Search NASA⌕ Search

SEARCH · Search NASA

Results for “capacity enhancement”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Feasibility of enhancing carbon sequestration and stock capacity in temperate and boreal European forests via changes to management regimes

Forest management practices might act as nature-based methods to remove CO 2 from the atmosphere and slow anthropogenic climate change and thus support an EU forest-based climate change mitigation strategy. However, the extent to which diversified management actions could lead to quantitatively important changes in carbon sequestration and stocking capacity at the tree level remains to be thoroughly assessed. To that end, we used a state-of-the-science bio-geochemically based forest growth model to simulate effects of multiple forest management scenarios on net primary productivity (NPP) and potential carbon woody stocks (pCWS) under twenty scenarios of climate change in a suite of observed and virtual forest stands in temperate and boreal European forests. Previous modelling experiments indicated that the capacity of forests to assimilate and store atmospheric CO 2 in woody biomass is already being attained under business-as-usual forest management practices across a range of climate change scenarios. Nevertheless, we find that on the long-term, with increasing atmospheric CO 2 concentration and warming, managed forests show both higher productivity capacity and a larger potential pool size of stored carbon than unmanaged forests as long as thinning and tree harvesting are of moderate intensity.

54 ENVIRONMENTAL SCIENCES↗

Covalent adaptable networks for electrolyte–binder integration in recyclable lithium metal batteries

Lithium-metal batteries (LMBs) are considered a promising next-generation energy storage technology due to their exceptionally high energy density. However, the development of solid polymer electrolytes and cathode binders for LMBs faces critical challenges, including interfacial instability, poor recyclability, and growing environmental concerns. In particular, current systems often rely on non-recyclable components featuring permanently crosslinked networks and polyfluoroalkyl substances (PFAS), such as poly(vinylidene fluoride) (PVDF), which cause battery waste and environmental harm. Herein, we introduce a multifunctional covalent adaptable network (CAN) platform based on thermally reversible Diels–Alder (DA) chemistry, designed for dual functionality as a CAN-based electrolyte (CAE) and a CAN-based cathode binder. The CAE achieves high ionic conductivity and strong storage modulus (1.4 mS cm −1 and ∼ 10 5 Pa at room temperature, respectively) and enables stable long-term cycling in symmetric Li||Li cells for over 2000 h with low overpotential. When it is applied as a cathode binder in LiFePO 4 (LFP) composite electrodes (C-LFP), the CAN matrix significantly reduces interfacial resistance and enhances discharge capacity compared to conventional PVDF-based systems. Thermal treatment induces self-healing at the cathode–electrolyte interface, further improving contact and yielding a discharge capacity of 150 mAh g −1 at 0.5 C. Moreover, the dynamic CAN architecture allows efficient recovery and reuse of lithium salts from spent electrolytes through retro-DA reactions under mild conditions (∼80 °C), establishing a low-energy, cost-effective recycling pathway. In conclusion, this work presents a scalable and sustainable strategy for high-performance LMBs by integrating recyclability, interfacial healing, and PFAS-free design, offering a holistic solution aligned with circular economy principles and next-generation battery demands.

Diels–Alder↗

Experimental results of embedded phase change material capsules for increasing the performance of a wrapped heat pump water heater

Herein, to enhance the capacity of heat pump water heaters (HPWHs), high energy density phase change material (PCM) was used in two experimentally tested HPWH prototypes. Preliminary findings showed that in the PCM, stored thermal potential energy could be effectively converted into sensible heat in the water over a slight temperature difference, with the goal of increasing the capacity of hot water above a desired cut-off temperature. This exchange of energy results in an increased amount of hot water necessary for mixing at the location utilized by the consumer. It was also found that for a wrapped HPWH, there was an average increase of 27.7% in the capacity when 7.6 L of novel PCM filled spherical capsules were added to a 22.7 L tank downstream of the HPWH. In the second design (Beta), PCM capsules were immersed into the tank with a cylindrical geometry, and the UEF was increased by 5.5% over the baseline HPWH test result. As for the Beta design, heat loss was reduced significantly compared to a typical HPWH and the Alpha design. Food-grade PCMs were selected as appropriate. The novel encapsulation design increased the effective conductivity inside the capsule by adding metal fins.

