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Method has been developed to improve the lower bound of the first excursion probability that can apply to the problem with either constant or time-dependent barriers. The method requires knowledge of the joint density function of the random process at two arbitrary instants.
The reliability of the small-core Lanthanide effective core potentials (ECP) is tested using MF and MF(3), for M=Eu, Gd, Tb, and Yb and the atomic excitation energies for Pr, Nd, Eu, Gd, Tb, Dy, Ho, Er, Tm, and Yb. In some case the ECP and all-electron (AE) results are in good agreement, while in others there are significant difference. The difference are much larger when the segmented basis set is used in conjunction with the ECP than when the atomic natural orbital (ANO) basis set is used. The study of the atoms suggests that problems for lanthanide containing molecules are associated with poor atomic excitation energies in the ECP treatment and even using the ANO basis set does not completely solve the problem. We note that the problem appears to be more severe for density functional approaches than for traditional correlation methods. We suggest that additional studies and new effective core potentials may be required for the Lanthanide atoms.
The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.
The iridium-pincer complex {p-OP( t Bu) 2 -C 6 H 2 -2,6-OP( t Bu) 2 ] 2 }Ir(C 2 H 4 ) ( P [Ir]) has been reported as a stable and active catalyst toward alkane dehydrogenation in homogeneous and supported heterogeneous systems. Dehydrogenation has been shown as a practical method toward functional polyolefins, with dehydrogenated high-density polyethylene (deHDPE) demonstrated as a valuable synthon for upcycling, as orthogonal C-H strategies are key to end-of-life upcycling. The heterogenization of P [Ir] on oxides (SiO 2 , Al 2 O 3 , and TiO 2 ; P [Ir]/E y O x ) yields a mixture of organometallic Ir-fragments whose catalytic nonoxidative dehydrogenation activity is modulated by the binding modes of the active metal on the surface. The binding mode was elucidated by a combination of solid-state NMR and XAFS analyses and supported by DFT calculations. Surface binding through the ligand enables active organoiridium that catalyzes internal olefination of deHDPE up to 1.23 mol % at 200 °C under dynamic vacuum. Alternatively, when the organoiridium is bonded though the metal center (Ir-O SiO ), catalyst activity is negligible. Furthermore, the catalytic activity of P [Ir]/SiO 2 showed comparable reactivity with the homogeneous analogue under the same catalytic conditions, and the heterogenized catalyst can be reused up to three cycles. In conclusion, this work highlights the importance of understanding how organometallic precursors react with hydroxylated metal oxide surfaces to establish structure-property relationships.
The density, viscosity, and electrical conductivity of Hg(0.8)Cd(0.2)Te melt were measured as a function of temperature. A pycnometric method was used to measure the melt density in the temperature range of 1072 to 1122 K. The viscosity and electrical conductivity were determined using a transient torque method from 1068 to 1132 K. The density result from this study is within 0.3% of the published data. However, the current viscosity result is approximately 30% lower than the existing data. The electrical conductivity of Hg(0.8)Cd(0.2)Te melt as a function of temperature, which is not available in the literature, is also determined. The analysis of the temperature dependent electrical conductivity and the relationship between the kinematic viscosity and density indicated that the structure of the melt appeared to be homogeneous when the temperature was above 1090 K. A structural transition occurred in the Hg(0.8)Cd(0.2)Te melt as the temperature was decreased to below 1090 K
Various methods of inverting solar Mg I 4571 and 5173 spectral line observations are examined to find the best method of using these lines to calculate the vertical temperature and electron density structure around the temperature minimum region. Following a perturbation analysis by Mein (1971), a Fredholm integral equation of the first kind is obtained which can be inverted to yield these temperature and density structures as a function of time. Several inversion methods are tested and compared. The methods are used to test data as well as to a subset of observations of these absorption lines taken on February 3, 1986 before and during a solar flare. A small but significant increase is found in the temperature and a relatively large increase in the electron density during this flare. The observations are inconsistent with heating and ionization by an intense beam of electrons and with ionization by UV photoionization of Si I.
Contents of this DOI are data for the research paper "Constraints on magnetism and correlations in RuO2 from lattice dynamics and Mossbauer spectroscopy" by the authors: George Yumnam, et. al. The dataset contains data from inelastic x-ray scattering measurements of RuO2 single crystals performed at the Advanced Photon Source in Argonne National Lab. This dataset also contains data from inelastic neutron scattering experiments of RuO2 powder performed at the ARCS spectrometer at Spallation Neutron Source at ORNL. Supporting theoretical calculations based on density functional theory with r2SCAN and DFT+U methods is also included in this dataset. Please see the README.txt files for more information of the dataset and file contents. For comments and questions, please contact: George Yumnam (yumnamg@ornl.gov) and/or Raphael P Hermann (hermannrp@ornl.gov)
Proton- γ coincidences from ( d , p ) reactions between a Ni 66 beam and a deuterated polyethylene target have been analyzed with the inverse-Oslo method to find the nuclear level density (NLD) and γ -ray strength function ( γ SF ) of Ni 67 . The Ni 66 ( n , γ ) capture cross section has been calculated using the Hauser-Feshbach model in using the measured NLD and γ SF as constraints. The results confirm that the Ni 66 ( n , γ ) reaction acts as a bottleneck when relying on one-zone nucleosynthesis calculations. However, the impact of this reaction is strongly dampened in multizone models of low-metallicity AGB stars experiencing i -process nucleosynthesis. Published by the American Physical Society 2025
Probabilistic finite element method (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties, and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.
