Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reactivity maps”

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.

206 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2023

RECLAIM: Electrochemical Lithium and Nickel Extraction with Concurrent Carbon Dioxide Mineralization

This project aims to develop technologies toward the production of Li and Ni from CO 2 -reactive minerals and rocks that contain Ca and Mg, while sequestering CO 2 . The technologies include acoustic stimulation and electrolytic proton production, which use electricity to liberate valuable metal ions from the surrounding mineral matrix at sub-boiling temperatures (~20-80°C). Feedstocks include Li/Ni/Ca/Mg-rich igneous and sedimentary rocks and minerals such as holmquistite, hectorite, lateritic Ni ores enriched in Mg-rich serpentine. Other examples of feedstocks that could be used include coarse grained orthocumulate, mine tailings, etc. In the first step, the electrolytic breakdown of water to H + and OH – (as well as O 2 and H 2 ) will be induced by applying an electric potential to simultaneously produce acidity and alkalinity. The solid feedstocks will be dissolved in the acidic anolyte under acoustic stimulation. Solubilized species will then undergo separation using our unique Li + -selective membranes driven by electrodialysis, leading to concentration of Li as soluble lithium silicate, from which Li 2 CO 3 can be derived by reaction with CO 2(g) while supplying cathode alkalinity. Also at the cathode, stepwise electrolytic precipitation of metal hydroxides, including Ni(OH) 2 , Ca(OH) 2 , and Mg(OH) 2 is performed along a cascade reactor in which both the applied potential and pH increase downstream, thereby simultaneously extracting and separating the metals. Finally, exposure of Ca(OH) 2 and Mg(OH) 2 to dilute CO 2 will result in CO 2 uptake in the form of Ca and Mg carbonates. The primary accomplishments include sample procurement and characterization. Progress has been made on precursor identification and mapping, establishing protocols for assessing metal extractability under sonication, and preliminary technoeconomic analysis (TEA) and life cycle analysis (LCA).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Li–Mn–O Li-rich cation disordered rock-salt cathode materials do not undergo reversible oxygen redox during cycling

An in-depth study of “Li 4 Mn 2 O 5 ”, a nanocomposite of Li 2 O and Li 4-x Mn 2 O 5 with a disordered rock salt structure (LMO), was conducted to determine the origins of the observed anomalously high charge and discharge capacity in lithium cells, which can exceed 350 mA h g -1 . Using soft and hard X-ray absorption spectroscopy (XAS), mapping of resonant inelastic X-ray scattering (mRIXS), and X-ray Raman spectroscopy (XRS), it was determined that electrochemical decomposition of Li 2 O upon charge and reduction of Mn to below 3+ during discharge is responsible for the capacities that are observed, with no evidence of contributions from reversible oxygen redox. Here, the over-reduction is exacerbated when charging limits of 4.5–4.8 V are used due to side reactions between electrolytic solution and the highly oxidized active material. These side reactions result in dissolution of Mn at room temperature and release of oxygen and other gases during initial cycles, which, in turn, cause rapid capacity fading. This is accompanied by evolution of the voltage profile upon cycling towards one that resembles that of manganese oxide spinels. The cycling behavior can be improved somewhat by reducing the upper voltage limit, although this results in a diminishment of the discharge capacities below 200 mA h g -1 . By adding various amounts of spinel LiMn 2 O 4 during synthesis, it was possible to produce LMOs with rock salt structures having significantly improved cycling behavior but still having capacities in excess of 250 mA h g -1 . An optimized modified material also exhibits better rate capability and much less gas evolution during initial cycles than the unmodified LMO. Interestingly, as-made modified materials generally exhibited lower than expected average Mn oxidation states attributable to oxygen loss during the synthesis process, as well as higher capacities than expected based on their manganese contents. The oxygen loss during processing may reduce the activity of the remaining oxygen and account for the lower reactivity of the spinel-modified material.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Method Development for In-situ Detection of Latent Herpesvirus DNA from Saliva using Nanopore Sequencing

