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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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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A “Graft to” Electrospun Zwitterionic Bilayer Membrane for the Separation of Hydraulic Fracturing-Produced Water via Membrane Distillation

Simultaneous fouling and pore wetting of the membrane during membrane distillation (MD) is a major concern. In this work, an electrospun bilayer membrane for enhancing fouling and wetting resistance has been developed for treating hydraulic fracture-produced water (PW) by MD. These PWs can contain over 200,000 ppm total dissolved solids, organic compounds and surfactants. The membrane consists of an omniphobic surface that faces the permeate stream and a hydrophilic surface that faces the feed stream. The omniphobic surface was decorated by growing nanoparticles, followed by silanization to lower the surface energy. An epoxied zwitterionic polymer was grafted onto the membrane surface that faces the feed stream to form a tight antifouling hydration layer. The membrane was challenged with an aqueous NaCl solution containing sodium dodecyl sulfate (SDS), an ampholyte and crude oil. In the presence of SDS and crude oil, the membrane was stable and displayed salt rejection (>99.9%). Further, the decrease was much less than the base polyvinylidene difluoride (PVDF) electrospun membrane. The membranes were also challenged with actual PW. Our results highlight the importance of tuning the properties of the membrane surface that faces the feed and permeate streams in order to maximize membrane stability, flux and salt rejection.

omniphobic↗
DOE OSTI2023

Comparative Energetics of Various Membrane Distillation Configurations and Guidelines for Design and Operation

This paper presents a comparative performance study of single-stage desalination processes with major configurations of membrane distillation (MD) modules. MD modules covered in this study are (a) direct contact MD (DCMD), (b) vacuum MD (VMD), (c) sweeping gas MD (SGMD), and (d) air gap MD (AGMD). MD-based desalination processes are simulated with rigorous theoretical MD models supported by molecular thermodynamic property models for the accurate calculation of performance metrics. The performance metrics considered in MD systems are permeate flux and energy efficiency, i.e., gained output ratio (GOR). A general criterion is established to determine the critical length of these four MDs (at fixed width) for the feasible operation of desalination in a wide range of feed salinities. The length of DCMD and VMD is restricted by the feed salinity and permeate flux, respectively, while relatively large AGMD and SGMD are allowed. The sensitivity of GOR flux with respect to permeate conditions is investigated for different MD configurations. AGMD outperforms other configurations in terms of energy efficiency, while VMD reveals the highest permeate production. With larger MD modules, utilization of thermal energy supplied by the hot feed for evaporation is in the order of VMD > AGMD > SGMD > DCMD. Simulation results highlight that energy efficiency of the overall desalination process relies on the efficient recovery of spent for evaporation, suggesting potential improvement in energy efficiency for VMD-based desalination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Low Temperature Geothermal Resource Assessment for Membrane Distillation Desalination in the United States: Preprint

Substantial drought and declines in potable groundwater in the United States over the last decade has increased the demand for fresh water. Desalination of saline water such as brackish surface or groundwater, seawater, brines co-produced from oil and gas operations, industrial wastewater, blow-down water from power plant cooling towers, and agriculture drainage water can reduce the volume of water that requires disposal while providing a source of high-quality fresh water for industrial or commercial use. Membrane distillation (MD) is a developing technology that uses low-temperature thermal energy for desalination. Geothermal heat can be an ideal thermal-energy source for MD desalination technology, with a target range of $1/m3 to $2/m3 for desalinated water depending on the cost of heat. Three different cases were analyzed to estimate levelized cost of heat (LCOH) for integration of MD desalination technology with low-grade geothermal heat: (1) residual heat from injection brine at a geothermal power plant, (2) heat from existing underutilized low-temperature wells, and (3) drilling new wells for low-temperature resources. The Central and Western United States have important low-temperature (<90 degrees C) geothermal resource potential with wide geographic distribution, but these resources are highly underutilized because they are inefficient for power production. According to the USGS, there are 1,075 identified low temperature hydrothermal systems, 55 low temperature sedimentary systems and 248 identified medium to high temperature geothermal systems in the United States. The estimated total beneficial heat potential from identified low temperature hydrothermal geothermal systems and residual beneficial heat from medium to high temperature systems is estimated as 36,300 MWth, which could theoretically produce 1.4 to 7 million m3/day of potable water, depending on desalination efficiency.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Low Temperature Geothermal Resource Assessment for Membrane Distillation Desalination in the United States

