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At least 1,351 records · Page 75

Inclusive and multiplicity dependent production of electrons from heavy-flavour hadron decays in pp and p-Pb collisions

Measurements of the production of electrons from heavy-flavour hadron decays in pp collisions at $\sqrt{s}$ = 13 TeV at midrapidity with the ALICE detector are presented down to a transverse momentum (p T ) of 0.2 GeV/c and up to p T = 35 GeV/c, which is the largest momentum range probed for inclusive electron measurements in ALICE. In p-Pb collisions, the production cross section and the nuclear modification factor of electrons from heavy-flavour hadron decays are measured in the p T range 0.5 < p T < 26 GeV/c at $\sqrt{s_{NN}}$= 8.16 TeV. The nuclear modification factor is found to be consistent with unity within the statistical and systematic uncertainties. In both collision systems, first measurements of the yields of electrons from heavy-flavour hadron decays in different multiplicity intervals normalised to the multiplicity-integrated yield (self-normalised yield) at midrapidity are reported as a function of the self-normalised charged-particle multiplicity estimated at midrapidity. The self-normalised yields in pp and p-Pb collisions grow faster than linear with the self-normalised multiplicity. A strong p T dependence is observed in pp collisions, where the yield of high-p T electrons increases faster as a function of multiplicity than the one of low-p T electrons. The measurement in p-Pb collisions shows no p T dependence within uncertainties. The self-normalised yields in pp and p-Pb collisions are compared with measurements of other heavy-flavour, light-flavour, and strange particles, and with Monte Carlo simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simple self-consistent method for excited states in density functional theory to characterize defect-derived behavior in wide-band-gap-based microelectronic materials

This final report summarizes the results of the Laboratory Direct Research and Development (LDRD) Project Number 229740. Wide band gap semiconductors such as gallium nitride (GaN) have features highly desirable for multiple mission electronic applications. Realization of their potential requires atomic-scale understanding of electronic behavior. The principal experimental tools for electronically probing defects in GaN are chemically undifferentiating and lack a practical theoretical counterpart needed to identify and characterize specific defects. This project investigated whether a simple idea for modeling defect excited states and their associated photoluminescence (PL) energies is viable, as a path to accelerate the understanding of defect behavior and gain valuable insights into engineering new electronic materials and devices. The research implemented a non-self-consistent total-energy evaluation of a Koopmans-type estimation of an excited electronic state energy in density functional theory (DFT) calculations, and proceeded to design, implement, and assess a self-consistent method for computing excited states based upon an OCcupation-Constrained-DFT (occ-DFT). The occ-DFT was verified in test calculations of defect excited states and validated against well-characterized PL data for 3d transition metal defects in GaN. The method proved stable and robust in computing excited states and gave accurate predictions compared to experimental PL data. The combined ground state/excited-state capability proved capable of chemically differentiating defect species in GaN. In application to 3d dopants in GaN, we reinterpreted extensive experimental literature, proposed new defects as prospective candidates for use in quantum information applications, and outlined design strategies to create and exploit these potentially useful functional defects in GaN.

36 MATERIALS SCIENCE↗

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic changes in connexin expression following engraftment of neural stem cells to striatal tissue

Gap-junctional intercellular communication between grafted neural stem cells (NSCs) and host cells seem to be essential for many of the beneficial effects associated with NSC engraftment. Utilizing murine NSCs (mNSCs) grafted into an organotypic ex vivo model system for striatal tissue we examined the prerequisites for formation of gap-junctional couplings between graft and host cells at different time points following implantation. We utilized flow cytometry (to quantify the proportion of connexin (Cx) 26 and 43 expressing cells), immunohistochemistry (for localization of the gap-junctional proteins in graft and host cells), dye-transfer studies with and without pharmacological gap-junctional blockers (assaying the functionality of the formed gap-junctional couplings), and proliferation assays (to estimate the role of gap junctions for NSC well-being) to this end. Immunohistochemical staining and dye-transfer studies revealed that the NSCs already form functional gap junctions prior to engraftment, thereby creating a substrate for subsequent graft and host communication. The expression of Cx43 by grafted NSCs was decreased by neurotrophin-3 overexpression in NSCs and culturing of grafted tissue in serum-free Neurobasal B27 medium. Cx43 expression in NSC-derived cells also changed significantly following engraftment. In host cells the expression of Cx43 peaked following traumatic stimulation and then declined within two weeks, suggesting a window of opportunity for successful host cell rescue by NSC engraftment. Further investigation of the dynamic changes in gap junction expression in graft and host cells and the associated variations in intercellular communication between implanted and endogenous cells might help to understand and control the early positive and negative effects evident following neural stem cell transplantation and thereby optimize the outcome of future clinical NSC transplantation therapies.