Research toward latent herpesvirus reactivation has been intensively addressed through Space Shuttle and International Space Station (ISS) investigations. This work has provided the understanding that persistent reactivation of herpesviruses from asymptomatic crew can be detected through viral shedding in saliva, urine, and blood. Occasionally, viral reactivation from the latency stage can pose a threat to crew health (clinical manifestation) before, during, and after flight missions. Furthermore, previous work detailing correlations with immunity indicate that monitoring viral reactivation could be implemented to assess potential immune dysfunction. While in-flight monitoring is desirable, there is no well-established procedure or method for real-time evaluations, and research to date has relied on postflight, ground-based analysis. The development of portable molecular technologies like the miniPCR™ (miniPCR Bio) thermal cycler and the MinION™ sequencer (Oxford Nanopore Technologies) have confirmed that real-time monitoring is possible in extreme and low resource environments. These devices, combined with simple sample preparation methods, have been used to demonstrate bacterial identification onboard the ISS, as well as rapid viral detection in remote locations on Earth. The work here builds upon previous molecular advancements onboard the ISS toward the development and validation of a spaceflight-compatible method for viral detection from crew samples. Several herpesviruses can be detected in saliva, which provides a non-invasive means to collect samples for monitoring. While the basis for this method lies in previous spaceflight investigations, key points for method optimization include DNA extraction from saliva, viral primer selection, and bioinformatic processes for data analysis. To increase viral yield, numerous DNA extraction methods have been evaluated and will be discussed in detail. For initial development and testing, varicella-zoster virus (VZV) is being targeted though open reading frame 51 and 63 (ORF51, ORF63), as the replication origin-binding protein is highly expressed during latency. Optimization of the thermal cycling parameters has resulted in the ability to test the entire process. The full method has been tested with both viral VZV DNA standards and saliva spiked with varying concentrations of VZV. Viral sequence data were mapped to the reference sequence using minimap2. Prior to mapping, DNA sequencing reads were filtered for length and quality, barcodes were removed, and alignment identity calculated. Following further assessments, statistics were compared across multiple sequencing experiments and are being used to determine the success of the protocols. Forward work will include the incorporation of herpes simplex virus 1 (HSV-1) and Epstein-Barr virus (EBV) primers as well as the validation of results to the terrestrial qPCR standard assay. Upon full validation of the developed method, saliva will be collected from 20 healthy subjects and spiked with viral DNA. These samples will be split and assayed with the MinION and standard qPCR assay.

Hang N Nguyen↗
DOE OSTI2023

Innovative Strategies for Long-Term Monitoring of Complex Groundwater Plumes at DOE’s Legacy Sites (Workshop Report)

Most remaining Department of Energy (DOE) sites will require extended periods of institutional control, especially at complex groundwater sites where attenuation-based strategies have been implemented to facilitate closure. The current practice of monitoring—obtaining and analyzing contaminant concentration in groundwater samples at numerous wells—will account for a large portion of the projected life-cycle at these DOE sites unless a new approach is adopted. State-of-the-art technologies are being developed, including in situ sensors, geophysics, radiation mapping, numerical modeling and AI/ML. These technologies can optimize monitoring strategies in space and time, provide spatially extensive information at vulnerable regions and/or provide more continuous monitoring at lower cost. As part of DOE’s Office of Environmental Management (DOE-EM’s) efforts to advance long-term monitoring systems, an in-person/virtual hybrid workshop was hosted by Savannah River National Laboratory (SRNL) on January 24 and 25, 2023, in Augusta, Georgia. Because DOE-EM’s complex sites will eventually be transferred to DOE’s Office of Legacy Management (DOE-LM), representatives of DOE-LM were important participants in the workshop. The purpose of the workshop was to identify challenges and opportunities for deploying advanced technologies for long-term monitoring at DOE sites. The key questions during the workshop were: 1) the regulatory acceptance of replacing a process that traditionally has used laboratory sampling and analysis of groundwater samples, and 2) the application of this strategy to the southwestern arid sites that include many of the remaining DOE-EM and DOE-LM complex groundwater plumes. Characteristics common to most arid sites present both limitations and opportunities for advanced technologies. DOE-EM has funded a National Laboratory team from SRNL, Lawrence Berkeley National Laboratory (LBNL), and Pacific Northwest National Laboratory (PNNL) to establish the overarching framework of long-term monitoring by systematically combining advanced hardware and software technologies. This project is titled “Advanced Long-Term Environmental Monitoring Systems (ALTEMIS)” and is sponsored by the DOE-EM Technology Development Program. The multi-laboratory team is currently developing and testing innovative monitoring strategies, including the use of in situ groundwater sensors, geophysics, drone/satellite-based remote sensing, reactive transport modeling, and artificial intelligence/machine learning (AI/ML). The project’s demonstration testbed is at the Savannah River Site (SRS) F-Area Seepage Basins, where a well-characterized complex groundwater plume composed of uranium and other radionuclides is in the latter stages of remediation. The workshop included more than 70 participants, presentations, a field visit to F-Area, breakout working groups, and large group discussion. Participants developed recommendations on five topics: in situ sensors, spatially integrative tools, challenges to regulatory acceptance, AI/ML strategies, and transitioning sites to DOE-LM.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Multi-state Catalysts Modulated by Mechanical Force (Final Report)

