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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.
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Cations and anions have different affinities for the air-water interface. The intrinsic orientation of surface molecules suggests such an asymmetry, but the bias is dominated by solvent response that is spatially local and significantly nonlinear.
The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.
The formation of exposed active sites that have high activity and stability for oxygen evolution reaction (OER) catalysis is a significant opportunity for improving water electrolysers. Low-index facets surface Ru can achieve both high activity and stability for OER. Here, we present a new catalyst design where low-index faceted Ru branches are grown off the corners of Pt nanocubes, forming open Ru branched nanoparticles. This open branched structure, exposing low-index facets on its length-tunable branch, enables a high electrochemically active surface area (ECSA), achieving high activity and stability for OER. This design strategy and synthetic control provide a principle for achieving high-performance OER nanocatalysts.
Little is known of acetogens in contemporary serpentinizing systems, despite widely supported theories that serpentinite-hosted environments supported the first life on Earth via acetogenesis. To address this knowledge gap, genome-resolved metagenomics was applied to subsurface fracture water communities from an area of active serpentinization in the Samail Ophiolite, Sultanate of Oman. Two deeply branching putative bacterial acetogen types were identified in the communities belonging to the Acetothermia (hereafter, types I and II) that exhibited distinct distributions among waters with lower and higher water–rock reaction (i.e., serpentinization influence), respectively. Metabolic reconstructions revealed contrasting core metabolic pathways of type I and II Acetothermia, including in acetogenic pathway components (e.g., bacterial- vs. archaeal-like carbon monoxide dehydrogenases [CODH], respectively), hydrogen use to drive acetogenesis, and chemiosmotic potential generation via respiratory (type I) or canonical acetogen ferredoxin-based complexes (type II). Notably, type II Acetothermia metabolic pathways allow for use of serpentinization-derived substrates and implicate them as key primary producers in contemporary hyperalkaline serpentinite environments. Phylogenomic analyses indicate that 1) archaeal-like CODH of the type II genomes and those of other serpentinite-associated Bacteria derive from a deeply rooted horizontal transfer or origin among archaeal methanogens and 2) Acetothermia are among the earliest evolving bacterial lineages. The discovery of dominant and early-branching acetogens in subsurface waters of the largest near-surface serpentinite formation provides insight into the physiological traits that likely facilitated rock-supported life to flourish on a primitive Earth and possibly on other rocky planets undergoing serpentinization.
In aluminum-clad spent nuclear fuels, an (oxy)hydroxide layer on the surface of the cladding hosts chemisorbed water formed during reactor and post-discharge exposure to water. Any residual water is susceptible to generating hydrogen via radiolysis, which can be a risk associated with dry fuel storage. Engineering-scale forced helium dehydration (FHD) and vacuum drying tests were conducted on mock-up fuel assemblies that included corroded aluminum surrogate plates to assess the removal of bulk and chemisorbed water. Thermogravimetric analysis was performed on samples of the surrogate plates, both undried control samples used to determine onset temperatures associated with a phase change occurring in the oxide layer and samples from drying tests used to determine the effectiveness of each drying method. Both vacuum drying and FHD processes were capable of removing bulk water. However, FHD was determined to provide additional drying capabilities, including partial removal of chemisorbed water from bayerite due to the higher temperatures during drying. In conclusion, the temperature threshold for partial dehydroxylation of the oxide layer was determined to be around 220°C, meaning any drying methods attempting to remove chemisorbed water must exceed 220°C.
The surface roughness of a thin film at a liquid interface exhibits contributions of thermally excited fluctuations. This thermal roughness depends on temperature (𝑇), surface tension (𝛾), and elastic material properties, specifically the bending modulus (𝜅) of the film. A nonzero 𝜅 suppresses the thermal roughness at small length scales compared to an interface with zero 𝜅, as expressed by the power spectral density of the thermal roughness. The description of the x-ray scattering of the standard capillary wave model (CWM), which is valid for zero 𝜅, is extended to include the effect of 𝜅. The extended CWM (eCWM) provides a single analytical form for both the specular x-ray reflectivity (XRR) and the diffuse scattering around the specular reflection, and recovers the expression of the CWM at its zero 𝜅 limit. This theoretical approach enables the use of single-shot grazing incidence x-ray off-specular scattering (GIXOS) measurements for characterizing the structure of thin films on a liquid surface. The eCWM analysis approach decouples the thermal roughness factor from the surface scattering signal, providing direct access to the intrinsic surface-normal structure of the film and its bending modulus. Moreover, the eCWM facilitates the calculation of reflectivity at any desired resolution (pseudo-XRR approach). The transformation into pseudo-XRR provides the benefit of using widely available XRR software to perform GIXOS analysis. The extended range of the vertical scattering vector (𝑄 𝑧 ) available with the GIXOS pseudo-XRR approach allows for a higher spatial resolution than with conventional XRR. Experimental results are presented for various lipid systems, showing strong agreement between conventional specular XRR and pseudo-XRR methods. This agreement validates the proposed approach and highlights its utility for analyzing soft, thin films.
Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasi-static solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.
When two is better than four Batteries based on the reaction of zinc and oxygen have been used for more than a century, but these have been primary (that is, nonrechargeable) cells. These batteries use an alkaline electrolyte and require a four-electron reduction of oxygen to water, which is a slow process. Sun et al. show that with the right choice of nonalkaline electrolyte, the battery can operate using a two-electron zinc-oxygen/zinc peroxide chemistry that is far more reversible. By making the electrolyte hydrophobic, water is excluded from the near surface of the cathode, thus preventing the four-electron reduction. These batteries also show higher energy density and better cycling stability. Science , this issue p. 46
The design of soft matter in which internal fuels or an external energy input can generate locomotion and shape transformations observed in living organisms is a key challenge. Such materials could assist in productive functions that may range from robotics to smart management of chemical reactions and communication with cells. In this context, hydrated matter that can function in aqueous media would be of great interest. Here, we report the design of hydrogels containing a scaffold of high–aspect ratio ferromagnetic nanowires with nematic order dispersed in a polymer network that change shape in response to light and experience torques in rotating magnetic fields. The synergistic response enables fast walking motion of macroscopic objects in water on either flat or inclined surfaces and also guides delivery of cargo through rolling motion and light-driven shape changes. The theoretical description of the response to the external energy input allowed us to program specific trajectories of hydrogel objects that were verified experimentally.
This software consists of python-based Jupyter Notebooks for processing transmission x-ray scattering images collected at beamline 7.3.3 at the Advanced Light Source. The measurements considered in these analyses are collected during membrane fouling experiments, where contaminants in the water deposit on/attach to the membrane surface. This software is used to elucidate the mechanisms of membrane fouling that occur during these operando membrane fouling experiments, but the analyses provided in these scripts can be extended to other scientific cases.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Tw4 Twitchell East End Wetland. This is the FLUXNET version of the carbon flux data for the site US-Tw4 Twitchell East End Wetland produced by applying the standard ONEFlux (1F) software. Site Description - The Twitchell East End Wetland is a newly constructed restored wetland on Twitchell Island, CA. This site and the surrounding region are part of the San Joaquin - Sacramento River Delta drained beginning in the 1850's and subsequently used for agriculture. The site was previously a corn field. The wetland was designed to have a mix of vegetated and open water channels and ponds (due to surface elevation differences). Flooding of the wetland was done gradually beginning in January, 2014. Berms wind throughout the wetland to allow vehicle access. Tule and Cattail plant material from a nearby wetland were spread along the berms immediately prior to flooding to facilitate plant establishment and stabilization of the berms from wind/water erosion. The tower was installed on November 25, 2013.
Heat duty and heat loss were measured at the pilot plant at UT Austin. Heat loss was measured with energy balances using water. Heat loss was studied using surface temperature measurements over 68 different locations at the pilot plant. Surface temperature measurements indicated that bare metal surfaces were the primary source of heat loss from the pilot plant. Heat loss from bare metal surfaces was at least 50% controlled by natural convection and in many cases was as high as 75% natural convection controlled. Measured heat loss at the pilot plant was 20100 BTU/hr and overall heat loss did not show any dependence on the heat rate of the plant. Compared to PZAS™ at the National Carbon Capture Center, heat loss relative to heat rate was higher at 38%. The relative heat loss at the pilot plants was found to decrease by 20% per MW of added capacity. Measured net heat duty was found to be dependent on measured lean loading and cold rich bypass flow rate. Measured net heat duty was between 2.2 and 2.4 GJ/tonne at an optimum lean loading of 0.2–0.21 mol/mol. Data reconciliation by Aspen Plus® Data Fit™ underpredicted CO2 flow rate by 20% due to an overprediction of lean loading by 19%, indicating a necessary change in thermodynamic parameters in the model. This resulted in an over prediction of heat duty by 33% on average.