Substantial drought and declines in potable groundwater in the United States over the last decade has increased the demand for fresh water. Desalination of saline water such as brackish surface or groundwater, seawater, brines co-produced from oil and gas operations, industrial wastewater, blow-down water from power plant cooling towers, and agriculture drainage water can reduce the volume of water that requires disposal while providing a source of high-quality fresh water for industrial or commercial use. Membrane distillation (MD) is a developing technology that uses low-temperature thermal energy for desalination. Geothermal heat can be an ideal thermal-energy source for MD desalination technology, with a target range of $1/m3 to $2/m3 for desalinated water depending on the cost of heat. Three different cases were analyzed to estimate levelized cost of heat (LCOH) for integration of MD desalination technology with low-grade geothermal heat: (1) residual heat from injection brine at a geothermal power plant, (2) heat from existing underutilized low-temperature wells, and (3) drilling new wells for low-temperature resources. The Central and Western United States have important low-temperature (<90 degrees C) geothermal resource potential with wide geographic distribution, but these resources are highly underutilized because they are inefficient for power production. According to the USGS, there are 1,075 identified low temperature hydrothermal systems, 55 low temperature sedimentary systems and 248 identified medium to high temperature geothermal systems in the United States. The estimated total beneficial heat potential from identified low temperature hydrothermal geothermal systems and residual beneficial heat from medium to high temperature systems is estimated as 36,300 MWth, which could theoretically produce 1.4 to 7 million m3/day of potable water, depending on desalination efficiency.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Development of Membrane Distillation Technology Utilizing Waste Heat for Treatment of High Salinity Wastewaters

Membrane distillation (MD) can serve as a cost effective method to treat high salinity wastewaters, especially if waste heat is utilized for its operation. The goal of this work is to study the feasibility of employing MD technology for the treatment of high salinity wastewaters which are generated as a result of natural gas production and active reservoir management for CO 2 sequestration. This study also aimed at quantifying the availability of waste heat which could be used as the primary source of thermal energy to drive the MD process. Bench scale studies were carried out with several commercially available membranes using both synthetic and actual high salinity wastewaters. The membranes tested with real wastewater samples exhibited excellent rejection of dissolved ions, including naturally occurring radioactive material (NORM). Long term bench scale experiments with real produced water from the Marcellus shale play revealed that iron oxide could precipitate on the feed side of direct contact MD (DCMD) module but had a negligible effect on the performance of the system. Based on the bench scale experiments, an ASPEN Plus simulation, which incorporated a mathematical model with fundamental heat and mass transfer equations, was developed and used to evaluate the process energy requirements. Despite low operating temperature and pressure for MD, it had a large thermal energy requirement for operation, which could make this technology expensive compared to reverse osmosis (RO) and forward osmosis (FO). However, it is important to note that RO and FO have limited applicability for high salinity shale gas wastewater. Moreover, MD could be integrated with renewable energy sources such as wind or solar energy or industrial waste heat sources to offset the thermal energy requirements and enhance the economics of wastewater treatment. Natural gas compressor stations (NG CS) have been proposed in this study as the source of waste heat based on the estimate of quantity and quality of available waste heat in the exhaust streams of gas turbine and internal combustion compressor engines. Using the actual installed capacity and location of compressor stations in the U.S., this analysis revealed that an average of 610 TJ/day of thermal energy is available at existing NG CS and that this source of waste heat is of high quality with temperatures above 645 K. A systems-level integration of MD with waste heat from NG CS revealed that approximately 56% of available waste heat at NG CS in Pennsylvania is sufficient to concentrate (from 10% to 30% salinity) all wastewater associated with shale gas extraction. Techno-economic assessment (TEA) accounting for capital as well as operating and maintenance costs with and without waste heat integration was conducted for a hypothetical 0.5 million gallons per day (MGD) DCMD plant using experimental and modeling results from this study. TEA revealed that the total cost of shale gas wastewater treatment using MD is $5.7/m 3 feed for the base case scenario in which the thermal energy requirements are met by external steam, however, the total cost can be reduced to $0.74/m 3 feed when integrated with free waste heat from NG CS. Sensitivity analysis revealed that thermal energy cost and feed TDS are the most important factors in total cost of high salinity wastewater treatment using DCMD.

