Search NASA⌕ Search

SEARCH · Search NASA

Results for “separability approach”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Empowering Machine Learning Forecasting of Labquake Using Event‐Based Features and Clustering Characteristics

Abstract Following recent advances of machine learning (ML), we present a novel approach to extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to empower ML‐based forecasting. The AE data were recorded during laboratory stick‐slip experiments on granite samples cut by rough faults. Based on the features computed for a past time window, a random forest (RF) classifier is used to forecast the occurrence of a large magnitude event ( M AE > 3.5) in the next time window. Event‐based features allow us to associate informative time‐space characteristics to each feature and nearest‐neighbor clustering analysis enables us to separate background and clustered seismicity and train individual models. The results show that the separation of AEs enhances the forecasting accuracy from 73.2% for the entire catalog up to 82.1% and 89.0% if background and clustered events are used separately. The presented new approach may be upscaled for applications to forecast tectonic earthquakes.

Karimpouli, Sadegh↗
DOE OSTI2025

Selective Recovery of Critical Minerals from Simulated Electronic Wastes Via Reaction‐Diffusion Coupling

Abstract Atom‐ and energy‐efficient chemical separations are urgently needed to meet the surging demand for critical materials that has strained supply chains and threatened environmental damage. In this study, we used reaction‐diffusion coupling to separate iron, neodymium, and dysprosium ions from model feedstocks of permanent magnets, which are typically found in electronic wastes. Feedstock solutions were placed in contact with a hydrogel loaded with potassium hydroxide and/or dibutyl phosphate, resulting in complex precipitation patterns as the various metal ions diffused into the reaction medium. Specifically, we observed the precipitation of up to 40 mM of iron from the feedstock, followed by the enrichment of 73 % dysprosium, and the extraction of >95 % neodymium product at a further distance from the solution‐gel interface. We designed a series of experiments and simulations to determine the relevant ion diffusivities, D Nd =5.4×10 −10 and D Dy =5.1×10 −10 m 2 /s, and precipitation rates, k Nd =1.0×10 −5 and k Dy =5.0×10 −3 m 9 mol −3 s −1 , which enabled a numerical model to be established for predicting the distribution of products in the reaction medium. Our proof‐of‐concept study validates reaction‐diffusion coupling as an effective and versatile approach for critical materials separations, without relying on ligands, membranes, resins, or other specialty chemicals.

Wang, Qingpu [Physical and Computational Sciences ↗
DOE OSTI2026

Lanthanide Separations through Helicate Self-Assembly

Skyrocketing demand for rare-earth elements makes their isolation and reuse from electronic waste an increasingly attractive alternative to mining. Typically, the capture of individual lanthanides from mixtures requires the iterative design of complex, macrocyclic ligands, a sometimes successful but often laborious process. Here we show that the self-assembly of rare-earth ions with a ditopic ligand, L d , results in the selective incorporation of smaller lanthanides and gives rise to impressive separation factors. Comparison to a monotopic ligand, L m , shows that the separation performance of ditopic L d critically depends on the presence of two adjacent binding sites. Isothermal titration calorimetry (ITC) experiments show that the selectivity of L d for smaller ions is thermodynamically driven and provide evidence of positive cooperativity among the two binding sites of L d . The simplicity of the separation procedure reported here, requiring only 1 min of sonication in methanol, shows the potential applicability of this approach to real-world separations. Here, by achieving efficient rare-earth separations in small, synthetically facile helicates, this work shows the promise of self-assembly as a mechanism to drive metal separations.

Alcohols↗
DOE OSTI2023

Electrically enhanced thermochemical cycles for hydrogen generation

In two-step metal-oxide (MO) solar thermochemical cycles, high temperature solar thermal energy is first converted to chemical energy in the form of a reduced MO. The reduced MO is then reoxidized in a second step with steam (or carbon dioxide) to produce hydrogen (or carbon monoxide) at a lower temperature. Solar thermochemical cycles of this type circumvent heat-to-electrical conversion required for electrochemical water splitting and promise high efficiencies. However, significant challenges remain to implementation. Ultra-high temperatures and efficiency-sapping low per-cycle conversion stand out as particularly difficult hurdles. Hybrid approaches utilizing both thermal and electrical energy provide some of the advantages of each, and can facilitate lower temperature operation and offer better per-pass utilization than thermochemical alone. However, early concepts for implementing the thermo-electrochemical approach introduced substantial new challenges including difficult separations, corrosive environments, and energy losses from large temperature swings and phase changes. We are currently investigating two different options for implementation. In the first, a MO that reduces at lower temperature is selected. As the reduced MO lacks the full thermodynamic driving force to effectively split water, the reaction is driven forward by an electrically-assisted proton-conducting membrane that separates and recovers hydrogen as it is produced. This approach produces a pure hydrogen stream, is mechanically simple, and has unique thermodynamic advantages. The second option seeks to more directly couple the electrical boost to the solid MO to drive either the reduction or oxidation step, or both, through the utilization of layered MO materials and advanced reactors. This approach could be applied to both water and carbon dioxide splitting. The results of process modeling and optimization will be presented, and progress towards demonstrating the concepts at the laboratory scale will be discussed.

