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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An improved process for the release of synthetic DNA sequences from a solid-phase capture support

Here, to facilitate the solid-phase purification of synthetic DNA sequences, a riboside phosphoramidite, carrying a 5-O-capture linker and a 2-O-silyl ether protecting group, is incorporated into a DNA sequence during its last solid-phase synthesis cycle. After deprotection and release of the DNA sequence from the synthesis support, the sequence is then covalently linked to a capture support to enable the removal of shorter unbound DNA sequences by simply washing these off the support. The solid-phase purified DNA sequence is then released from the capture support, through an innovative intramolecular cyclodeesterification of its terminal riboside ethyl phosphate triester entity and is isolated in a yield of 94% while displaying an exquisite purity of 97%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Sub-picosecond Production of Solute Radical Cations in Tetrahydrofuran after Radiolysis

Ultrafast hole transfer from solvent radical cations produced by radiolysis with ~10 ps, 9 MeV electron pulses to solutes was investigated in tetrahydrofuran (THF). Because of rapid fragmentation of initially produced THF +• , solute radical cations are not expected and have not previously been reported. Using 9,9-Dihexyl-2,7-dibromofluorene (Br 2 F) at 5 to 1000 mM, Br 2 F +• was observed with radiation chemical yields up to G = 2.23 / 100 eV absorbed. While more than half of this was the result of direct solute ionization, the results highlight the importance of capture of holes from THF +• prior to solvation and fragmentation. The observed data show a time-resolution limited (15 ps) rise in transient absorption of Br 2 F +• , identical in form to reports of pre-solvated or dry electron capture in water and a few organic liquids, including THF. The results were thus interpreted with a similar formalism, finding C 37 = 1.7 M, the concentration at which 37% of holes escape capture. The yield of solvent hole capture can be accounted for by the formation of solvent holes adjacent to solute molecules reacting faster than they can fragment, however mechanisms such as delocalized holes or rapid hopping may play a role. Finally, low temperature results find over two times more capture, supporting the speculation that if THF +• was longer lived, the yield of capture in under 15 ps would have been at least 2x larger at 1 M Br 2 F, possibly capturing nearly all available holes from the solvent.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Policies and Programs Available in the United States in Support of Carbon Capture and Utilization

The article seeks to compile policies and programs that provide revenue and financing support for carbon capture and utilizations projects, which are available in the United States. Often technically minded entrepreneurs and investors new to this space are unaware of available support, which could help successful development of carbon capture and utilization projects.Covered in this article are the 45Q tax credit, green bonds, loan guarantee programs, the regional greenhouse gas initiative, and low carbon fuel standards.1This article covers the eligibility and effect of each policy and program. The article also briefly reviews the current state of technology and summarizes how each technology pathway pairs with the policies covered in the article.The goal of the article is to serve as a primer for lawyers, corporate development professionals, and practitioners, who seek to learn about policies and programs available to support carbon capture and utilization (CCU) projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Role of Polymer Architecture in CO 2 Capture from Air Using Supported Poly(alkylenimine)s: Linear vs Branched Polymers

Direct air capture (DAC) of CO 2 coupled with geologic storage is a promising climate change mitigation strategy, with some applications employing amines supported on porous solids as CO 2 sorbents. While branched poly(ethylenimine) (PEI) is the standard benchmark amine material, it suffers from limited oxidative stability. Poly(propylenimine) (PPI), as an alternative, has previously demonstrated improved resistance to degradation under harsh oxidative conditions. Linear and branched PEI are commercially available, though at different molecular weights, while PPI is not commercially available. For this reason, a comparative study of all four polymers (linear PEI, branched PEI, linear PPI, branched PPI) has not been reported for DAC. In this study, we synthesize and compare low-molecular-weight (∼800 g/mol) linear (L) and branched (B) PEI and PPI supported on a model support, SBA-15 silica. These materials are evaluated for CO 2 adsorption under dry, DAC-relevant conditions (400 ppm of CO 2 , 30 °C). LPPI exhibited the highest amine efficiency at all loadings, reaching a maximum of 0.14 mmol CO 2 /mmol N, outperforming BPEI, while LPEI consistently showed the lowest uptake capacity. Temperature-programmed desorption reveals that the structure of the amine polymer impacts the CO 2 binding strength, with branched polymers displaying higher desorption energies of 102−111 kJ/mol. In situ infrared spectroscopy experiments show that all sorbents preferentially capture CO 2 as ammonium carbamate. Isobaric CO 2 uptake studies further underscore the influence of polymer mobility and support pore crowding on performance, while demonstrating the sorbents’ performance at elevated temperatures and CO 2 concentrations. All materials demonstrated good stability over 25 adsorption−desorption cycles using thermal regeneration in an inert gas purge, with only BPPI displaying a 10−11% decrease in capacity/amine efficiency during cycling, possibly due to the loss of low molecular weight, oligomeric amines. This is the first side-by-side comparison of the CO 2 sorption properties of linear and branched PEI and PPI with similar molecular weights. These findings highlight the significant role of polymer architecture in CO 2 capture efficiency and inform future designs of durable, high-performance DAC sorbents.