03 NATURAL GAS↗
DOE OSTI2019

Way to increase the energy efficiency of the distillation unit at ethylbenzene manufacturing technology

The object of research is the installation of rectification columns for benzene, ethylbenzene, and polyalkylbenzenes. The purpose of this work is an optimization of rectification technological modes and energy efficiency increasing of distillation in the technology of ethylbenzene production by replacing of the used in reboilers vapor at 4 MPa by vapor at 2 MPa. The proposed optimization option of the rectification unit is efficient since the implementation of the proposed technical solution will be achieved using Vapor 2 with increased efficiency of the process, namely a reduction of vapor consumption. The total consumption of vapor after the upgrade will be 2.751 Gcal / hour, which is 2168 Gcal per year less than the current vapor load.

09 BIOMASS FUELS↗
DOE OSTI2019

From graphical to model-based distillation column design: A McCabe-Thiele-inspired mathematical programming approach

We propose a mixed-integer nonlinear programming (MINLP) model for simple and complex distillation column design and optimization. The model is based upon the concepts and equations underpinning the McCabe-Thiele method. Generalizing this method, we introduce material balances at various locations of the column and employ binary variables to determine the optimal number of trays and optimal feed locations. We model the vapor–liquid equilibrium using continuous piecewise linear approximating functions. The model is extended to account for multicomponent mixtures and non-constant-molar overflow. We also discuss how to estimate the minimum number of trays and the minimum reflux ratio.

42 ENGINEERING↗
DOE OSTI2023

Technoeconomic assessment of distillation heat transfer intensification using aeroelastically fluttering reeds

Dry cooling, where forced air is the heat transfer medium, is a preferable cooling method in arid locations lacking readily available process water. However, such locations often experience high ambient temperatures that limit the effectiveness of air cooling. The objective of this study is to quantify the economic and energetic benefits of heat transfer intensification via the implementation of aeroelastically fluttering reeds to the air-cooled condenser of a methanol distillation column. Condenser size and performance, regarding recovered methanol and required fan power, is evaluated across condenser operating temperatures (T cond ) from 60 to 62°C and heat transfer coefficients (U) U base –2U base for a range of inlet air temperatures based on ambient temperature data from Yuma, Arizona. Under typical design sizing, condenser capital cost was reduced by 6%–35% (1.3U base –2U base ) and nominal methanol recovery was increased from 0.26% to 0.38% (T cond = 62–60°C). At optimized condenser size, all enhanced U and T cond pairs increase methanol recovery and reduce fan power costs compared to the optimal Ubase reference. Overall, using enhanced heat transfer to maintain condenser temperature under a wider range of inlet conditions, rather than to reduce operation temperature, produces more favorable performance. Methanol price is not a determining factor in which pairs are profitable. Analysis was repeated for a global warming scenario, revealing more valuable improvements under elevated temperatures. Energy savings from condenser improvement to a methanol production system are not significant with respect to an optimized conventional system. Furthermore, unit economic and energetic incentives suggest implementation of fluttering reeds may be justified in other applications.

