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At least 613 records · Page 34

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗

Characterization of Adsorption Enthalpy of Novel Water-Stable Zeolites and Metal-Organic Frameworks

Water adsorption is becoming increasingly important for many applications including thermal energy storage, desalination, and water harvesting. To develop such applications, it is essential to understand both adsorbent-adsorbate and adsorbate-adsorbate interactions, and also the energy required for adsorption/desorption processes of porous material-adsorbate systems, such as zeolites and metalorganic frameworks (MOFs). In this study, we present a technique to characterize the enthalpy of adsorption/desorption of zeolites and MOF-801 with water as an adsorbate by conducting desorption experiments with conventional differential scanning calorimetry (DSC) and thermogravimetric analyzer (TGA). With this method, the enthalpies of adsorption of previously uncharacterized adsorbents were estimated as a function of both uptake and temperature. Our characterizations indicate that the adsorption enthalpies of type I zeolites can increase to greater than twice the latent heat whereas adsorption enthalpies of MOF-801 are nearly constant for a wide range of vapor uptakes.

42 ENGINEERING↗

A deep decarbonization framework for the United States economy – a sector, sub-sector, and end-use based approach

Achieving the United States' target of net-zero greenhouse gas emissions by 2050 will require technological transformations and energy sector mitigation. To understand the role of dynamically evolving technologies, identify synergies and dissonance and the effect of allocating limited low-carbon biomass resources in decarbonizing the U.S. economy, we developed the Decarbonization Scenario Analysis Model. A Life Cycle Assessment based approach is implemented considering the U.S. economy as the functional unit, to estimate greenhouse gas mitigation potential for projected energy demand based on several sector-level and cross-sectoral decarbonization pathways. Direct and supply-chain emissions are accounted, resulting from changes in patterns of energy generation and consumption, technology breakthroughs, and reductions in fugitive emissions over time at the granularity of economic sectors, sub-sectors, and end-use. Decarbonization strategies are implemented over a reference case developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020–2050. Based on the considered scenarios, 80–90% economy-wide decarbonization relative to the 2020 reference case is projected. Electrification, low-carbon fuels, and reduction of fugitive emissions play the most significant role to decarbonization. The majority of the remaining emissions are accounted to the supply-chain and end-use emissions from natural gas and diesel fossil-based fuels in heavy duty transportation and heavy industries, highlighting the need for developing low-carbon and carbon-negative alternatives to mitigate those fossil-based carbon emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An accurate measurement of the spectral resolution of the JWST Near Infrared Spectrograph

The spectral resolution (R ≡ λ/Δλ) of spectroscopic data is crucial information for accurate kinematic measurements. In this letter we present a robust measurement of the spectral resolution of the JWST Near Infrared Spectrograph (NIRSpec) in fixed slit (FS) and integral field spectroscopy (IFS) modes. Due to the similarity of the utilized slit dimension in the FS mode to that of the shutters in the multi-object spectroscopy (MOS) mode, our resolution measurements in the FS mode can also be used for the MOS mode in principle. We modeled H and He lines of the planetary nebula SMP LMC 58 using a Gaussian line spread function (LSF) to estimate the wavelength-dependent resolution for multiple disperser and filter combinations. We corrected for the intrinsic width of the planetary nebula’s H and He lines due to its expansion velocity by measuring it from a higher-resolution X-shooter spectrum. We find that NIRSpec’s in-flight spectral resolutions exceed the pre-launch estimates provided in the JWST User Documentation by 11–53% in the FS mode and by 1–24% in the IFS mode across the covered wavelengths. We recover the expected trend that the resolution increases with the wavelength within a configuration. The robust and accurate LSFs presented in this letter will enable high-accuracy kinematic measurements using NIRSpec for applications in cosmology and galaxy evolution.

methods: data analysis↗

An ab initio approach to free-energy reconstruction using logarithmic mean force dynamics

We present an ab initio approach for evaluating a free energy profile along a reaction coordinate by combining logarithmic mean force dynamics (LogMFD) and first-principles molecular dynamics. The mean force, which is the derivative of the free energy with respect to the reaction coordinate, is estimated using density functional theory (DFT) in the present approach, which is expected to provide an accurate free energy profile along the reaction coordinate. We apply this new method, first-principles LogMFD (FP-LogMFD), to a glycine dipeptide molecule and reconstruct one- and two-dimensional free energy profiles in the framework of DFT. The resultant free energy profile is compared with that obtained by the thermodynamic integration method and by the previous LogMFD calculation using an empirical force-field, showing that FP-LogMFD is a promising method to calculate free energy without empirical force-fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites

We present a parametric modeling of the thermoelectric transport coefficients based on a model previously used to interpret experimental measurements on the conductivity, σ, and Seebeck coefficient, S, in highly Boron-doped polycrystalline Si, where a very significant thermoelectric power factor (TPF) enhancement was observed. We have derived analytical formalism for the transport coefficients in the presence of an energy barrier assuming thermionic emission over the barrier for (i) non-degenerate and (ii) degenerate one-band semiconductor. Simple generic parametric equations are found that are in agreement with the exact Boltzmann transport formalism in a wide range of parameters. Moreover, we explore the effect of energy barriers in 1-d composite semiconductors in the presence of two phases: (a) the bulk-like phase and (b) the barrier phase. It is pointed out that significant TPF enhancement can be achieved in the composite structure of two phases with different thermal conductivities. The TPF enhancement is estimated as a function of temperature, the Fermi energy position, the type of scattering, and the barrier height. The derived modeling provides guidance for experiments and device design.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Amino-terminated biphenylthiol self-assembled monolayers as highly reactive molecular templates

Self-assembled monolayers (SAMs) with amino tail groups are of interest due to their ability of coupling further compounds. Such groups can be, in particular, created by electron irradiation of nitro- or nitrile-substituted aromatic SAMs, which provide a basis for chemical nanolithography and the fabrication of functionalized nanomembranes. An estimate of reactivity of the created amino groups requires a reference system of homogeneous, amino-terminated aromatic SAMs, which can also be used as a highly reactive molecular template. Here, we describe the synthesis of 4′-aminobiphenyl-4-thiol (ABPT) and SAMs prepared from this precursor on Au(111). The monolayers were characterized by X-ray photoelectron spectroscopy and near edge X-ray absorption fine structure spectroscopy, which revealed that they are well defined, chemically uniform, densely packed, and highly ordered. To examine the influence of electron irradiation on the reactivity of the terminal amino groups, ABPT SAMs were exposed to low energy (50 eV) electrons up to a dose of 40 mC/cm{sup 2} and, subsequently, immersed in either trifluoroacetic, pentafluoropropionic, or heptafluorobutyric anhydride. Analysing the amount of the attached anhydride species made it possible to determine the percentage of reactive amino groups as well as the effect of steric hindrance upon the coupling reaction. The above results are compared with those obtained for the well-established nitro-substituted biphenylthiol monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing the emission, propagation, and focusing of an intense electron beam

Intense electron beams can be used to study the dynamical response of materials under shocks in order to adjust the models developed for hydrodynamics simulations. We present in this paper a characterization of beams produced in a field emission diode coupled to the generator RKA at CEA/CESTA. Cherenkov emission, produced by the beam interacting in a fused silica disk, was observed by fast optical cameras to estimate beam homogeneity. GEANT4 simulations were performed to estimate the transfer function of the silica target and to optimize the anode foil. First, we chose the best cathode material available among the most common materials used in field emission systems. In addition, we found that by optimization of the anode thickness, we could improve the spatial homogeneity of the beam which is of prime importance for computing the interaction of the beam with materials. Next, we changed the beam fluence by increasing the beam current and by reducing the beam radius. Finally, we studied the propagation and focusing of the electron beam in low pressure gases and observed that we could use self-magnetic field focusing in order to increase beam fluence at the target location. The experimental results are in good agreement with PIC simulations.

43 PARTICLE ACCELERATORS↗

Solvation structures of water in trihexyltetradecylphosphonium-orthoborate ionic liquids

Atomistic molecular dynamics simulations have been performed to investigate effective interactions of isolated water molecules dispersed in trihexyltetradecylphosphonium-orthoborate ionic liquids (ILs). The intrinsic free energy changes in solvating one water molecule from gas phase into bulk IL matrices were estimated as a function of temperature, and thereafter, the calculations of potential of mean force between two dispersed water molecules within different IL matrices were performed using umbrella sampling simulations. The systematic analyses of local ionic microstructures, orientational preferences, probability and spatial distributions of dispersed water molecules around neighboring ionic species indicate their preferential coordinations to central polar segments in orthoborate anions. The effective interactions between two dispersed water molecules are partially or totally screened as their separation distance increases due to interference of ionic species in between. These computational results connect microscopic anionic structures with macroscopically and experimentally observed difficulty in completely removing water from synthesized IL samples and suggest that the introduction of hydrophobic groups to central polar segments and the formation of conjugated ionic structures in orthoborate anions can effectively reduce residual water content in the corresponding IL samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging

The universal tendency in scanning probe microscopy (SPM) over the last two decades is to transition from simple 2D imaging to complex detection and spectroscopic imaging modes. The emergence of complex SPM engines brings forth the challenge of reliable data interpretation, i.e., conversion from detected signals to descriptors specific to tip–surface interactions and subsequently to material’s properties. In this work, we implemented a Bayesian inference approach for the analysis of the image formation mechanisms in band excitation SPM. Compared to the point estimates in classical functional fit approaches, Bayesian inference allows for the incorporation of extant knowledge of materials and probe behavior in the form of corresponding prior distribution and return the information on the material functionality in the form of readily interpretable posterior distributions. We explore the nonlinear mechanical behaviors spatially in a classical ferroelectric material, PbTiO 3 . We observe the non-trivial evolution of the Duffing stiffness term and the nonlinearity of the sample surface, determine spatial clustering of the nonlinear response, and perform a Landau analysis on predicting the nonlinear coefficient, which indicates that ferroelectric behavior can be a cause of the observed results. These observations suggest that the spectrum of anomalous behaviors at the ferroelectric domain walls may be broader than previously believed and can extend to non-conventional mechanical properties in addition to static and microwave conductance.

36 MATERIALS SCIENCE↗

Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients

Wind farm layout optimization (WFLO) studies often aim to maximize the annual energy production (AEP) of a wind farm by choosing an arrangement of turbines that minimizes wake interactions. One way to reduce the cost of WFLO studies is by using more computationally efficient AEP models. The cost of standard AEP modeling approaches, based on the numerical integration of low-fidelity engineering wake models, scales poorly with the number of simulated discrete wind conditions. A second way to reduce cost when using a gradient-based algorithm is to supply exact gradient information instead of finite-difference estimates. However, analytical functions for the derivatives of AEP with respect to turbine positions are not always available in the conventional modeling approach. FLOWERS is a computationally inexpensive, analytical model for wind farm AEP that is specifically developed for WFLO applications. In this paper, we analyze the performance of the FLOWERS AEP model with analytic gradients in a layout optimization study compared with a reference optimization framework across three wind farm case studies. We find that the FLOWERS-based approach reduces computation time by a factor of 50–4000 and improves optimal AEP by about 0.3% with less than half of the variability in AEP across instances with randomized initial conditions. We also find the optimal layouts to be insensitive to model parameter tuning, making FLOWERS-based layout optimization a streamlined, user-friendly approach.

17 WIND ENERGY↗

Transfer learning for analysis of collective and non-collective Thomson scattering spectra

Thomson scattering (TS) diagnostics provide reliable, minimally perturbative measurements of fundamental plasma parameters, such as electron density (⁠n e ) and electron temperature (⁠T e ⁠). Deep neural networks can provide accurate estimates of ⁠n e and T e when conventional fitting algorithms may fail, such as when TS spectra are dominated by noise, or when fast analysis is required for real-time operation. Although deep neural networks typically require large training sets, transfer learning can improve model performance on a target task with limited data by leveraging pre-trained models from related source tasks, where select hidden layers are further trained using target data. We present five architecturally diverse deep neural networks, pre-trained on synthetic TS data and adapted for experimentally measured TS data, to evaluate the efficacy of transfer learning in estimating n e and T e in both the collective and non-collective scattering regimes. We evaluate errors in n e and T e estimates as a function of training set size for models trained with and without transfer learning, and we observe decreases in model error from transfer learning when the training set contains ≲ 200 experimentally measured spectra.

Artificial neural networks↗

Nano- and femtosecond high-repetition-rate multipulse laser irradiation of dehydrated bone tissue: role of accumulated heat and model of cooling

A model is proposed to describe the cooling of a biotissue surface after irradiation by a series of laser pulses. The spatial distribution of heat accumulated by the surface of a hard biotissue irradiated by nano- and femtosecond laser pulses is qualitatively estimated as a function of the pulse repetition rate. The obtained results are compared with the data of experimental irradiation of dry bone with both nanosecond and femtosecond laser pulses. The key contribution of the variation of the biotissue optical characteristics to the dependence of heat, accumulated by its surface, on the repetition rate of nanosecond laser pulses is demonstrated. The mechanism of the pulse repetition rate affecting the residual heat in the biotissue is more complex and requires adequate consideration of the change in its optical and thermophysical parameters. The application of the cooling model allowed substantial confirmation of the key role of the accumulated heat in the process of hard tissue carbonisation around the area of laser impact and the necessity of external cooling in the course of high-repetition-rate multipulse laser processing using both nanosecond and femtosecond pulses. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Physical mechanism of electron bunch generation by an ultrarelativistic-intensity laser pulse passing through a sharp plasma boundary

