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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

First-Principles Integrated Adsorption Modeling for Selective Capture of Uranium from Seawater by Polyamidoxime Sorbent Materials

Nuclear power is a relatively carbon-free energy source that has the capacity to be utilized today in an effort to stem the tides of global warming. The growing demand for nuclear energy, however, could put significant strain on our uranium ore resources, and the mining activities utilized to extract that ore can leave behind long-term environmental damage. A potential solution to enhance the supply of uranium fuel is to recover uranium from seawater using amidoximated adsorbent fibers. This technology has been studied for decades but is currently plagued by the material’s relatively poor selectivity of uranium over its main competitor vanadium. In this work, we investigate the binding schemes between uranium, vanadium, and the amidoxime functional groups on the adsorbent surface. Using quantum chemical methods, binding strengths are approximated for a set of complexation reactions between uranium and vanadium with amidoxime functionalities. Those approximations are then coupled with a comprehensive aqueous adsorption model developed in this work to simulate the adsorption of uranium and vanadium under laboratory conditions. Experimental adsorption studies with uranium and vanadium over a wide pH range are performed, and the data collected are compared against simulation results to validate the model. It was found that coupling ab initio calculations with process level adsorption modeling provides accurate predictions of the adsorption capacity and selectivity of the sorbent materials. Furthermore, this work demonstrates that this multiscale modeling paradigm could be utilized to aid in the selection of superior ligands or ligand compositions for the selective capture of metal ions. Furthermore, this first-principles integrated modeling approach opens the door to the in silico design of next-generation adsorbents with potentially superior efficiency and selectivity for uranium over vanadium in seawater.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Use of FLOSIC for understanding anion-solvent interactions

An Achille’s heel of lower-rung density-functional approximations is that the highest-occupied-molecular-orbital energy levels of anions, known to be stable or metastable in nature, are often found to be positive in the worst case or above the lowest-unoccupied-molecular-orbital levels on neighboring complexes that are not expected to accept charge. A trianionic example, [Cr(C2O4)3]3−, is of interest for constraining models linking Cr isotope ratios in rock samples to oxygen levels in Earth’s atmosphere over geological timescales. Here we describe how crowd sourcing can be used to carry out self-consistent Fermi–Löwdin–Orbital-Self-Interaction corrected calculations (FLOSIC) on this trianion in solution. The calculations give a physically correct description of the electronic structure of the trianion and water. In contrast, uncorrected local density approximation (LDA) calculations result in approximately half of the anion charge being transferred to the water bath due to the effects of self-interaction error. Use of group-theory and the intrinsic sparsity of the theory enables calculations roughly 125 times faster than our initial implementation in the large N limit reached here. By integrating charge density densities and Coulomb potentials over regions of space and analyzing core-level shifts of the Cr and O atoms as a function of position and functional, we unambiguously show that FLOSIC, relative to LDA, reverses incorrect solute-solvent charge transfer in the trianion-water complex. In comparison to other functionals investigated herein, including Hartree–Fock and the local density approximation, the FLOSIC Cr 1s eigenvalues provide the best agreement with experimental core ionization energies.

Chemistry↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Measurement of the W boson mass

The W boson mass is measured using proton-proton collision data at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 1.7 fb -1 recorded during 2016 by the LHCb experiment. With a simultaneous fit of the muon $q/ρ_T$ distribution of a sample of W →$μv$ decays and the $\phi^*$ distribution of a sample of Z → $μμ$ decays the W boson mass is determined to be $m_w$ =80354±23 stat ±10 exp ±17 theory ±9 PDF MeV, where uncertainties correspond to contributions from statistical, experimental systematic, theoretical and parton distribution function sources. This is an average of results based on three recent global parton distribution function sets. The measurement agrees well with the prediction of the global electroweak fit and with previous measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Probing Intra-Halo Light with Galaxy Stacking in CIBER Images

