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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A new large-scale suspended sediment model and its application over the United States

Abstract. Suspended sediment plays a vital role in the regional and global cycling of carbon and nutrients by carrying carbon and nutrients from headwaters into lowland rivers and the oceans. Sediment transport through river systems is often fundamentally modified by human activities such as reservoir management. However, a physically based representation of sediment transport is still missing in most existing Earth system models (ESMs), which are essential tools for modeling and predicting Earth system changes. Here, we introduce a multi-process river sediment module for ESMs, which includes (1) hillslope soil erosion and sediment discharge into streams, (2) sediment transport processes through river networks, (3) reservoir operation based on the inflows from upstream areas and water demand from downstream areas, and (4) sediment trapping by reservoirs. All model parameters are estimated a priori without calibration. We apply this new sediment modeling framework to the contiguous United States and validate it against historical observations of monthly streamflow and sediment discharges at 35 river gauges. The model reasonably well captures the long-term balance and seasonal variations of suspended sediment in large river systems. Furthermore, our model results show that suspended sediment discharge in managed rivers is affected more by reservoirs' direct trapping of sediment particles than by their flow regulation. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The drivers and predictability of wildfire re-burns in the western United States (US)

Evidence is mounting that the effectiveness of using prescribed burns as a management tactic may be diminishing due to the higher incidence of wildfire re-burns. The development of predictive models of re-burns is thus essential to better understand their primary drivers so that forest management practices can be updated to account for these events. First, we assess the potential for human activity as a driver of re-burns by evaluating re-burn trends both within and outside of the wildland–urban interface (WUI) of the western US. Next, we investigate the predictability of re-burns through the application of both random forest and the explanatory machine learning non-negative matrix factorization using k-means clustering (NMFk) algorithms to predict re-burn occurrence over California based on a number of climate factors. Our findings indicate that while most states showed increasing trends within the WUI when trends were conducted over longer moving windows (e.g. 20 years), California was the only state where the rate of increase was consistently higher in the WUI, indicating a stronger potential for human activity as a driver in that location. Furthermore, we find model performance was found to be robust over most of California (Testing F1 scores = 0.688), although results were highly variable based on EPA level III Ecoregion (F1 scores = 0.0–0.778). Insights provided from this study will lead to a better understanding of climate and human activity drivers of re-burns and how these vary at broad spatial scales so that improvements in forest management practices can be tuned according to the level of change that is expected for a given region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Solvent and Temperature Effects on Photoinduced Proton-Coupled Electron Transfer in the Marcus Inverted Region

Concerted proton-coupled electron transfer (PCET) in the Marcus inverted region was recently demonstrated. Understanding the requirements for such reactivity is fundamentally important and holds promise as a design principle for solar energy conversion systems. Herein, we investigate the solvent polarity and temperature dependence of photoinduced proton-coupled charge separation (CS) and charge recombination (CR) in anthracene–phenol–pyridine triads: 1 (10-(4-hydroxy-3-(4-methylpyridin-2-yl)benzyl)anthracene-9-carbonitrile) and 2 (10-(4-hydroxy-3-(4-methoxypyridin-2-yl)benzyl)anthracene-9-carbonitrile). Both the CS and CR rate constants increased with increasing polarity in acetonitrile:n-butyronitrile mixtures. The kinetics were semi-quantitatively analyzed where changes in dielectric and refractive index, and thus consequently changes in driving force (–ΔG°) and reorganization energy (λ), were accounted for. The results were further validated by fitting the temperature dependence, from 180 to 298 K, in n-butyronitrile. The analyses support previous computational work where transitions to proton vibrational excited states dominate the CR reaction with a distinct activation free energy (ΔG* CR ~ 140 meV). However, the solvent continuum model fails to accurately describe the changes in ΔG° and λ with temperature via changes in dielectric constant and refractive index. Satisfactory modeling was obtained using the results of a molecular solvent model, which predicts that λ decreases with temperature, opposite to that of the continuum model. To further assess the solvent polarity control in the inverted region, the reactions were studied in toluene. Nonpolar solvents decrease both ΔG° CR and λ, slowing CR into the nanosecond time regime for 2 in toluene at 298 K. This demonstrates how PCET in the inverted region may be controlled to potentially use proton-coupled CS states for efficient solar fuel production and photoredox catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The Influence of ENSO Diversity on Future Atlantic Tropical Cyclone Activity