adsorbents↗
DOE OSTI2024

Integrated Renewable Combined Heat and Power for Ethanol

Conference presentation at 48th International Technical Conference on Clean Energy (Clearwater Clean Energy Conference), Clearwater, Florida, June 16–19, 2024. This project evaluates the technical and economic feasibility of small‑scale combined heat and power (CHP) systems using corn stover to support bioenergy with carbon capture and storage (BECCS) at ethanol facilities. The work includes resource characterization, pilot‑scale gasification and CO 2 capture testing to support techno‑economic analysis, economic evaluation of CHP deployment and potential carbon revenue, and life‑cycle assessment of gasification‑based CHP systems.

09 BIOMASS FUELS↗
DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Accelerated Aging of a Polymer-Supported Molecular Amine Direct Air Capture Sorbent: Experiments and Theory

Amine-functionalized polymer sorbents are the preferred materials for CO2 extraction from air (DAC) due to their “high” CO2 adsorption capacity and selectivity at ultra-dilute conditions. The lifetime of adsorbents is a key property of equal importance as adsorption capacity, selectivity and kinetics with direct impact on the economics of commercial-scale operations. Therefore, a detailed investigation into the contributing factors (e.g. temperature, humidity) as well as the mechanism of amine degradation is vital for the development of amines with long-term stability. Herein, in situ attenuated total reflection (ATR) Fourier transform infrared spectroscopy (FTIR) is used to monitor the real time changes to amine-based sorbents under systematically varied conditions. In addition, IR spectra obtained from density functional theory molecular dynamics are used to obtain mechanistic insights pertaining to the degradation of amine groups in DAC sorbents.

Muldoon, Patrick↗
DOE OSTI2023

Support-free adsorbents for CO 2 capture from air

A resin includes a functionalized aminopolymer having amine sites for capturing carbon dioxide molecules, where each aminopolymer molecule has at least one functional group amenable to crosslinking, a porogen, and a crosslinking initiator. A product includes an aminopolymer material formed into a self-supporting structure, the aminopolymer material including crosslinked aminopolymers having amine sites for the capture of carbon dioxide molecules.

Pang, Simon Hoching↗
DOE OSTI2024

IDAES-PSE 2.7.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.7.0 Release Highlights New features: AutoScaler and CustomScalerBase classes: Such tools are the core of the new scaling framework being implemented in IDAES. Wider adoption of scaling tools among users will result in quicker and more robust model solutions. Scaler for equilibrium reactor and saponification properties: These scaler models are examples to follow for how to use the new scaling tools. ONNX Surrogate support from Optimization & Machine Learning Toolkit (OMLT): ONNX is an open standard format to save and load ML/AI models that is widely supported by all major frameworks. This capability makes it easier for IDAES users to create surrogate models and use them without having to support each framework individually. 1D Membrane Model for CO2 Capture and Utilization: Supports ongoing efforts for modeling and optimizing polymer membrane processes for CO2 capture and conversion into formic acid. StreamScaler unit model: Unrelated to the CustomScalerBase, this unit model allows a stream’s extensive variables to be scaled by a fixed factor. This allows streams being processed by multiple units in parallel to be scaled down to unit scale and scaled back up to process scale. Bug fixes or improvements: Scaling, EoS, Diagnostics tool, Modular Properties, tests & documentation Deprecations: Old Cubic EoS

AS↗