Theory of nearly symmetric excited-state - Excited-state electron capture in ion-atom inelastic scattering
Symmetric excited state electron capture cross sections in ion-atom inelastic scattering, using two state approximation formulas
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Symmetric excited state electron capture cross sections in ion-atom inelastic scattering, using two state approximation formulas
LANDSAT-1 imagery has been used for water quality and land use monitoring in and around the Swift Creek and Lake Chesdin Reservoirs in Virginia. This has proved useful by (1) helping determine valid reservoir sampling stations, (2) monitoring areas not accessible by land or water, (3) giving the State a viable means of measuring Secchi depth readings in these inaccessible areas, (4) giving an overview of trends in changing sedimentation loadings over a given time period and classifying these waters into various categories, (5) enabling the State to inventory all major lakes and reservoirs and computing their acreage, (6) monitoring land use changes in any specific area, (7) evaluating possible long-term environmental effects of nearby developments, and (8) monitoring and predicting population shifts with possible impact on water quality problems. The main problems in the long-term use of such imagery appear to be cost and lack of consistency due to cloud cover limitations.
Gigantic photoionization was discovered on GaAs-oxide interfaces leading to the discharge of deep surface states with rates exceeding 1000 times those of photoionization transitions to the conduction band. It exhibits a peak similar to acceptor-donor transitions and is explained as due to energy transfer from photo-excited donor-acceptor pairs to deep surface states. This new process indicates the presence of significant concentrations of shallow donor and acceptor levels not recognized in previous interface models.
The partial and total photoionization cross sections for the S(3s/2/3p/4/ /3/Pe) ground state are calculated in both the dipole length and velocity forms. The prominent features in the cross sections are the autoionization Rydberg series converging to S+(3s/2/p/3/ /2/D/0/, /2/P/0/) excited-state thresholds. The results are pertinent to the study of sulfur in the plasma of Jupiter's satellite Io.
Converged quantum mechanical calculations of scattering matrices and transition probabilities are reported for the reaction of H with H2 with total angular momentum 0, 1, and 4 as functions of total energy in the range 0.85-1.15 eV on an accurate potential energy surface. The resonance structure is illustrated with Argand diagrams. State-to-state reactive collision delay times and lifetimes are presented. For J = 0, 1, and 4, the lowest-energy H3 resonance is at total energies of 0.983, 0.985, and 1.01 eV, respectively, with lifetimes of about 16-17 fs. For J = 1 and 4 there is a higher-energy resonance at 1.10-1.11 eV. For J = 1 the lifetime is about 4 fs and for J = 4 it is about 1 fs.
Using super-Baker-Campbell-Hausdorff relations on the elements of the supergroup OSP(2/2), we derive the supersqueeze operator and the supersqueezed states, which are the supersymmetric generalization of the squeezed states of the harmonic oscillator.
A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.
Provide information regarding state-to-state modeling for nonequilibrium thermochemistry in H2/He entry flows relevant to gas giants/ice giants
Internal and vibrational partition functions of carbon dioxide and rotational line intensities arising from transitions from ground and first excited states
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Iron formations (IFs) are chemical sedimentary rocks that were widely deposited before the Great Oxidation Event (GOE) around 2.4- 2.2 Ga. It is generally thought that IFs precipitated as hydrated Fe 3+ oxides (HFOs) such as ferrihydrite following surface oxidation of Fe 2+ -rich, anoxic deep waters. This model often implicates biological oxidation and underpins reconstructions of marine nutrient concentrations. However, nanoscale petrography indicates that an Fe 2+ silicate, greenalite, is a common primary mineral in well-preserved IFs, motivating an alternative depositional model of anoxic ferrous silicate precipitation. It is unclear, however, if Fe 2+ -rich silicates can produce the Fe isotopic variations in IFs that are well explained by Fe 2+ oxidation. To address this question, we constrain the equilibrium Fe isotopic ( 56 Fe/ 54 Fe) fractionation of greenalite and ferrihydrite by determining the iron phonon densities of states for those minerals. Here, we use ab initio density functional theory (DFT + U) calculations and nuclear resonant inelastic X-ray scattering spectroscopy to show that ferrous greenalite should be isotopically lighter than ferrihydrite by similar to 1-1.2 parts per thousand at equilibrium, and fractionation should scale linearly with increasing Fe 3+ content in greenalite. By anchoring ferrihydrite-greenalite mineral pair fractionations to published experimental Fe isotopic fractionations between HFOs and aqueous Fe 2+ , we show that ferrous greenalite may produce all but the heaviest pre-GOE Fe isotopic compositions and mixed valence greenalites can produce the entire record. Our results suggest that heavy Fe isotope enrichments alone are not diagnostic of primary IF mineralogies, and ferrihydrite and partially oxidized or even purely ferrous greenalite are all viable primary IF mineralogies.
Abstract not provided
This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.
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The project has two primary objectives: (1) down select three-dimensional (3D) printing and post-processing approaches for solid-state electrolyte (SSE) / cathode integration, and (2) understand battery failure mechanisms via ex situ and in situ characterization.
Quantum mechanical potential energy curves for lower excited states of helium 2 and hydrogen 2
Isotherms and isobars for polymer liquids using corresponding states principle to establish function describing dependence of internal pressure on volume or temperature