42 ENGINEERING↗

A microgrid deployment framework to support drayage electrification

The electrification of heavy-duty commercial vehicles (HDCVs) is key to enhancing air quality and reducing urban air pollution, but it also imposes significant demands on an electric grid not designed for such high loads. Without complementary infrastructure, electrification may yield limited air quality improvements. This article explores the critical role of microgrids—integrating solar photovoltaics and battery storage—in supporting HDCV electrification. We present an integrated framework to identify viable microgrid sites in a given region, estimate deployment costs, and optimize power use to reduce dependence on the grid. As a case study, we apply the framework to the region around the Port of Savannah, GA, USA, demonstrating how targeted microgrid deployment can enhance grid capacity, improve energy resiliency, and support electrified freight transport.

Electrical engineering↗

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗

Evaluation of a high-throughput method for processing sponge-stick samples to detect viable, non-spore-forming biothreat agents

After a bioterrorism incident, surface sampling is often used to determine the extent of contamination and exposure, guiding decontamination efforts and decisions for re-occupancy of affected sites. The sponge-stick (SS) is a preferred and commonly used device for sample collection to detect both spore-forming and non-spore-forming biothreat agents from non-porous surfaces. Here, in this study, a recently developed high-throughput method (HTM) for processing SS samples to detect viable Bacillus anthracis spores was adapted for detection of non-spore-forming biothreat agents, Yersinia pestis and Francisella tularensis. The scalable HTM was used to process up to 20 SS samples simultaneously, compared to the current stomacher-based method which processes one SS at a time. Comparisons of the HTM and the stomacher-based method were statistically indistinguishable for most experiments (P > 0.05) with HTM recoveries of 37–60 % for Y. pestis inoculated at 102–103 cells/SS and held 48 h at 4 °C to mimic sample transport/storage. The HTM was integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis to detect viable Y. pestis in the presence of particulate contamination (Arizona Test Dust, ATD). This approach detected Y. pestis inoculated at 20 cells/SS and ATD did not impact detection (P > 0.05). F. tularensis showed significantly lower recoveries between no-hold time and 48-h hold time (4 °C, P < 0.05) using the HTM, which further testing showed could be due to toxicity of the neutralizing buffer used for SS pre-wetting. With modifications, this method could enhance throughput capacity while maintaining similar recovery efficiencies to current methods for other non-spore-forming bacterial pathogens.

Biological and medical sciences↗

XERICO as a target for engineering stress-resilient crops: Mechanisms, applications, and future directions

XERICO's capacity to enhance ABA-driven stress responses across diverse crops, its regulatory crosstalk with other hormonal pathways, and its compatibility with advanced genetic engineering tools highlight its central role in sustainable agriculture. Leveraging XERICO in crop improvement programs aligns with the urgent need to mitigate the impacts of climate-induced stress in agriculture, offering a pathway toward resilient and high-yielding crops. Here, by enabling crops to withstand drought and other environmental stresses, XERICO-based biotechnological approaches hold transformative potential for global food security and environmental sustainability.

09 BIOMASS FUELS↗

Minimizing grid energy consumption in wastewater treatment plants: Towards green energy solutions, water sustainability, and cleaner environment

Wastewater treatment plants (WWTPs) consume significant amount of energy to sustain their operation. From this point, the current study aims to enhance the capacity of these facilities to meet their energy needs by integrating renewable energy sources. The study focused on the investigation of two primary solar energy systems in As Samra WWTP in Jordan. The first system combines parabolic trough collectors (PTCs) with thermal energy storage (TES). This system primarily serves to fulfill the thermal energy demands of the plant by reducing the demands from boiler units, which allows more biogas for electricity generation. The second system is a photovoltaic (PV) system with Lithium-Ion batteries, which directly produces electricity that will be used to cover part of the electrical energy demands of plant. To assess the optimal configuration, two distinct scenarios have been formulated and compared to the current case scenario (SC#1). The first scenario focuses on maximizing the net present value (NPV) and minimizing the levelized cost of electricity (LCOE). The second scenario is centred on minimizing the levelized cost of heat (LCOH). The findings indicate that both scenarios succeeded in reducing the reliance on the grid to a value that reach 1 %. Moreover, they both reduced biogas percentage in energy production from 88 % to approximately 65 % through the integration of the PV system. In terms of thermal demand, SC#2 reduced the reliance on biogas boiler units from 100 % to 25 %, while SC#3 achieved an even more impressive reduction to just 8 %. The best LCOE value was attained in SC#2, at 0.0895 USD/kWh, with an NPV of 10.54 million USD. Conversely, SC# 3 yielded an LCOH value of 0.0432 USD/kWh th compared to 0.0534 USD/kWh th USD for SC#2. In conclusion, despite their relatively high capital and operating costs, SC#2 and SC#3 managed to substantially decrease the annual electricity expenditure from approximately 2 million USD to 86,000 USD and 0 USD, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Size-Selectively Biomolecule-Immobilized Nanoprobe-Based Chemiluminescent Lateral Flow Immunoassay for Detection of Avian-Origin Viruses

