of jet fuel, 638 million liters of renewable diesel, and 1.289 billion liters of naphtha, along with 0.735 TWh of electricity. From this analysis, in PA, under the BECCS pathway, up to 36 million Mg per year of CO2 could be abated at costs of up to $134 per Mg; under the SAF pathway, up to 17.5 million Mg per year of CO2 could be abated at costs up to $150 per Mg of CO2. The use of mine land willow as a supplemental feedstock for SAF and BECCS would need strong incentive programs if costs of production are to be comparable with production on agricultural land.

Wahlstrom, Mallory [Pennsylvania State University]↗

Effect of reacting gas flowrates and hydration on the carbonation of anion exchange membrane fuel cells in the presence of CO 2

Anion exchange membrane fuel cells (AEMFCs) have been widely touted as a low-cost alternative to existing proton exchange membrane fuel cells. However, one of the limitations of this technology has been the severe performance penalty related to the introduction of CO 2 to the cell – typically in the air cathode feed. Introduction of CO 2 into AEMFCs results in cell carbonation, which imparts thermodynamic, kinetic and Ohmic overpotentials that can add up to hundreds of millivolts. Therefore, it is important to find strategies and operational protocols for AEMFCs that minimize these overpotentials. In this paper, we reserach the impacts of the anode and cathode flowrate, as well as the cell hydration level, on the extent of cell carbonation and cell polarization. Key findings include: (1) decreasing the cathode flowrate generally decreases the total CO 2 -related voltage loss while changing the anode flowrate has a minimal effect; (2) increasing cell hydration helps to mitigate the performance loss in the presence of CO 2 ; and (3) operational combinations are found that significantly reduce the CO 2 penalty compared to the present literature.

25 ENERGY STORAGE↗

Impact of Permanganate Oxidation of Glycolate on Corrosion of the Defense Waste Processing Facility (DWPF) Recycle Collection Tank (RCT), Transfer-line and Waste Tank Materials of Construction (MoC)

Savannah River Remediation (SRR) is evaluating the use of glycolic acid to replace formic acid as an alternate reductant for the Defense Waste Processing Facility (DWPF) at Savannah River Site (SRS). The replacement is aimed at reducing facility hazards, improving pH stability and rheological control, and lowering off gas production. Glycolate, which is the product that may remain, can also be carried downstream to High-Level Waste and Low-Level Waste facilities. Complete oxidation of glycolate and other organic species from the Sludge Receipt and Adjustment Tank (SRAT) may be necessary to minimize thermolytic hydrogen generation that can cause flammability issues. The glycolate oxidation may be performed in the Recycle Collection Tank (RCT). The RCT heel would be adjusted with sodium hydroxide to maintain the solution caustic and sodium nitrite as corrosion inhibitor prior to the addition of condensate that can be from the contents of the Slurry Mix Evaporator Condensate Tank (SMECT) or Offgas Condensate Tank (OGCT). The RCT tank collects the waste to be transferred via the Low Point Pump Pit – Recycle Pump Tank (LPPP-RPT) through a jacketed transfer-line to the Tank Farm facility. Scoping studies were performed to evaluate an oxidizing agent and sodium permanganate was selected as the best option for glycolate destruction. Testing was recommended to determine the impact on the Materials of Construction (MoC) due to the addition of sodium permanganate. The targeted concentration of sodium permanganate used equated to a 7:1 molar permanganate to glycolate ratio (nominally 0.002 M permanganate). However, to conservatively maximize the permanganate corrosivity, in some cases no glycolate was added.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Titanium Nitride as an Intermetallic Diffusion Barrier for Hydrogen Permeation in Palladium–Vanadium Composite Membranes

Hydrogen purification is a critical industrial process, and there are ongoing efforts to develop low-cost alternatives to palladium foil membranes. Titanium nitride (TiN) is studied as an interdiffusion barrier to enable hydrogen permeation in composite palladium–vanadium membranes. TiN was deposited via reactive sputtering, and films with the desired (200) orientation were obtained in the metallic regime at 400 °C under a 200 V bias to the substrate. The permeability of thin-film TiN was determined with palladium-based sandwich structures. TiN layers up to 10 nm resulted in a minimal decrease in flux (~20%) relative to a freestanding PdCu foil, which was attributed to the interfacial resistance. At greater thicknesses, the TiN layer was rate-limiting, and it was found that the effective permeability of the sputtered TiN thin films was ~6 × 10−12 mol s−1 m−1 Pa−0.5. Composite Pd|TiN|V|TiN|Pd membranes exhibited permeability values up to three times greater than pure palladium, exhibiting stability at 450 °C for over 100 h, with the lack of intermetallic diffusion and alloy formation being confirmed with XRD. The membranes were unstable at 500 °C, which was attributed to the instability of the thin Pd layer and loss of catalytic activity.