08 HYDROGEN↗
DOE OSTI2023

Rational Design and Reticulation of Infinite qbe Rod Secondary Building Units into Metal–Organic Frameworks through a Global Desymmetrization Approach for Inverse C 3 H 8 /C 3 H 6 Separation

Abstract The development of reticular chemistry has enabled the construction of a large array of metal–organic frameworks (MOFs) with diverse net topologies and functions. However, dominating this class of materials are those built from discrete/finite secondary building units (SBUs), yet the designed synthesis of frameworks involving infinite rod‐shaped SBUs remain underdeveloped. Here, by virtue of a global linker desymmetrization approach, we successfully targeted a novel Cu‐MOF (Cu‐ASY) incorporating infinite Cu‐carboxylate rod SBUs with its structure determined by micro electron diffraction (MicroED) crystallography. Interestingly, the rod SBU can be simplified as a unique cylindric sphere packingqbetubule made of [4 3 .6 2 ] tiles, which further connect the tritopic linkers to give a newly discovered 3,5‐connectedgfcnet. Cu‐ASY is a permanent ultramicroporous material featuring 1D channels with highly inert surfaces and shows a preferential adsorption of propane (C 3 H 8 ) over propene (C 3 H 6 ). The efficiency of C 3 H 8 selective Cu‐ASY is validated by multicycle breakthrough experiments, giving C 3 H 6 productivity of 2.2 L/kg. Density functional theory (DFT) calculations reveal that C 3 H 8 molecules form multiple C−H⋅⋅⋅π and atypical C−H⋅⋅⋅ H−C van der Waals interactions with the inner nonpolar surfaces. This work therefore highlights the linker desymmetrization as an encouraging and intriguing strategy for achieving unique MOF structures and properties.

Chemistry↗
DOE OSTI2021

Reducing Antisolvent Use in the STRAP Process by Enabling a Temperature–Controlled Polymer Dissolution and Precipitation for the Recycling of Multilayer Plastic Films

The recently reported processing strategy called solvent-targeted recovery and precipitation (STRAP) enables deconstruction of multilayer plastic packaging films into their constituent resins by selective dissolution. It uses a series of solvent washes that are guided by thermodynamic calculations of polymer solubility. In this work, the use of antisolvents in the STRAP process was reduced and solvent mixtures were considered to enable the temperature-controlled dissolution and precipitation of the target polymers in multilayer films. This was considered as a means to further improve the STRAP process and its estimated costs. Two STRAP approaches were compared based on different polymer precipitation techniques: precipitation by the addition of an antisolvent (STRAP-A) and precipitation by decreasing the solvent temperature (STRAP-B). Both approaches were able to separate the constituent polymers in a post-industrial film composed primarily of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET) with near 100 % material efficiency. Technoeconomic analysis indicates that the minimum selling price (MSP) of the recycled resins with STRAP-B is 21.0 % lower than that achieved with STRAP-A. This provides evidence that thermally driven polymer precipitation is an option to reduce the use of antisolvents, making the STRAP process more economically and environmentally attractive. A third process, STRAP-C, was demonstrated with another post-industrial multilayer film of a different composition. Here, the results demonstrate that this process can also recover polymers at similar costs to those of virgin resins, indicating that the STRAP technology is flexible and can remain economically competitive as the plastic feed complexity is increased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Chemical looping air separation with Sr 0.8 Ca0.2Fe 0.9 Co 0.1 O 3-δ perovskite sorbent: Packed bed modeling, verification, and optimization