Here, a signal-amplifiable nanoprobe-based chemiluminescent lateral flow immunoassay (CL-LFA) was developed to detect avian influenza viruses (AIV) and other contagious and fatal viral avian-origin diseases worldwide. Signal-amplifiable nanoprobes are capable of size-selective immobilization of antibodies (binding receptors) and enzymes (signal transducers) on sensitive paper-based sensor platforms. Particle structure designs and conjugation pathways conducive for antigen accessibility to maximum amounts of immobilized enzymes and antibodies have advanced. The detection limit of the CL-LFA using the signal-amplifiable nanoprobe for the nucleoprotein of the H3N2 virus was 5 pM. Sensitivity tests for low pathogenicity avian influenza H9N2, H1N1, and high pathogenicity avian influenza H5N9 viruses were conducted, and the detection limits of CL-LFA were found to be 10 3.5 50% egg infective dose (EID 50 )/mL, 10 2.5 EID 50 /mL, and 10 4 EID 50 /mL, respectively, which is 20 to 100 times lower than that of a commercial AIV rapid test kit. Moreover, CL-LFA demonstrated high sensitivity and specificity against 37 clinical samples. The signal-amplifiable probe designed in this study is a potential diagnostic probe with ultrahigh sensitivity for applications in the field of clinical diagnosis, which requires sensitive antigen detection as evidenced by enhanced signaling capacity and sensitivity of the LFAs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sorbent Regeneration via Radiofrequency-Assisted Dielectric Heating for Direct Air Capture of CO 2

Direct air capture (DAC) of CO 2 is a negative emission technology that utilizes sorbents requiring a regeneration step for repeated ab(/d)sorption–desorption cycles. Here we report an unconventional approach to desorb captured CO 2 from a porous sorbent using radiofrequency (RF) irradiation for dielectric heating and targeted energy transfer, thus enabling modularity and promoting renewable energy input. Regeneration of composites of functional ionic liquid and metal–organic framework with high CO 2 capacity and enhanced transport is demonstrated under conditions relevant to DAC. RF-assisted dielectric heating at the megahertz frequency range shows effective absorption of electromagnetic energy and consequently rapid release of the captured CO 2 .

Ionic liquids↗

Mechanisms and Energetics of CO 2 Chemisorption in Choline-Based Eutectic Solvents

Understanding the influences of proton sharing and hydrogen transfer in amine and hydroxyl functionalized eutectic solvents is important for tuning CO 2 binding as they relate to the chemisorption capacity and energetics of solvent regeneration in carbon capture. In this study, we examine how the CO 2 binding mechanism and energetics vary in eutectic solvents composed of choline-based hydrogen-bond acceptors (HBAs) with amine and hydroxyl moieties and ethylene glycol (EG), propylene glycol (PG), 1,2-butanediol (BD), and monoethanolamine (MEA)-type hydrogen-bond donors (HBDs), through absorption–desorption experiments and spectral analysis, supported with density functional theory (DFT) calculations. While the HBD-CO 2 complex is the major and the thermodynamically more favored product of absorption in all of the examined eutectic solvents, this complexation is only possible proceeding a proton transfer from HBD to the HBA in diol-based systems (EG, PG, BD). The interplay between HBA-CO 2 and HBD-CO 2 speciation is governed by the HBD concentration, basicity, and steric effects, with increased HBD-CO 2 interactions in the presence of smaller HBDs (size: BD > PG > EG). On the other hand, in MEA-based systems, CO 2 readily binds to the amine followed by a proton transfer from the amine to the HBA as confirmed by DFT calculations. In this way, the MEA-CO 2 chemisorption capacities exceeded that of the conventional amine (up to 0.93 mol of CO 2 per mol of MEA versus 0.5). Furthermore, the increase in CO 2 capacities and enhanced binding in eutectics including MEA or the more basic HBAs also resulted in regeneration temperatures of 70 to 60 °C with calculated reaction energies of −82 to −57 kJ/mol, compared to 50 °C for others with weaker binding, following CO 2 absorption at 25 °C.

absorption↗

Permanent Nanobubbles in Water: Liquefied Hollow Carbon Spheres Break the Limiting Diffusion Current of Oxygen Reduction Reaction