Biochemistry & Molecular Biology↗

Development of a directly driven multi-shell platform: Laser drive energetics

Simulations predict that directly driven multi-shell targets can provide a robust alternative to conventional high-convergence implosion concepts by coupling two to three times more energy into the final igniting thermonuclear fuel assembly than indirect-drive concepts. The three-shell directly driven Revolver concept [K. Molvig, M. J. Schmitt, B. J. Albright, E.S. Dodd, N.M. Hoffman, G.H. McCall, and S.D. Ramsey, Phys. Rev. Lett. 116, 255003 (2016)] utilizes a design that maximizes laser energy conversion into inward kinetic energy of the outermost ablator shell (~9%) while minimizing the DT fuel convergence (~9) to reduce the mixing of material from the innermost shell into the fuel. Inherent in this design concept is the use of 192 narrow beams (with a 1/e laser beam-to-capsule diameter ratio of 0.33) from the National Ignition Facility laser pointed in a polar direct drive laser configuration. In this paper, we demonstrate that low average laser intensity at the capsule surface (≤300 TW/cm 2 ) limits the measured laser backscatter, indicating that a greater amount of laser energy is coupled into the target. Omega experiments have been performed to determine the coupling of laser energy to the outermost shell of a scaled Revolver target (i.e., the ablator shell) by measuring capsule implosion trajectories and scattered-light fractions for two different drive configurations. Comparisons of simulated shell trajectory and velocity profiles with experimental data obtained from self-emission images show good agreement and are consistent with measured scattered light data. Furthermore, the low levels of scattered light measured are consistent with post-shot simulation results that show high hydro-coupling efficiency. These results strengthen the case for using narrow beams at low intensity to drive large ablator capsules for future direct-drive, multi-shell ignition concepts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Charge Block Length on Conformation and Solution Behavior of Polyampholytes

In this paper, we investigate the effect of charge block length on polyampholyte chain conformation and phase behavior using small-angle X-ray scattering (SAXS) and implicit-solvent molecular simulations. To this end, we use solid phase peptide synthesis to precision-tailor a series of polyampholytes consisting of l-glutamic acid (E) and l-lysine (K) monomers arranged in alternating blocks from 2 to 16 monomers. We observe that the polyampholytes tend to phase separate as block size increases. With addition of NaCl, phase separated polyampholytes exhibit a salting-in effect dependent on charge block length. Fourier-transform infrared (FTIR) spectroscopy reveals the presence of intramolecular hydrogen bonds that are disrupted upon the addition of NaCl, implicating both electrostatic interactions and hydrogen bonding in the phase behavior. SAXS spectra at no-added salt conditions show minimal dependence of charge block length on the radius of gyration (R g ) for soluble polyampholytes, but local chain stiffening is found to be dependent on charge block length. With increasing NaCl, consistent with electrostatic screening, all polyampholytes expand and behave as neutral or swollen chains in good solvent conditions. Molecular simulations are qualitatively consistent with experiments. Implications for understanding intracellular condensates and material design are noted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect-driven anomalous transport in fast-ion conducting solid electrolytes

We report solid-state ionic conduction is a key enabler of electrochemical energy storage and conversion. The mechanistic connections between material processing, defect chemistry, transport dynamics, and practical performance are of considerable importance, but remain incomplete. Here, inspired by studies of fluids and biophysical systems, we re-examine anomalous diffusion in the iconic two-dimensional fast-ion conductors, the β- and β"-aluminas. Using large-scale simulations, we reproduce the frequency dependence of alternating-current ionic conductivity data. We show how the distribution of charge-compensating defects, modulated by processing, drives static and dynamic disorder, which lead to persistent sub-diffusive ion transport at macroscopic timescales. We deconvolute the effects of repulsions between mobile ions, the attraction between the mobile ions and charge-compensating defects, and geometric crowding on ionic conductivity. Our quantitative framework based on these model solid electrolytes connects their atomistic defect chemistry to macroscopic performance with minimal assumptions and enables mechanism-driven 'atoms-to-device' optimization of fast-ion conductors.

25 ENERGY STORAGE↗