We study the stellar halos of 0.2 ≲ $z$ ≲ 0.5 galaxies with stellar masses spanning $M$* ~ 10 10.5 to 10 12 $M$ ⊙ (approximately $L$* galaxies at this redshift) using imaging data from the Cosmic Infrared Background Experiment (CIBER). A previous CIBER fluctuation analysis suggested that intra-halo light (IHL) contributes a significant portion of the near-infrared extragalactic background light (EBL), the integrated emission from all sources throughout cosmic history. In this work, we carry out a stacking analysis with a sample of ~30,000 Sloan Digital Sky Survey (SDSS) photometric galaxies from CIBER images in two near-infrared bands (1.1 and 1.8 $μ$m) to directly probe the IHL associated with these galaxies. We stack galaxies in five sub-samples split by brightness and detect an extended galaxy profile beyond the instrument point-spread function (PSF) derived by stacking stars. We jointly fit a model for the inherent galaxy light profile plus large-scale one- and two-halo clustering to measure the extended galaxy IHL. We detect nonlinear one-halo clustering in the 1.8 $μ$m band at a level consistent with numerical simulations. Furthermore, by extrapolating the fraction of extended galaxy light, we measure to all galaxy mass scales, we find ~30%/15% of the total galaxy light budget from galaxies is at radius $r$ > 10/20 kpc, respectively. These results are new at near-infrared wavelengths at the $L$* mass scale and suggest that the IHL emission and one-halo clustering could have appreciable contributions to the amplitude of large-scale EBL background fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Coupling of an atmospheric pressure microplasma ionization source with an Orbitrap Fusion Lumos Tribrid 1M mass analyzer for ultra-high resolution isotopic analysis of uranium

The coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma to an Orbitrap Fusion Lumos Tribrid 1M mass spectrometer is described as a significant step towards the elimination of isobaric interferences in elemental/isotopic mass spectrometry. The developed setup permits broadband, elemental mass spectra to be easily acquired at a mass resolution (m/Δm) of 500 000. A new ion source housing and integrated control system provide enhanced stability and sensitivity of the microplasma ion source in comparison to the previous designs. Detailed evaluation of the ion sampling parameters provided insight into differences with other Orbitrap platforms leading to a 5-fold increase in resolution in elemental/isotopic analysis. The roles of data acquisition/ion processing parameters were evaluated with regards to the precision and accuracy of 235 U/ 238 U isotope ratios. Significantly, the precision of those measurements improves as a function of pre-set mass resolution up to a value of 1 000 000, where a precision of 0.086% RSD is obtained for uranium concentrations of 100 ng mL− 1 . Analytical response curves (log–log), acquired for the two uranium isotopes at a resolution of 120 000 were linear (R 2 = 0.9969) over more than 5 orders of magnitude, with limits of detection of 1 pg mL −1 for U. Based on 60 μL injection volumes, this represents a mass of 70 fg 235 U. These figures of merit satisfy International Target Values (ITVs) for Measurement Uncertainties in Safeguarding Nuclear Materials set by the International Atomic Energy Agency (IAEA). Ultimately, and totally unique from beam-type instruments, the move to the higher-resolution Orbitrap platform provides all of the benefits of high mass resolution, with no penalties in sensitivity, precision, or dynamic range for uranium analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

DISTINCT: Diversity in Solar Talent Through INnovative Curriculum and Training: An Integrated Research and Education Approach towards Creating Diversity and Advancing Utility-Scale Solar Technology

The DISTINCT project research objective is to develop an innovative N-port power converter for a utility-scale PV system that is modular, compact and cost-effective and that will enable the integration of a high-frequency, high-voltage solid-state transformer. The novelty of the proposed research is the electrical power conversion architecture using an N-port converter system that replaces the output 60Hz transformer with an integrated high-frequency low-weight solid-state transformer reducing power electronics and BOS costs to meet SunShot goals through modularity and direct high-voltage interconnection. A challenge in direct integration with a 13.8kV line is the high voltage handling capacity of the converters combined with high efficiency operation. The front-end converter for each port is a Neutral-Point Clamped (NPC) Multi-Level dc-dc Dual-Active Bridge (ML-DAB) which allows Maximum Power Point Tracking (MPPT). The integrated high frequency transformer provides the galvanic isolation between the PV and grid side and also steps up the low dc voltage from PV source. Following the ML-DAB stage, in each port, is an inverter with H-bridge configuration or NPC configuration. N number of NPC inverters’ outputs are cascaded to attain the per-phase line-to-neutral voltage to connect directly to the distribution grid (i.e. 13.8 kV). The cascaded inverters have the inherent advantage of using lower rated devices, smaller filters and low Total Harmonic Distortion (THD) required for PV grid interconnection. Our analysis and simulation results show improved performance on cost, efficiency, service life with zero downtime and THD. A comprehensive control scheme is presented to ensure the maximum power from each port and each phase are sent to the grid. A functional prototype of a 2-port converter with ML-DAB and cascaded H-bridges has been designed, built, and tested in a laboratory setup to verify the target technical metrics. The N-port converter system due to its modular structure with individual control per port can be easily adapted to integrate functionalities that go well beyond the conventional grid support functions and mitigates impacts of forecasted fast ramp downs or ramp ups and single-fault conditions by automatic reconfiguration of the output.