42 ENGINEERING↗
DOE OSTI2024

δ 2 H isotopic offsets in xylem water measurements under cryogenic vacuum distillation: Quantifying and correcting wood‐water hydrogen exchange influences

Stable isotopes δ 18 O and δ 2 H are used to infer vegetation water sources. In some studies, significant xylem water δ 2 H offsets from potential source waters have been observed. The offsets appear to be more prevalent with cryogenic vacuum distillation (CVD) of plant water. Hypothesized mechanisms for these offsets include changes during plant water uptake and transport, and methodological problems. We propose that a large portion of the offsets are due to hydrogen isotope exchange between xylem water and non-crystalline hydroxyl groups of wood cellulose and hemicellulose during CVD. We present a method for estimating the hypothesized isotopic exchange between wood tissues and water, which is the result of Rayleigh and equilibrium fractionation. To estimate the exchange, we use published wood properties for North American tree species and isotope chemical relationships as a function of moisture content, CVD temperature and water extraction efficiency. A simple model of exchange between xylem water and hydroxyl groups captures the range of observations in studies in which CVD and non-CVD methods were compared. To evaluate the model, we compared observed δ 2 H offsets (sw-excess) values from two field datasets (90°C, n = 364, and 170°C, n = 43) to δ 2 H offsets estimated with our chemical model. We found good agreement between observed and estimated δ 2 H offsets for samples extracted at 90°C (r 2 = 0.69) but not for samples extracted at 170°C (r 2 = 0.20). The offset may be eliminated by increasing the extraction temperature to 229°C or by adding a standard sufficient to raise the moisture content to >150%. A correction can also be approximated by applying a theoretical calculation based on the extraction temperature, moisture content and water extraction efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Holographic entanglement distillation from the surface state correspondence

We study correlations between geometric subfactors living on the Ryu-Takayanagi surface that bounds the entanglement wedge. Using the surface-state correspondence and the bit threads program, we are able to calculate mutual information and conditional mutual information between subfactors. This enables us to count the shared Bell pairs between subfactors, and we propose an entanglement distillation procedure over these subsystems via a SWAP gate protocol. We comment on extending to multipartite entanglement.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Beyond toy models: distilling tensor networks in full AdS/CFT

We present a general procedure for constructing tensor networks that accurately reproduce holographic states in conformal field theories (CFTs). Given a state in a large-N CFT with a static, semiclassical gravitational dual, we build a tensor network by an iterative series of approximations that eliminate redundant degrees of freedom and minimize the bond dimensions of the resulting network. We argue that the bond dimensions of the tensor network will match the areas of the corresponding bulk surfaces. For “tree” tensor networks (i.e., those that are constructed by discretizing spacetime with nonintersecting Ryu-Takayanagi surfaces), our arguments can be made rigorous using a version of one-shot entanglement distillation in the CFT. Using the known quantum error correcting properties of AdS/CFT, we show that bulk legs can be added to the tensor networks to create holographic quantum error correcting codes. These codes behave similarly to previous holographic tensor network toy models, but describe actual bulk excitations in continuum AdS/CFT. By assuming some natural generalizations of the “holographic entanglement of purification” conjecture, we are able to construct tensor networks for more general bulk discretizations, leading to finer-grained networks that partition the information content of a Ryu-Takayanagi surface into tensor-factorized subregions. While the granularity of such a tensor network must be set larger than the string/Planck scales, we expect that it can be chosen to lie well below the AdS scale. However, we also prove a no-go theorem which shows that the bulk-to-boundary maps cannot all be isometries in a tensor network with intersecting Ryu-Takayanagi surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Life-cycle analysis of soybean meal, distiller-dried grains with solubles, and synthetic amino acid-based animal feeds for swine and poultry production