El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Dynamic magneto-chiral instability in photoexcited tellurium

In systems of charged chiral fermions out of equilibrium, an electric current parallel to a magnetic field can generate a dynamic instability that amplifies electromagnetic waves. Whether this mechanism also operates in chiral solid-state systems has remained uncertain. Here we observe signatures of a dynamic magneto-chiral instability in elemental tellurium, a structurally chiral crystal, using time-domain terahertz emission spectroscopy. Under transient photoexcitation in a moderate magnetic field, we observe terahertz radiation with coherent modes that grow in amplitude over time. We present a theoretical model that describes this behaviour based on a dynamic instability of electromagnetic waves interacting with infrared-active oscillators of acceptor states in tellurium, giving rise to an amplifying polariton. These results demonstrate that magneto-chiral instabilities can emerge in solid-state systems and establish a mechanism for terahertz-wave amplification in chiral materials.

42 ENGINEERING↗
DOE OSTI2022

Cyber-Attack Detection for Active Neutral Point Clamped (ANPC) Photovoltaic (PV) Converter using Kalman Filter

With the upgrading of communication technology, cyber threats to power converters are increasing. In this paper, a model-based cyber-attack detection methodology is proposed for the interleaved Active neutral point clamped (ANPC) Photovoltaic (PV) converter. The proposed methodology identifies cyber-attacks using two estimations based on the Kalman filter and the state-space model of the ANPC PV converter. The residual between the two estimations is analyzed from a statistical perspective. Based on the Cumulative Sum (CUSUM) Control Chart, the standard errors shift of the residual is used to identify cyber-attacks. Besides, to validate the feasibility of the proposed methodology, several conditions are considered in the simulation, including white noise in the sensor, irradiance variation, and cyber-attacks in the PV converter. Furthermore, the simulation result demonstrates the proposed method can identify cyber-attacks in the ANPC PV converter.

14 SOLAR ENERGY↗
DOE OSTI2023

Evaluating the Aftershock Duration of Induced Earthquakes

As the carbon sequestration community prepares to scale up the number and size of commercial operations, the need for tools and methods to assess and mitigate risks associated with these operations becomes increasingly important. One outstanding question is whether aftershocks of induced events decay quickly after injection operations cease or if aftershock activity persists for hundreds of years before returning to background levels more akin to tectonic events (Stein and Liu, 2009). Appropriate estimates of the aftershock duration impact several operational management decisions including mitigation strategies and post-injection monitoring for seismic activity. It is hypothesized that induced earthquake rates may diminish more quickly after injection is stopped, owing to higher stressing rates from injected fluids. Alternatively, it is plausible that only the first event in the sequence is induced by increased fluid overpressures, whereas subsequent events (e.g., aftershocks) respond to the stored tectonic stresses and static and dynamic stress changes due to the mainshock (Keranen et al., 2013). Further, if the aftershock duration can be linked to stressing rates due to injection, then it follows that operational strategies to reduce seismic hazard by reducing injection rates or volumes may be successful. However, if aftershocks of induced events are relieving stored tectonic stresses, then altering injection volumes may not alleviate ongoing seismic activity. Furthermore, knowledge of an aftershock duration could aid in the determination of an appropriate post-injection monitoring period for ongoing seismicity, which is a factor in overall operational costs. In this study, we model induced seismicity sequences in Oklahoma with a coupled Coulomb rate–state earthquake rate model (Dieterich, 1994; Kroll et al., 2017) to estimate aftershocks durations. Results for the current study indicate that elevated rates of aftershock activity following induced mainshocks return to background seismicity rates in less than five years, contrary to the tens to hundreds of years observed for tectonic aftershocks.

58 GEOSCIENCES↗
DOE OSTI2026

Free Energy and Flexibility Analysis of Autoinhibited Human BRAF

The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery, given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14−3−3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing the intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with the membrane-bound RAS.