The development of more efficient catalytic processes and new approaches to control catalytic activity and selectivity are central to the realization of more selective, atom economic, and energy efficient routes to value added chemicals and polymers. The reactivity and selectivity of a transition metal catalyst is intimately related to the ligand-sphere geometry and, in many cases, the ideal ligand geometry for one step of a catalytic cycle is poorly matched to the ideal ligand geometry for another, resulting in sub-optimal efficiency. Macroscopic mechanical forces are both large, potentially much larger than interatomic forces, and are directional and localized to an extent that differentiates them from other forms of energy input such as heat or light. As such, mechanical force represents a heretofore untapped approach to modulate catalyst geometry, with the potential to reversibly modulate catalyst geometry on the timescale of catalytic turnover or monomer enchainment. This project has addressed the fundamental challenges in material-to-molecule strain coupling associated with the development of a new class of mechanically responsive catalysts (mechanocatalysts) in which active organotransition metal catalysts are strategically embedded in a flexible polymer network such that application of external mechanical force (stretching or deformation) leads to modulation of catalyst geometry, and hence reactivity and selectivity. Our efforts during the tenure of this grant were directed toward the elucidation of force-reactivity relationships of elementary transformations that occur within the first coordination sphere of a transition metal complex employing stiff stilbene photoswitches tethered to a flexible bidentate phosphine ligand derived from MeOBiphep as molecular force probes which provide a range of compressive and extension forces to the coupled transition metal complex depending on the geometry of the stiff stilbene and length of the tethering chains. During the tenure of this grant, we have quantified the rate of C(sp 2 )-C(sp 2 ) reductive elimination from platinum(II) diaryl complexes containing bis(phosphine) force probe ligands as a function of mechanical force; compressive forces decreased the rate of reductive elimination whereas extension forces increased the rate relative to the strain-free MeOBiphep complex with a 3.4-fold change in rate over a ~290 pN range of restoring forces. In a similar manner, we have quantified the rate of oxidative addition of bromobenzene to low-ligated palladium(0) complexes containing force probe ligands as a function of mechanical force; compressive forces increase the rate of oxidative addition, whereas tensile forces decrease the rate with a ~6 fold change in rate across ~340 pN of force applied to the complexes. In both cases, experimental and computational analyses argue strongly against any significant force-induced perturbation of ground state geometry within the first coordination sphere of the reactant complexes. Rather, the force/rate behavior observed for these transformations across these ranges of forces is attributed to the coupling of force to the nuclear motion comprising the reaction coordinates for reductive elimination and oxidative addition. These results together inform the development of catalysts whose activity can be tuned by an external force that is adjusted within a catalytic cycle and suggest opportunities to experimentally map geometry changes associated with reactions in transition metal complexes and potential strategies for force-modulated catalysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Multichannel dynamics in the OH+ n -butane reaction revealed by crossed-beam slice imaging and quasiclassical trajectory calculations

Multidimensional reactions present various channels that can exhibit very different dynamics and give products of varying subsequent reactivity. Here, we present a combination of experiment and theory to reveal the dynamics of hydrogen abstraction by OH radical at primary and secondary sites in n-butane at a collision energy of 8 kcal/mol. Crossed molecular beam slice imaging experiments unequivocally probe the secondary abstraction channel showing backward angular distributions with mild energy release to product translation, which are accurately captured by trajectory calculations using a specific-reaction-parameter Hamiltonian. Additionally, experiments containing both reaction channels indicate a less marked backward character in the angular distribution, whose origin is shown by trajectory calculations to appear as an evolution toward more sideways scattering from the secondary to primary channel. While the two channels have markedly different angular distributions, their energy release is largely comparable, showing ample energy release into the water product. The synergistic combination of crossed-beam imaging and trajectories opens the door to detailed reaction-dynamics studies of chemical reactions with ever-increasing complexity.

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

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