Chemical looping air separation (CLAS) represents a promising approach for efficient O 2 production from the air. This present study aims at optimizing the absorber/desorber operations and the separation process with extensive experimental validation. Specifically, a one-dimensional packed bed model was developed to investigate the CLAS operation with a Sr 0.8 Ca 0.2 Fe 0.9 Co 0.1 O 3-δ perovskite sorbent. The redox thermodynamics of perovskite sorbent was measured by TGA and then incorporated into a linear driving force model to describe the O 2 absorption and desorption rates. Both 4-step and 5-step air separation cycle configurations, with various cyclic structures, were performed in a subpilot-scale packed bed. The model predicted O2 purity and productivity were consistent with experimental results, supporting its accuracy and applicability. Parametric analysis and multi-objective optimization were further carried out to assess the performance of CLAS. Both O 2 purity and recovery increased monotonically with the cycle time, airflow rate, steam flow rate, and absorption pressure. Meanwhile, optimal O 2 productivity and power consumption can only be achieved by specific combinations of these parameters. The optimized results showed that CLAS can be highly competitive when compared to conventional pressure swing adsorption (PSA) or cryogenic distillation. The 5-step cycle configuration achieved a minimum power consumption of 118 kW·h for producing 1 ton O 2 with ≥ 95% purity. The maximum O 2 productivity reached 0.0932 g O2 /(g sorbent ·h) with 390 kW·h/ton O 2 of energy consumption (95% pure). The optimization results also indicate that CLAS can potentially be more efficient than cryogenic distillation even when the required O 2 purity is above 99%.

42 ENGINEERING↗
DOE OSTI2022

A parametric approach to identify synergistic domains of process intensification for reactive separation

Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). Further, the trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Phenomena-based graph representations and applications to chemical process simulation

Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.

Convergence↗
DOE OSTI2026

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI↗
DOE OSTI2020

Engineered Pseudomonas putida simultaneously catabolizes five major components of corn stover lignocellulose: Glucose, xylose, arabinose, p-coumaric acid, and acetic acid

Valorization of all major lignocellulose components, including lignin, cellulose, and hemicellulose is critical for an economically viable bioeconomy. In most biochemical conversion approaches, the standard process separately upgrades sugar hydrolysates and lignin. Here, we present a new process concept based on an engineered microbe that could enable simultaneous upgrading of all lignocellulose streams, which has the ultimate potential to reduce capital cost and enable new metabolic engineering strategies. Specifically, we engineered Pseudomonas putida, a robust microorganism capable of catabolizing aromatic compounds, organic acids, and D-glucose, to utilize D-xylose and L-arabinose by tuning D-xylose transport and pentose phosphate pathway flux. Distinct L-arabinose pathways enabled D-glucose, D-xylose, and L-arabinose co-utilization in minimal medium using model compounds as well as corn stover hydrolysate. After modifying catabolite repression, our engineered P. putida simultaneously co-utilized five representative compounds from cellulose, hemicellulose, and lignin, demonstrating the feasibility of simultaneously upgrading total lignocellulosic biomass to value-added chemicals.

Elmore, Joshua R.↗
DOE OSTI2024

Circularly Polarized Attosecond Pulses Enabled by an Azimuthal Phase and Polarization Grating

High-harmonic generation (HHG) is an extreme nonlinear optical process that can map the properties of an infrared driving laser beam onto short wavelength attosecond pulse trains. However, current techniques for generating circularly polarized high harmonics for probing magnetic materials and chiral systems have limitations: two-color collinear counter-rotating driving lasers result in a low cutoff photon energy, while single-color non-collinear counter-rotating schemes suffer from low conversion efficiency. In this work, we generate circularly polarized attosecond pulse trains by using a structured laser driver which has a rotating polarization and phase grating along the azimuthal coordinate. Furthermore, our experimental and numerical results demonstrate the production of left and right circularly polarized harmonics, which naturally separate upon propagation. Our approach uses a single laser color in a collinear geometry, that can be scaled for high efficiency. Simulations show this scheme can extend into the soft x-ray region when driven by mid-infrared driving lasers, while preserving the same high phase-matching cutoff photon energy as for linearly-polarized high harmonics.

attosecond science↗
DOE OSTI2022

Selective bacterial separation of critical metals: towards a sustainable method for recycling lithium ion batteries

The large scale recycling of lithium ion batteries (LIBs) is essential to satisfy global demands for the raw materials required to implement this technology as part of a clean energy strategy. However, despite what is rapidly becoming a critical need, an efficient and sustainable recycling process for LIBs has yet to be developed. Biological reactions occur with great selectivity under mild conditions, offering new avenues for the implementation of more environmentally sustainable processes. Here, we demonstrate a sequential process employing two bacterial species to recover Mn, Co and Ni, from vehicular LIBs through the biosynthesis of metallic nanoparticles, whilst Li remains within the leachate. Moreover the feasibility of Mn recovery from polymetallic solutions was demonstrated at semi-pilot scale in a 30 L bioreactor. Additionally, to provide insight into the biological process occurring, we investigated selectivity between Co and Ni using proteomics to identify the biological response and confirm the potential of a bio-based method to separate these two essential metals. Our approach determines the principles and first steps of a practical bio-separation and recovery system, underlining the relevance of harnessing biological specificity for recycling and up-cycling critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Estimating viscosity of individual substrate-deposited particles from measurements of their height-to-width ratios