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

Latent bone modelling for estimation of plutonium concentration in skeleton of former nuclear workers

Abstract The skeleton is a major plutonium retention site in the human body. Estimation of the total plutonium activity in the skeleton is a challenging problem. For most tissue donors at the United States Transuranium and Uranium Registries, a limited number of bone samples is available. The skeleton activity is calculated using plutonium activity concentration (Cskel) and skeleton weight. In this study, latent bone modelling was used to estimate Cskel from the limited number of analysed bone samples. Data from 13 non-osteoporotic whole-body donors were used to develop latent bone model (LBM) to estimate Cskel for seven cases with four to eight analysed bone samples. LBM predictions were compared to Cskel estimated using an arithmetic mean in terms of accuracy and precision. For the studied cases, LBM offered a significant reduction of uncertainty of Cskel estimate.

Environmental Sciences & Ecology↗
DOE OSTI2026

Active learning of a crystal plasticity flow rule from discrete dislocation dynamics simulations

Continuum-scale material deformation models, such as crystal plasticity (CP), can significantly enhance their predictive accuracy by incorporating input from lower-scale (i.e. mesoscale) models. The procedure to generate and extract the relevant information is however typically complex and ad hoc, involving decision and intervention by domain experts, leading to long development times. In this study, we develop a principled approach for calibration of continuum-scale models using lower scale information by representing a CP flow rule as a Gaussian process model. This representation allows for efficient parameter space exploration, guided by the uncertainty embedded in the model through a process known as Bayesian optimization (BO). We demonstrate a semi-autonomous BO loop which instantiates discrete dislocation dynamics simulations whose initial conditions are automatically chosen to optimize the uncertainty of a model CP flow rule. Our self-guided computational pipeline efficiently generated a dataset and corresponding model whose error, uncertainty, and physical feature sensitivities were validated with comparison to an independent dataset four times larger, demonstrating a valuable and efficient active learning implementation readily transferable to similar material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Emergence of Lanes and Turbulent-like Motion in Active Spinner Fluid

Assemblies of self-rotating particles are gaining interest as a novel realization of active matter with unique collective behaviors such as edge currents and non-trivial dynamic states. Here, we develop a continuum model for a system of fluid-embedded spinners by coarse-graining the equations of motion of the discrete particles. We apply the model to explore mixtures of clockwise and counterclockwise rotating spinners. We find that the dynamics is sensitive to fluid inertia: in the inertialess system, after transient turbulent-like motion the spinners segregate and form steady traffic lanes. At small but finite Reynolds number instead, the turbulent-like motion persists and the system exhibits a chirality breaking transition leading to a single rotation sense state. Our results shed light on the dynamic behavior of non-equilibrium materials exemplified by active spinners.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Increasing aggregate size reduces single-cell organic carbon incorporation by hydrogel-embedded wetland microbes

Abstract Microbial degradation of organic carbon in sediments is impacted by the availability of oxygen and substrates for growth. To better understand how particle size and redox zonation impact microbial organic carbon incorporation, techniques that maintain spatial information are necessary to quantify elemental cycling at the microscale. In this study, we produced hydrogel microspheres of various diameters (100, 250, and 500 μm) and inoculated them with an aerobic heterotrophic bacterium isolated from a freshwater wetland (Flavobacterium sp.), and in a second experiment with a microbial community from an urban lacustrine wetland. The hydrogel-embedded microbial populations were incubated with 13C-labeled substrates to quantify organic carbon incorporation into biomass via nanoSIMS. Additionally, luminescent nanosensors enabled spatially explicit measurements of oxygen concentrations inside the microspheres. The experimental data were then incorporated into a reactive-transport model to project long-term steady-state conditions. Smaller (100 μm) particles exhibited the highest microbial cell-specific growth per volume, but also showed higher absolute activity near the surface compared to the larger particles (250 and 500 μm). The experimental results and computational models demonstrate that organic carbon availability was not high enough to allow steep oxygen gradients and as a result, all particle sizes remained well-oxygenated. Our study provides a foundational framework for future studies investigating spatially dependent microbial activity in aggregates using isotopically labeled substrates to quantify growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