Swine and poultry meat production are two important sectors in the U.S. economy. They play an important role in environmental sustainability because they contribute to the greenhouse gas (GHG) emissions as the result of agricultural and production activities. To improve the sustain ability of swine and poultry meat production, it is important to understand the environmental effects and identify the key drivers of the production activities. In this work, we presented an environmental assessment of the production of swine (i.e., pork) and poultry (i.e., broiler chicken). We conducted a life-cycle analysis of formulating animal feeds using soybean meal, corn, distiller-dried grains with solubles (DDGS), and synthetic amino acids as candidate ingredients to produce swine and poultry. We evaluated GHG emissions, fossil fuel consumption, and water consumption from formulating and utilizing a variety of animal feeds based on these ingredients for swine and poultry production, using an expanded version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET (R)) model. With pork and broiler chicken as the finished products, the functional unit was defined as one kg of live-weight animal at the farm gate. Feed production was the major contributor to the life-cycle GHG emissions (88 % and 91 % of the total GHG emissions for swine and poultry production, respectively) and fossil fuel consumption (79 % and 84 % of the total fossil fuel consumption for swine and poultry process, respectively). Among the four ingredient types, amino acids had the biggest GHG emission footprint; however, DDGS had the largest effect on increasing GHG emissions of swine and poultry production.

animal feed production↗
DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cost of Deconstruction Depots for Diversified, Waste-Based Lignocellulosic Sugars Using Distillable Solvents

Transitioning to a bioeconomy that makes use of low-emission and waste feedstocks requires greater flexibility to accommodate seasonal variations and mitigate long-term storage challenges, such as material loss and fire risk. To achieve this goal, biomass deconstruction technologies must efficiently handle diverse feedstocks. Here, we assess the cost of using butylaminea distillable solventto deconstruct 22 different biomass feedstocks: 7 herbaceous, 9 woody, 4 food processing residues, and 2 blends. Lignocellulosic sugar production costs, based on current empirical data, range from $1.3 to 6.1/kg, suggesting that substantial improvements are required to compete with conventional sugars. The high solvent loading (850 g/kg of whole slurry) is a process bottleneck. Lowering the solvent loading to 59 g/kg of whole slurry, demonstrated in an L-scale reactor using poplar biomass, reduces the minimum sugar selling price by 33%. Solvent loading and recovery, solid loading, sugar yield, enzyme use, and delivered biomass cost all play key roles in reaching sugar production costs of $0.45-0.79/kg. Strategic feedstock blending to maximize carbohydrate content, process optimization to improve conversion efficiency, and the selection of low-cost feedstocks are important to advancing feedstock-flexible biorefineries.

TEA↗
DOE OSTI2014

Omniphobic Membrane for Robust Membrane Distillation

In this work, we fabricate an omniphobic microporous membrane for membrane distillation (MD) by modifying a hydrophilic glass fiber membrane with silica nanoparticles followed by surface fluorination and polymer coating. The modified glass fiber membrane exhibits an anti-wetting property not only against water but also against low surface tension organic solvents that easily wet a hydrophobic polytetrafluoroethylene (PTFE) membrane that is commonly used in MD applications. By comparing the performance of the PTFE and omniphobic membranes in direct contact MD experiments in the presence of a surfactant (sodium dodecyl sulfate, SDS), we show that SDS wets the hydrophobic PTFE membrane but not the omniphobic membrane. Our results suggest that omniphobic membranes are critical for MD applications with feed waters containing surface active species, such as oil and gas produced water, to prevent membrane pore wetting.

Lin, SH↗
DOE OSTI2021

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Abstract Accurately identifying the local structural heterogeneity of complex, disordered amorphous materials such as amorphous silicon is crucial for accelerating technology development. However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored. We resolve phonon vibrational modes of a-Si at a lateral resolution of <60 nm by tip-enhanced Raman spectroscopy. To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm. It allows for quantifying average Si-Si distortion angle and the strain free energy at nanoscale without a human-specified physical threshold. The multiresolution feature of the multiresolution manifold learning allows for distilling local defects of ultra-low abundance (< 0.3%), presenting a new Raman mode at finer resolution grids. This work promises a general paradigm of resolving nanoscale structural heterogeneity and updating domain knowledge for highly disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Abstract Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

59 BASIC BIOLOGICAL SCIENCES↗