The physical mechanism of the interaction process of a laser pulse of ultrarelativistic intensity with semi-bounded plasma having a sharp boundary is studied in one-dimensional geometry. It is shown that electron bunches are generated by the laser pulse due to the multiflow motion of plasma electrons with crossing trajectories. An analytical relation that allows an electron bunch charge to be estimated as a function of plasma characteristics and electron trajectory parameters is derived and confirmed by the results of numerical simulations. (paper)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

THE OPTICAL COMPANION TO THE INTERMEDIATE-MASS MILLISECOND PULSAR J1439-5501 IN THE GALACTIC FIELD

We present the identification of the companion star to the intermediate-mass binary pulsar (PSR) J1439-5501 obtained by means of ground-based deep images in the B, V, and I bands, acquired with FORS2 mounted at the European Southern Observatory (ESO)-Very Large Telescope (VLT). The companion is a massive white dwarf (WD) with B = 23.57 {+-} 0.02, V = 23.21 {+-} 0.01, and I = 22.96 {+-} 0.01, located at only {approx}0.''05 from the pulsar radio position. Comparing the WD location in the (B, B-V) and (V, V-I) color-magnitude diagrams with theoretical cooling sequences, we derived a range of plausible combinations of companion masses (1 M{sub Sun} {approx}< M{sub COM} {approx}< 1.3 M{sub Sun }), distances (d {approx}< 1200 pc), radii ({approx}< 7.810{sup -3} R{sub Sun }), and temperatures (T=31350{sup +21500}{sub -7400}). From the PSR mass function and the estimated mass range we also constrained the inclination angle i {approx}> 55 Degree-Sign and the pulsar mass (M{sub PSR} {approx}< 2.2 M{sub Sun }). The comparison between the WD cooling age and the spin-down age suggests that the latter is overestimated by a factor of about 10.

79 ASTRONOMY AND ASTROPHYSICS↗

A non-parametric consistency test of the ΛCDM model with Planck CMB data

Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.

79 ASTRONOMY AND ASTROPHYSICS↗

Beam test measurements of Low Gain Avalanche Detector single pads and arrays for the ATLAS High Granularity Timing Detector

For the high luminosity upgrade of the LHC at CERN, ATLAS is considering the addition of a High Granularity Timing Detector (HGTD) in front of the end cap and forward calorimeters at (z) = 3.5 m and covering the region 2.4 < (Eta) < 4 to help reducing the effect of pile-up. The chosen sensors are arrays of 50 Mu-m thin Low Gain Avalanche Detectors (LGAD). This paper presents results on single LGAD sensors with a surface area of 1.3x1.3 mm2 and arrays with 2x2 pads with a surface area of 2x2 mm2 or 3x3 mm2 each and different implant doses of the p+ multiplication layer. They are obtained from data collected during a beam test campaign in autumn 2016 with a pion beam of 120 GeV energy at the CERN SPS. In addition to several quantities measured inclusively for each pad, the gain, efficiency and time resolution have been estimated as a function of the position of the incident particle inside the pad by using a beam telescope with a position resolution of few Mu-m. Different methods to measure the time resolution are compared, yielding consistent results. The sensors with a surface area of 1.3x1.3 mm 2 have a time resolution of about 40 ps for a gain of 20 and of about 27 ps for a gain of 50 and fulfill the HGTD requirements. Larger sensors have, as expected, a degraded time resolution. All sensors show very good efficiency and time resolution uniformity.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Searching for quasar candidates with periodic variations from the Zwicky Transient Facility: results and implications

ABSTRACT We conduct a systematic search for quasars with periodic variations from the archival photometric data of the Zwicky Transient Facility by cross-matching with the quasar catalogues of the Sloan Digital Sky Survey and Véron-Cetty and Véron. We first select out 184 primitive periodic candidates using the generalized Lomb–Scargle periodogram and autocorrelation function and then estimate their statistical significance of periodicity based on two red-noise models, i.e. damped random walk (DRW) and single power-law (SPL) models. As such, we finally identify 106 (DRW) and 86 (SPL) candidates with the most significant periodic variations out of 143 700 quasars. We further compare DRW and SPL models using Bayes factors, which indicate a relative preference of the SPL model for our primitive sample. We thus adopt the candidates identified with SPL as the final sample and summarize its basic properties. We extend the light curves of the selected candidates by supplying other archival survey data to verify their periodicity. However, only three candidates (with 6–8 cycles of periods) meet the selection criteria. This result clearly implies that, instead of being strictly periodic, the variability must be quasi-periodic or caused by stochastic red-noise. This exerts a challenge to the existing search approaches and calls for developing new effective methods.

Chen, Yong-Jie (ORCID:0000000342807673)↗