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

Proton-induced reactions on Fe, Cu, and Ti from threshold to 55 MeV

Theoretical models often differ significantly from measured data in their predictions of the magnitude of nuclear reactions that produce radionuclides for medical, research, and national security applications. In this paper, we compare a priori predictions from several state-of-the-art reaction modeling packages (CoH, EMPIRE, TALYS, and ALICE) to cross sections measured using the stacked-target activation method. The experiment was performed using the Lawrence Berkeley National Laboratory 88-Inch Cyclotron with beams of 25 and 55 MeV protons on a stack of iron, copper, and titanium foils. Thirty-four excitation functions were measured from 4–55 MeV, including the first measurement of the independent cross sections for nat Fe(p,x) 49,51 Cr, 51,52m,52g,56 Mn, and 58m,58g Co. All of the models, using default input parameters to assess their predictive capabilities, failed to reproduce the isomer-to-ground state ratio for reaction channels at compound and pre-compound energies, suggesting issues in modeling the deposition or distribution of angular momentum in these residual nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗
DOE OSTI2021

A Transient-Response methodology based on experiments and modeling for Cu-Redox Half-Cycle kinetic analysis on a Cu-SSZ-13 SCR catalyst

In this report the Standard SCR reaction catalyzed by Cu-SSZ-13 is a redox process consisting of a reduction half cycle (RHC) and an oxidation half cycle (OHC) that cycle the active Cu sites between the Cu(II) and Cu(I) states. In the current work, a transient-response methodology consisting of experimental transient response Cu-redox (TRCR) measurements and kinetic modeling was developed for detailed study of individual SCR Cu-redox half cycles. The TRCR protocol allows quantification of the reducible Cu density, Cu(II)-Cu(I) partitioning, relative native RHC and OHC rates, and limiting half cycle during SCR. The half-cycle kinetics are studied over a wide (170–450 °C) temperature, and in differential segments along the catalyst length using spatially resolved capillary inlet mass-spectrometry (SpaciMS). The protocol alone provides two independent measures indicating that OHC increases faster than RHC with temperature, and that at all but the lowest temperature SCR is RHC limited. Introducing the transient kinetic models allows half-cycle reaction pathways, orders and activation energies to be studied and determined; e.g., RHC involves surface and gas-phase NH 3 routes, and OHC with O 2 involves dimer formation. Application of the full methodology provides further confirmation and quantification of the protocol conclusions, and specifically the first measurements of RHC and OHC activation energies; specifically for parallel RHC surface and gas-phase routes, and experimentally obtained OHC activation energy vs. first-principle calculations in the literature. Beyond insights related to the degreened catalyst studied here, the methodology provides a broadly available approach for quantifying how aging processes selectively impact RHC and OHC.

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

Structure and Site Evolution of Framework Ni Species in MIL-127 MOFs for Propylene Oligomerization Catalysis

A mixed-valence oxotrimer metal–organic framework (MOF), Ni-MIL-127, with a fully coordinated nickel atom and two iron atoms in the inorganic node, generates a missing linker defect upon thermal treatment in helium (>473 K) to engender an open coordination site on nickel which catalyzes propylene oligomerization devoid of any cocatalysts or initiators. This catalyst is stable for ~20 h on stream at 500 kPa and 473 K, unprecedented for this chemistry. The number of missing linkers on synthesized and activated Ni-MIL-127 MOFs is quantified using temperature-programmed oxidation, 1 H nuclear magnetic resonance spectroscopy, and X-ray absorption spectroscopy to be ~0.7 missing linkers per nickel; thus, a majority of Ni species in the MOF framework catalyze propylene oligomerization. In situ NO titrations under reaction conditions enumerate ~62% of the nickel atoms as catalytically relevant to validate the defect density upon thermal treatment. Propylene oligomerization rates on Ni-MIL-127 measured at steady state have activation energies of 55–67 kJ mol –1 from 448 to 493 K and are first-order in propylene pressures from 5 to 550 kPa. Density functional theory calculations on cluster models of Ni-MIL-127 are employed to validate the plausibility of the missing linker defect and the Cossee–Arlman mechanism for propylene oligomerization through comparisons between apparent activation energies from steady-state kinetics and computation. Here this study illustrates how MOF precatalysts engender defective Ni species which exhibit reactivity and stability characteristics that are distinct and can be engineered to improve catalytic activity for olefin oligomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