14 SOLAR ENERGY↗
DOE OSTI2023

Time-Resolved Line Shapes of Single Quantum Emitters via Machine Learned Photon Correlations

Solid-state single-photon emitters (SPEs) are quantum light sources that combine atomlike optical properties with solid-state integration and fabrication capabilities. SPEs are hindered by spectral diffusion, where the emitter’s surrounding environment induces random energy fluctuations. Timescales of spectral diffusion span nanoseconds to minutes and require probing single emitters to remove ensemble averaging. Photon correlation Fourier spectroscopy (PCFS) can be used to measure time-resolved single emitter line shapes, but is hindered by poor signal-to-noise ratio in the measured correlation functions at early times due to low photon counts. Here, we develop a framework to simulate PCFS correlation functions directly from diffusing spectra that match well with experimental data for single colloidal quantum dots. We use these simulated datasets to train a deep ensemble autoencoder machine learning model that outputs accurate, noiseless, and probabilistic reconstructions of the noisy correlations. Using this model, we obtain reconstructed time-resolved single dot emission line shapes at timescales as low as 10 ns, which are otherwise completely obscured by noise. This enables PCFS to extract optical coherence times on the same timescales as Hong-Ou-Mandel two-photon interference, but with the advantage of providing spectral information in addition to estimates of photon indistinguishability. Further, our machine learning approach is broadly applicable to different photon correlation spectroscopy techniques and SPE systems, offering an enhanced tool for probing single emitter line shapes on previously inaccessible timescales.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Valuation of ecosystem services in alternative bioenergy landscape scenarios

Abstract Agricultural land in the Midwest is a source of food and fuel, as well as biodiversity. It is also a cause of excess nutrients that make their way to the Mississippi River and the Gulf of Mexico. To address unsustainable changes to biogeochemical cycles and ecosystem functions, a multidisciplinary approach involving social science, natural science, and engineering is often effective. Given the potential of second‐generation biofuels, and capitalizing on the deep‐rooted perennial bioenergy crops capable of thriving in poor soils, we demonstrated an integrated socio‐environmental analysis of the impacts of growing switchgrass within row‐crop landscapes in Illinois. In this study, we model land use scenarios that incorporate switchgrass as a biofuel crop in a Midwest corn‐belt watershed using the Soil Water Assessment Tool coupled with an economic analysis for the Vermilion Basin in Illinois. We estimated the values of ecosystem services under an alternative bioenergy landscape, including commodity and bioenergy crops, changes in biogeochemistry, and recreational services. The estimated annual values of nitrate and sediment reduction attributed to bioenergy crops range from $38 million to $97 million and $16,000 to $197,000, respectively. The annual value of carbon dioxide emission reduction ranges from $1.8 million to $6.1 million based on the initial crop rotation pattern. Estimated average annual values for wildlife viewing, water‐based recreation, and pheasant hunting are $1.24 million, $0.17 million, and $0.3 million, respectively. To our knowledge, this study represents the first effort to comprehensively quantify ecosystem services using a process‐based model, and estimate their value in an alternative bioenergy landscape. The information we generate could aid in understanding the potential for biomass production from marginal land and the total economic value of the landscape at various spatial scales. The framework is useful in fostering alternative bioenergy landscapes with synergies in a food, energy, and conservation nexus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing

The surge in scientific literature obscures breakthroughs and hinders the discovery of new research paths. We propose an artificial intelligence (AI) powered framework using large language models (LLMs) and knowledge graphs (KGs) to automate parts of scientific discovery, focusing on energy-efficient AI circuits. Our hybrid approach combines LLMs, structured data, and ontology-based reasoning to construct a comprehensive knowledge graph that integrates insights across computational neuroscience, spiking neuron models, learning rules, architectural motifs, and neuromorphic device technologies. This multi-domain representation enables the generation of hypotheses that connect biological function with implementable, energy-efficient hardware architectures. Using KG embeddings and graph neural networks, the framework generates hypotheses for novel circuits, validates them through optimization on exascale HPC systems, and with tools like SuperNeuro and Fugu, the most promising designs will be prototyped in hardware. This open-source system aims to accelerate discoveries and bridging neuroscience with hardware innovation, drive collaboration, and unlock new opportunities in low-power AI computing.