The lifting condensation level height (LCL, m) is determined from continuous surface-air observations of relative humidity and temperature as the altitude where the surface-air moisture equals saturation following a dry-adiabatic ascent. Values are computed from surface meteorological observations for 16 facilities belonging to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) atmospheric observatory and for 133 Oklahoma Mesonet (OKM) stations. The LCL Height Value-Added Product (VAP) was developed for use by the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project (Gustafson et al. 2016, 2017, 2018, 2020).
The electrochemical reduction of carbon dioxide (CO2) into valuable fuels such as C1 (syngas, methane) and C2 (ethylene, ethanol) products is a key strategy for achieving a carbon-neutral economy. Computational studies of C-C coupling, a critical step in CO2 reduction, are essential for designing more efficient catalysts. However, simulating these processes under realistic electrochemical conditions, including temperature and solvent effects, is computationally demanding. In this work, we develop a machine learning-based atomistic potential to study CO2 reduction on Cu(100) surfaces, accounting for temperature and explicit water solvent effects. We compute thermodynamic free energies of the possible C-C coupling pathways, CO*+CO*→OCCO*, CO*+CHO*→OCCHO*, CO*+COH*→OCCOH*, CHO*+COH*→OHCCOH*, COH*-COH*→HOCCOH*, and CHO*-CHO*→OHCCHO*. Our results quantify the thermodynamic tendencies of these reactions and reveal that, in addition to the well-established CO* + CO* → OCCO* pathway, CHO* is a critical intermediate in the formation of C2 products on Cu(100). Furthermore, we demonstrate that the machine learning approach offers a cost-efficient framework for studying CO2 reduction on diverse catalysts under realistic electrochemical conditions.
Abstract. Continuous water vapor and temperature profiles are critically needed for improved understanding of the lower atmosphere and potential advances in weather forecasting skill. Ground-based, national-scale profiling networks are part of a suite of instruments to provide such observations; however, the technological method must be cost-effective and quantitative. We have been developing an active remote sensing technology based on a diode-laser-based lidar technology to address this observational need. Narrowband, high-spectral-fidelity diode lasers enable accurate and calibration-free measurements requiring a minimal set of assumptions based on direct absorption (Beer–Lambert law) and a ratio of two signals. These well-proven quantitative methods are known as differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL). This diode-laser-based architecture, characterized by less powerful laser transmitters than those historically used for atmospheric studies, can be made eye-safe and robust. Nevertheless, it also requires solar background suppression techniques such as narrow-field-of-view receivers with an ultra-narrow bandpass to observe individual photons backscattered from the atmosphere. We discuss this diode-laser-based lidar architecture's latest generation and analyze how it addresses a national-scale profiling network's need to provide continuous thermodynamic observations. The work presented focuses on general architecture changes that pertain to both the water vapor and the temperature profiling capabilities of the MicroPulse DIAL (MPD). However, the specific subcomponent testing and instrument validation presented are for the water vapor measurements only. A fiber-coupled seed laser transmitter optimization is performed and shown to meet all of the requirements for the DIAL technique. Further improvements – such as a fiber-coupled near-range receiver, the ability to perform quality control via automatic receiver scanning, advanced multi-channel scalar capabilities, and advanced processing techniques – are discussed. These new developments increase narrowband DIAL technology readiness and are shown to allow higher-quality water vapor measurements closer to the surface via preliminary intercomparisons within the MPD network itself and with radiosondes.
The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO 2 -emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.
Frost is a common problem in heating, ventilation, and air conditioning (HVAC) systems that can degrade their efficiencies, leading to excessive electricity consumption. Appropriate defrosting is therefore essential for heat pumps and refrigeration systems. However, these systems typically run the defrost cycle based on a predetermined time interval, a method that does not accurately identify the amount of frost and thus consume excessive electricity. To substantially improve defrosting initiation and termination, this paper describes development of a smart sensor based on a capacitive sensing technique that can quantify frost accumulation and difference between frost, ice, and water. The reported sensor adopts interdigitated comb electrodes and can be updated to a potential multifunctional sensor array for the enhancing identification of frost, ice, and water with the integrated measurement of surface temperature, frost capacitance, and resistance. The proposed frost sensor is potentially expected to have widespread applications in HVAC systems, including heat pumps, refrigerators, and commercial refrigeration systems.
Methods for fabricating thin, high-aspect-ratio Ge nanostructures from high-quality, single-crystalline Ge substrates are provided. Also provided are grating structures made using the methods. The methods utilize a thin layer of graphene between a surface of a Ge substrate, and an overlying resist layer. The graphene passivates the surface, preventing the formation of water-soluble native Ge oxides that can result in the lift-off of the resist during the development of the resist.