60 APPLIED LIFE SCIENCES↗

Impact of acute temperature and air pollution exposures on adult lung function: A panel study of asthmatics

Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM 2.5 ) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV 1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM 2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM 2.5 , DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM 2.5 , but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM 2.5 , had a significant association with FEV 1 . When DBGT and PM 2.5 exposures were placed in the same model, the strongest association between cumulative PM 2.5 exposures and the use of rescue bronchodilator was identified at the 0–24 hours (OR = 1.030; 95% CI = 1.012–1.049; p-value = 0.001) and 0–48 hours (OR = 1.030; 95% CI = 1.013–1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0–6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV 1 . No significant interactions between DBGT and PM 2.5 were observed for rescue bronchodilator use or FEV 1 . Conclusions Short-term increases in PM 2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV 1 ). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM 2.5 and DBGT on lung function in asthmatics.

60 APPLIED LIFE SCIENCES↗

Binding Affinity Prediction by Pairwise Function Based on Neural Network

In this paper, we present a new approach to estimate the binding affinity from given three-dimensional poses of protein–ligand complexes. In this scheme, every protein–ligand atom pair makes an additive free-energy contribution. The sum of these pairwise contributions then gives the total binding free energy or the logarithm of the dissociation constant. The pairwise contribution is calculated by a function implemented via a neural network that takes the properties of the two atoms and their distance as input. The pairwise function is trained using a portion of the PDBbind 2018 data set. The model achieves good accuracy for affinity predictions when evaluated with PDBbind 2018 and with the CASF-2016 benchmark, comparing favorably to many scoring functions such as that of AutoDock Vina. The framework here may be extended to incorporate other factors to further improve its accuracy and power.

59 BASIC BIOLOGICAL SCIENCES↗

Isolated Photosystem I Reaction Centers on a Functionalized Gated High Electron Mobility Transistor

In oxygenic plants, photons are captured with high quantum efficiency by two specialized reaction centers (RC) called Photosystem I (PS I) and Photosystem II (PS II). The captured photon triggers rapid charge separation and the photon energy is converted into an electrostatic potential across the nanometer-scale nm reaction centers. The exogenous photovoltages from a single PS I RC have been previously measured using the technique of Kelvin force probe microscopy (KFM). However, biomolecular photovoltaic applications require two-terminal devices. This paper presents for the first time, a micro-device for detection and characterization of isolated PS I RCs. The device is based on an AlGaN/GaN high electron mobility transistor (HEMT) structure. AlGaN/GaN HEMTs show high current throughputs and greater sensitivity to surface charges compared to other field-effect devices. PS I complexes immobilized on the floating gate of AlGaN/GaN HEMTs resulted in significant changes in the device characteristics under illumination. An analytical model has been developed to estimate the RCs of a major orientation on the functionalized gate surface of the HEMTs.

Eliza, Sazia A.↗

Inadequacy of current approaches for characterizing membrane transport properties at high salinities

Cost optimal design of osmotic membrane processes requires an accurate estimate of membrane transport parameters across their full operational range. However, standard approaches for estimating these parameters rely on empirical methods, the accuracy of which remains unquantified as a function of temperature, salinity, and measurement error. Herein, we present a systematic accuracy analysis of previously developed methods for estimation of membrane transport properties in reverse osmosis, high-pressure reverse osmosis, forward osmosis, pressure retarded reverse osmosis, and osmotically assisted reverse osmosis. We use a Monte Carlo approach to sample the full range of feasible membrane water permeabilities, salt permeabilities, structural parameters, and operating conditions for these processes. These material and process parameters are then incorporated into a physical transport model for each process. Our analysis shows that the statistical uncertainty of current empirical methods for estimating membrane parameters increases by 5 times from low-salinity to high-salinity conditions. Here, the result of this work demonstrates that empirical methods are inadequate for precisely estimating membrane transport properties at high salinity and highlight a critical need for the development of statistically validated higher accuracy methods.