Gautam, Ashish [ORNL]↗
DOE OSTI2020

Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)

One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) and TempestRemap offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

58 GEOSCIENCES↗
DOE OSTI2019

Centralized System Management of IPMI Enabled Platforms Using EPICS

Intelligent Platform Management Interface (IPMI) is a specification for computer hardware platform management and monitoring. The interface includes features for monitoring hardware sensors like fan speed and device temperature, inventory discovery, event propagation and logging. All IPMI functionality is accessible without the host operating system running. With its wide support across hardware vendors and the backing of a standardization committee, it is a compelling instrumentation for integration into a control system for large experimental physics projects. Integrating IPMI into EPICS provides the benefit of centralized monitoring, archiving and alarming integrated with the facility control system. A new project has been started to enable this capability by creating a native EPICS device driver built on the open-source FreeIPMI library for the remote host connection interface. The driver supports automatic system components discovery for creating EPICS database templates, detailed device information from Field Replaceable Unit interface, sensor monitoring with remote threshold management, geographical PV addressing in PICMG based platforms and PICMG front panel lights readout.

Vodopivec, Klemen↗
DOE OSTI2026

Bioinorganic Chemistry of Nitrification: Structure and Function of Ammonia Monooxygenase (Final Technical Report)

The overarching goal of this project was to elucidate biochemical mechanisms that ubiquitous microorganisms use to enable primary metabolism based on nitrification, the multi-electron oxidation of ammonia (NH 3 ) to nitrite (NO 2 – ). This chemistry enables life to substitute carbon based fuel with nitrogen. Understanding the underlying chemistry was pursued to help inform the use of ammonia as an alternative fuel source compared to petroleum, capitalizing on the widespread infrastructure for production and distribution of this substance in the US. This project specifically focused on characterizing ammonia monooxygenase, an integral membrane copper protein that initiates nitrification via the aerobic oxidation of NH 3 to hydroxylamine (NH 2 OH).

09 BIOMASS FUELS↗
DOE OSTI2021

Evaluation of Data Catalog Software for Hanford Site Environmental Datasets

Environmental information and data underpin achievement of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) mission at the Hanford Site. The Hanford Environmental Data Management (HEDM) Program is the DOE Richland Operations Office (RL) approach to develop and implement a formal program for managing environmental data and the associated records, materials, and systems at the Hanford Site. The current project, contract, organization, and contractor-specific efforts at managing environmental data sets are insufficient to provide orderly, long-term, site-wide access. A vital element to be created within the HEDM program plan is a catalog of data sources, called the Hanford Environmental Information and Data Index (HEIDI), that will enable long-term access and retrievability for the multiple independent sources of data that might otherwise be difficult to discover. This report compares leading open source and commercial data catalog platforms using criteria to assess the functionality needed to develop the HEIDI catalog of Hanford data sources that connects and exchanges data with established Hanford Local Area Network (HLAN) enterprise information technology systems. Proprietary platforms evaluated included ArcGIS Enterprise Sites, Junar, OpenDataSoft, and Socrata, and non-proprietary platforms included Energy Data eXchange (EDX), Comprehensive Knowledge Archive Network (CKAN), and DKAN (a Drupal-based open data portal based on CKAN). Capabilities supporting data discoverability, retrieval, and archival, as well as metadata standard requirements and integration into the HLAN were rated as either failing to meet requirements (F), meeting requirements (M), or exceeding requirements by delivering additional desired features (E). The lowest rating for any capability area was assigned as the overall rating for the platform. These findings enable DOE-RL and the contractors implementing the HEDM plan to focus on candidate tools likely to meet the requirements for implementing HEIDI. All of the platforms receiving an overall rating of ‘F’ were unable to be deployed on Hanford infrastructure or within dedicated cloud resources. A propriety software-as-a-service (SaaS) model of delivering a data catalog (e.g., found in software such as Junar and OpenDataSoft) favors consistency across customers at the expense of customization and configurable roles that are needed for Hanford work. Hosting data on a shared commercial platform places limits on dataset size (maximum of 240 Mb for OpenDataSoft), a significant limitation for HEIDI implementation. EDX, a government data catalog based on CKAN, received the ‘F’ rating due to an inability to incorporate authentication from HLAN into the system. Among platforms rated ‘M’ or ‘E’, only the Socrata platform had a SaaS delivery model. In contrast to other SaaS platforms, Socrata provided custom roles and gateways that allow local datasets to be incorporated into an online catalog. Socrata also complies with the Federal Risk and Authorization Management Program, a significant benefit for cloud-based management of Hanford data. The other platforms rated ‘M’ or ‘E’, ArcGIS Enterprise Sites, CKAN, and DKAN, provide fully self-hosted options, allowing for greater control and flexibility with the HEIDI catalog. These widely used tools have supportive communities of practice, extensive customization options, and demonstrated deployments that provide evidence that they can meet requirements, often deliver additional desired features, and work well with federal government systems. Completely customized alternatives built on a collection of applications were not evaluated because achieving similar performance to CKAN or DKAN requires substantial resources, especially in the absence of the active communities that have grown to support these tools. ArcGIS Enterprise Sites, Socrata, CKAN, and DKAN were evaluated as strong candidates for successful implementation with HEIDI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Systems and methods for advanced grid integration of distributed generators and energy resources