Probabilistic methods, synthesizing the power of finite element methods with second-order perturbation techniques, are formulated for linear and nonlinear problems. Random material, geometric properties and loads can be incorporated in these methods, in terms of their fundamental statistics. By construction, these methods are applicable when the scale of randomness is not too large and when the probabilistic density functions have decaying tails. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. Applications showing the effects of combined random fields and cyclic loading/stress reversal are studied and compared with Monte Carlo simulation results.
Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.
An analytic solution for the critical, monoenergetic, bare, infinite cylinder is presented. The solution is obtained by modifying a previous development based on a neutron density transform and Case's singular eigenfunction method. Numerical results for critical radii and the neutron density as a function of position are included and compared with the results of other methods.
Orbital relaxation of the core region is a primary source of error in the computation of core ionization and core excitation energies. Recently, Transition-Potential Coupled Cluster (TP-CC) methods have been used to explicitly treat orbital relaxation using non-variational molecular orbitals determined by reoccupation of orbitals optimized for a fractional core occupation. The amount of fractional occupation is governed by parameter λ, and recommended values for accurate TP-CCSD and XTP-CCSD computations of carbon, nitrogen, oxygen, and fluorine K edges were previously determined. Herein, we explore the performance of several density functionals for generating the fractionally occupied orbitals used in TP-CCSD. These functionals include HF, BP86, BH&HLYP, B3LYP, M06-2X, and ωB97m-V. The fractionally occupied orbitals computed across the various functionals were subsequently employed as the initial orbitals for our TP-CCSD calculations of organic K-edge x-ray absorption and photoelectron spectra. Regardless of the functional used to generate the fractionally occupied orbitals, the TP-CCSD calculations yield accurate and comparable core ionization energies, core excitation energies, and oscillator strengths.
Quantum algorithms are touted as a way around some classically intractable problems such as the simulation of quantum mechanics. At the end of all quantum algorithms is a quantum measurement whereby classical data is extracted and utilized. In fact, many of the modern hybrid-classical approaches are essentially quantum measurements of states with short quantum circuit descriptions. Here, we compare and examine three methods of extracting the time-dependent one-particle probability density from a quantum simulation: direct Z -measurement, Bayesian phase estimation, and harmonic inversion. We have tested these methods in the context of the potential inversion problem of time-dependent density functional theory. Our test results suggest that direct measurement is the preferable method. We also highlight areas where the other two methods may be useful and report on tests using Rigetti's quantum virtual device. This study provides a starting point for imminent applications of quantum computing.
The Cholesky decomposition technique is commonly used to reduce the memory requirement for storing two-particle repulsion integrals in quantum chemistry calculations that use atomic orbital bases. However, when quantum methods use multicomponent bases, such as nuclear–electronic orbitals, additional challenges are introduced due to asymmetric two-particle integrals. This work proposes several multicomponent Cholesky decomposition methods for calculations using nuclear–electronic orbital density functional theory. To analyze the errors in different Cholesky decomposition components, benchmark calculations using water clusters are carried out. The largest benchmark calculation is a water cluster (H 2 O) 27 where all 54 protons are treated quantum mechanically. Furthermore, this study provides energetic and complexity analyses to demonstrate the accuracy and performance of the proposed multicomponent Cholesky decomposition method.
Current wind turbine design methods require tens of thousands of time-domain simulations and use different random seeds to account for the stochasticity of the environmental conditions. The account of stochasticity is nonintrusive because the sampling method calls a deterministic model multiple times without changing its underlying equations. In this work, we investigate and demonstrate using simple proof of concepts how intrusive approaches can be used to directly account for stochasticity in the equations representing a mechanical system. Our long term goal is to apply such methodology to the design of wind turbines without requiring an excessive number of simulations. Intrusive methods manipulate stochastic variables directly to provide the probability density functions (PDFs) of the states and outputs at any time as functions of the PDFs of the inputs. We illustrate how different methods can be used with a reduced-order model of a wind turbine with one degree of freedom and for linear and nonlinear models. We discuss how the methods can be extended and what it will take to apply them to a level of fidelity similar to current state-of-the-art wind turbine design tools.
The density, viscosity, and electrical conductivity of Hg(sub 0.8)Cd(sub 0.2)Te melt were measures as a function of temperature. A pycnometric method was used to measure the melt density in the temperature range of 1072 to 1122 K. The viscosity and electrical conductivity were determined using a transient torque method from 1068 to 1132 K. The density result from this study is within 0.3% of the published data. However, the current viscosity result is approximately 30% lower than the existing data. The electrical conductivity of Hg(sub 0.8)Cd(sub 0.2)Te melt as a function of temperature, which is not available in the literature, is also determined. The analysis of the temperature dependent electrical conductivity and the relationship between the kinematic viscosity and density indicated that the structure of the melt appeared to be homogeneous when the temperature was above 1090 K. A structural transition occurred in the Hg(sub 0.8)Cd(sub 0.2)Te melt as the temperature was decreased to below 1090 K.
Thermophysical properties, namely, density, viscosity, and electrical conductivity of Hg(sub o.8)Cd(sub 0.2)Te melt were measured as a function of temperature. A pycnometric method was used to measure the melt density in the temperature range of 1072 to 1122 K. The viscosity and electrical conductivity were simultaneously determined using a transient torque method from 1068 to 1132 K. The density result from this study is within 0.3% of the published data. However, the current viscosity result is approximately 30% lower than the existing data. The electrical conductivity of Hg(sub o.8)Cd(sub 0.2)Te melt as a function of temperature, which is not available in the literature, is also determined. The analysis of the temperature dependent electrical conductivity and the relationship between the kinematic viscosity and density indicated that the structure of the melt appeared to be homogeneous when the temperature was above 1090 K. A structural transition occurred in the Hg(sub 0.8)Cd(0.2)Te melt as the temperature was decreased from 1090 K to the liquidus temperature.