Porous liquids have traditionally been designed with sterically hindered solvents. Alternatively, recent efforts rely on dispersing microporous frameworks in simpler solvents like water. Here we report a unique strategy to construct macroporous water by selectively incorporating hydrophilicity on the surfaces of hydrophobic hollow carbon spheres (HCS). Specifically, we show that the stable dispersion surface ionized HCS in water while retaining the inherent porosity. The electrocatalytic conversion of small gas molecules in aqueous electrolytes is limited by the concentration and diffusion rates of gas molecules in water. In this case, macroporous water exhibited 6 times gas uptake compared to nonporous (pure) water. Furthermore, by leveraging the high gas capacity and enhanced diffusion kinetics, the limiting diffusion current of oxygen reduction reaction (ORR) in macroporous water is 2 times that in nonporous water, offering promising prospects for sustainable energy conversion technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shark nanobodies with potent SARS-CoV-2 neutralizing activity and broad sarbecovirus reactivity

Despite rapid and ongoing vaccine and therapeutic development, SARS-CoV-2 continues to evolve and evade, presenting a need for next-generation diverse therapeutic modalities. Here we show that nurse sharks immunized with SARS-CoV-2 recombinant receptor binding domain (RBD), RBD-ferritin (RFN), or spike protein ferritin nanoparticle (SpFN) immunogens elicit a set of new antigen receptor antibody (IgNAR) molecules that target two non-overlapping conserved epitopes on the spike RBD. Representative shark antibody variable NAR-Fc chimeras (ShAbs) targeting either of the two epitopes mediate cell-effector functions, with high affinity to all SARS-CoV-2 viral variants of concern, including the divergent Omicron strains. The ShAbs potently cross-neutralize SARS-CoV-2 WA-1, Alpha, Beta, Delta, Omicron BA.1 and BA.5, and SARS-CoV-1 pseudoviruses, and confer protection against SARS-CoV-2 challenge in the K18-hACE2 transgenic mouse model. Structural definition of the RBD-ShAb01-ShAb02 complex enabled design and production of multi-specific nanobodies with enhanced neutralization capacity, and picomolar affinity to divergent sarbecovirus clade 1a, 1b and 2 RBD molecules. These shark nanobodies represent potent immunotherapeutics both for current use, and future sarbecovirus pandemic preparation.

60 APPLIED LIFE SCIENCES↗

Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions

Machine learning has revolutionized drug discovery by enabling the exploration of vast, uncharted chemical spaces essential for discovering novel patentable drugs. Despite the critical role of human G protein-coupled receptors in FDA-approved drugs, exhaustive in-distribution drug-target interaction testing across all pairs of human G protein-coupled receptors and known drugs is rare due to significant economic and technical challenges. This often leaves off-target effects unexplored, which poses a considerable risk to drug safety. In contrast to the traditional focus on out-of-distribution exploration (drug discovery), we introduce a neighborhood-to-prediction model termed Chemical Space Neural Networks that leverages network homophily and training-free graph neural networks with labels as features. We show that Chemical Space Neural Networks’ ability to make accurate predictions strongly correlates with network homophily. Thus, labels as features strongly increase a machine learning model’s capacity to enhance in-distribution prediction accuracy, which we show by integrating labeled data during inference. We validate these advancements in a high-throughput yeast biosensing system (3773 drug-target interactions, 539 compounds, 7 human G protein-coupled receptors) to discover novel drug-target interactions for FDA-approved drugs and to expand the general understanding of how to build reliable predictors to guide experimental verification.

Hansson, Frederik G↗

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↗

Uncovering Hidden Entanglement in Twin Beams

Proper characterization of quantum correlations in multimode optical quantum states is critical for applications in quantum information science. However, standard entanglement measurements can lead to incomplete state reconstruction and characterization. Here, we implement a resonator-based detection system that reveals entanglement between sideband modes of twin beams, achieving full tomography and retrieving often ignored quantum correlations. Unlike standard spectral measurements such as homodyne detection, resonator detection can independently address the sidebands of each beam, thereby accessing these hidden correlations. Additionally, we show how phase shifts between the carrier and the sideband modes of the involved fields redistribute information and modify the observation of entanglement for different witnesses. The ability of the resonant detection to independently address sideband modes of entangled states can contribute to enhancing the capacity for secure communication and quantum networking protocols.

Rincon Celis, Raul [University of Sao Paulo, Brazi↗