A circuit for a smart photovoltaic (PV) inverter system and the smart PV inverter system are described. The circuit includes one or more strings coupled to an electrical load. Each of the one or more strings further includes one or more string members coupled in series, where each of the one or more string members comprises a voltage source and an inverter. The circuit also includes a controller to receive an output from an operator controller and control the strings, where the controller is configured to control the strings by providing a function command to a first string member of each of the one or more strings based on the output from the operator controller. The voltage source may also receive an output from an energy output device. Further, the inverter may be configured to convert the output of energy output device into an energy source of electrical load.

Bhowmik, Shibashis↗
DOE OSTI2024

Ionic Pairs-Engineered Fluorinated Covalent Organic Frameworks Toward Direct Air Capture of CO 2

The covalent organic frameworks (COFs) possessing high crystallinity and capability to capture low-concentration CO 2 (400 ppm) from air are still underdeveloped. The challenge lies in simultaneously incorporating high-density active sites for CO 2 insertion and maintaining the ordered structure. Herein, a structure engineering approach is developed to afford an ionic pair-functionalized crystalline and stable fluorinated COF (F-COF) skeleton. The ordered structure of the F-COF is well maintained after the integration of abundant basic fluorinated alcoholate anions, as revealed by synchrotron X-ray scattering experiments. The breakthrough test demonstrates its attractive performance in capturing (400 ppm) CO 2 from gas mixtures via O$-$C bond formation, as indicated by the in situ spectroscopy and operando nuclear magnetic resonance spectroscopy using 13 C-labeled CO 2 sources. Both theoretical and experimental thermodynamic studies reveal the reaction enthalpy of ≈-40 kJ mol -1 between CO 2 and the COF scaffolds. This implies weaker interaction strength compared with state-of-the-art amine-derived sorbents, thus allowing complete CO 2 release with less energy input. The structure evolution study from synchrotron X-ray scattering and small-angle neutron scattering confirms the well-maintained crystalline patterns after CO 2 insertion. In conclusion, the as-developed proof-of-concept approach provides guidance on anchoring binding sites for direct air capture (DAC) of CO 2 in crystalline scaffolds.

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

A Simple Criterion for Feasibility of Heat Integration between Distillation Streams Based on Relative Volatilities

In a multicomponent distillation configuration, there are numerous sources and sinks of heat, and a potential way to reduce the heat duty requirement is to perform heat integration. Unfortunately, an algorithmic search of the optimal heat integration opportunities is intractable when the required temperatures of intermediate streams are computed via complex models. Instead, in this work, we introduce pressure-scaled pseudo relative volatility, a new metric to compare stream temperatures. Here, we justify the use of pseudo relative volatility by proving that this variable is a monotonically increasing function of the liquid fraction in a saturated mixture stream. Using this metric, we derive a shortcut criterion to check the feasibility of various heat integration opportunities, such as thermal coupling via heat transfer (TCH). The advantage of this approach is that it circumvents the need for explicit temperatures and instead relies on composition, component relative volatilities, and pressure—quantities that are readily available in shortcut models for optimization of distillation configurations. Leveraging this fact, we propose a new optimization framework that identifies feasible TCHs that we consider within the formulation while minimizing the total heat duty of a distillation configuration. We demonstrate, on a few examples, that our formulation can identify heat duty efficient configurations, some of which are multieffect configurations. Using this methodology, we discover configurations that are not only simpler than the fully thermally coupled (FTC) configuration but also have a much lower heat duty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Podman-hpc v1.0

We have developed some scripts and tools that compliment an existing open-source product (Podman, https://podman.io/). This enables podman to function as a high-performance container solution. This capability is similar to Shifter and Singularity (both developed at LBNL). The advantage of leveraging Podman is it has greater support in the broader community outside of HPC and has capabilities missing from many of the HPC-only solutions. The specific enhancements we wish to share our how to enable Podman to scale to very large HPC jobs and our integrations we have done to utilize high-performance interconnects and GPUs.

Cannon, Richard↗