Airborne particles alter the radiative forcing of climate and have further consequences on air visibility, atmospheric chemistry, and human health. Recent studies reported the existence of highly viscous semisolid and even solid amorphous organic aerosol (OA) particles. Particle viscosity has an impact on the heterogeneous chemistry, gas-particle partitioning, and ice nucleation properties. Consequently, variations in particle viscosity must be considered when predicting the atmospheric impact of OA. Here, in this work, we use scanning electron microscopy (SEM) and scanning transmission X-ray microscopy (STXM) to estimate the viscosity of individual particles deposited on substrates based on their characteristic height-to-width ratios, which are affected by changes in morphology upon deposition. The height-to-width ratios obtained from SEM and STXM exhibit a strong correlation, demonstrating that both imaging approaches can be applied separately for viscosity assessment of the substrate-deposited particles. While these metrics are largely qualitative, this method enables rapid assessment of particle viscosity ranges, distinguishing between semisolid (>10 10 Pa·s), viscous (10 4– 10 8 Pa·s), and liquid (10°–10 1 Pa·s) particles within ensembles of ambient particles collected for microscopy studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Natural evolutionary strategies for variational quantum computation

Abstract Natural evolutionary strategies (NES) are a family of gradient-free black-box optimization algorithms. This study illustrates their use for the optimization of randomly initialized parameterized quantum circuits (PQCs) in the region of vanishing gradients. We show that using the NES gradient estimator the exponential decrease in variance can be alleviated. We implement two specific approaches, the exponential and separable NES, for parameter optimization of PQCs and compare them against standard gradient descent. We apply them to two different problems of ground state energy estimation using variational quantum eigensolver and state preparation with circuits of varying depth and length. We also introduce batch optimization for circuits with larger depth to extend the use of ES to a larger number of parameters. We achieve accuracy comparable to state-of-the-art optimization techniques in all the above cases with a lower number of circuit evaluations. Our empirical results indicate that one can use NES as a hybrid tool in tandem with other gradient-based methods for optimization of deep quantum circuits in regions with vanishing gradients.

Anand, Abhinav (ORCID:0000000280812310)↗
DOE OSTI2023

Constraints on OPF Surrogates for Learning Stable Local Volt/Var Controllers

We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power setpoints that approximate optimal power flow (OPF) solutions. We propose an incremental control algorithm and identify two different sets of slope conditions on the local surrogates such that the network is collectively steered toward desired configurations asymptotically. Our results reveal the trade-offs between each set of conditions, with coupled voltage-power slope constraints allowing an arbitrary shape of surrogate functions but risking limitations on exploiting generation capabilities, and reactive power slope constraints taking full advantage of generation capabilities but constraining the shape of surrogate functions. AC power flow simulations on the IEEE 37-bus feeder illustrate their guaranteed stability properties and respective advantages in two DG scenarios.

asymptotic stability↗
DOE OSTI2024

Statistical Behavior of Low-Amplitude Power System Point-on-Wave Measurements

The power grid is undergoing massive changes to ensure resiliency and reliability in a more decentralized world. Distributed energy resources are becoming a prominent source of generation, potentially leading to a lack of centralized generation sources. Due to these new behaviors and system topologies, it is important to install measurement devices that are 1) accurate and 2) self-aware of their measurement quality. In this paper, a residential-scale microgrid is used to generate voltage and current waveforms, captured by Verivolt and National Instruments measurement equipment. A least-squares approach is used to separate the “clean” signals from the noise. Finally, Gaussian mixture modeling is used to approximate noise distributions, and it is shown these higher-order distribution estimates are a better fit to voltage and current noise profiles than single-mode Gaussian estimates.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Vector Field Decompositions Using Multiscale Poisson Kernel

Extraction of multiscale features using scale-space is one of the fundamental approaches to analyze scalar fields. However, similar techniques for vector fields are much less common, even though it is well known that, for example, turbulent flows contain cascades of nested vortices at different scales. The challenge is that the ideas related to scale-space are based upon iteratively smoothing the data to extract features at progressively larger scale, making it difficult to extract overlapping features. Instead, we consider spatial regions of influence in vector fields as scale, and introduce a new approach for the multiscale analysis of vector fields. Rather than smoothing the flow, we use the natural Helmholtz-Hodge decomposition to split it into small-scale and large-scale components using progressively larger neighborhoods. Our approach creates a natural separation of features by extracting local flow behavior, for example, a small vortex, from large-scale effects, for example, a background flow. We demonstrate our technique on large-scale, turbulent flows, and show multiscale features that cannot be extracted using state-of-the-art techniques.

97 MATHEMATICS AND COMPUTING↗