42 ENGINEERING↗

Experimental and Theoretical Study of Azimuth Angle and Polarization Dependences of Sum-Frequency-Generation Vibrational Spectral Features of Uniaxially Aligned Cellulose Crystals

Comprehensive interpretation of vibrational sum-frequency-generation (SFG) spectroscopic features of SFG-active nanodomains interspersed in amorphous bulk requires the knowledge of nonlinear susceptibility, χ ijk (2) , of the SFG-active phase as a function of its spatial arrangement in the bulk as well as the polarizations of the probe lights. Our work reports the full analysis of the azimuth angle and polarization dependence of SFG signals from a control sample consisting of uniaxially aligned cellulose Iβ crystals. The χ ijk (2) terms of cellulose were estimated from quantum mechanics calculations using time-dependent density functional theory (TD-DFT), and a simple structural model was built with truncated glucose dimers. The theoretical azimuth angle and polarization dependences of characteristic CH/CH 2 and OH stretch modes of cellulose were compared with the experimentally observed trends. These comparisons revealed that the relative polarity of crystallites within the SFG coherence length, the random quasi phase-matching of polycrystalline domains, and the preferential packing of crystallites in the bulk play important roles governing the spectral features. Compared to that of small molecules, the difference between chiral and achiral responses in SFG spectra is more difficult to confirm because of the inhomogeneous distribution of crystallites in the bulk sample.

59 BASIC BIOLOGICAL SCIENCES↗

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Effective Field Theory of Large Scale Structures at two loops

Here, large scale structure surveys promise to be the next leading probe of cosmological information. It is therefore crucial to reliably predict their observables. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a manifestly convergent perturbation theory for the weakly non-linear regime of dark matter, where correlation functions are computed in an expansion of the wavenumber k of a mode over the wavenumber associated with the non-linear scale k NL . Since most of the information is contained at high wavenumbers, it is necessary to compute higher order corrections to correlation functions. After the one-loop correction to the matter power spectrum, we estimate that the next leading one is the two-loop contribution, which we compute here. At this order in k/k NL , there is only one counterterm in the EFTofLSS that must be included, though this term contributes both at tree-level and in several one-loop diagrams. We also discuss correlation functions involving the velocity and momentum fields. We find that the EFTofLSS prediction at two loops matches to percent accuracy the non-linear matter power spectrum at redshift zero up to k~ 0.6 h Mpc –1 , requiring just one unknown coefficient that needs to be fit to observations. Given that Standard Perturbation Theory stops converging at redshift zero at k~ 0.1 h Mpc –1 , our results demonstrate the possibility of accessing a factor of order 200 more dark matter quasi-linear modes than naively expected. If the remaining observational challenges to accessing these modes can be addressed with similar success, our results show that there is tremendous potential for large scale structure surveys to explore the primordial universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Global leaf trait estimates biased due to plasticity in the shade

The study of leaf functional trait relationships, the so-called leaf economics spectrum , is based on the assumption of high-light conditions (as experienced by sunlit leaves). Owing to the exponential decrease of light availability through canopies, however, the vast majority of the world's vegetation exists in at least partial shade. Plant functional traits vary in direct dependence of light availability, with different traits varying to different degrees, sometimes in conflict with expectations from the economic spectrum. This means that the derived trait relationships of the global leaf economic spectrum are probably dependent on the extent to which observed data in existing large-scale plant databases represent high-light conditions. Here, using an extensive worldwide database of within-canopy gradients of key physiological, structural and chemical traits, along with three different global trait databases we show that: (1) accounting for light-driven trait plasticity can reveal novel trait relationships, particularly for highly plastic traits (for example, the relationship between net assimilation rate per area (A a ) and leaf mass per area (LMA)); and (2) a large proportion of leaf traits in current global plant databases reported as measured in full sun were probably measured in the shade. Our results show that even though the majority of leaves exist in the shade, along with a large proportion of observations, our current understanding is too focused on conditions in the sun.

59 BASIC BIOLOGICAL SCIENCES↗

Localized Active Space Pair-Density Functional Theory

Accurate quantum chemical methods for the prediction of spin-state energy gaps for strongly correlated systems are computationally expensive and scale poorly with the size of the system. This makes calculations for many experimentally interesting molecules impractical even with abundant computational resources. Previous work has shown that the localized active space (LAS) self-consistent field (SCF) method can be an efficient way to obtain multiconfiguration SCF wave functions of comparable quality to the corresponding complete active space (CAS) ones. To obtain quantitative results, a post-SCF method is needed to estimate the complete correlation energy. One such method is multiconfiguration pair-density functional theory (PDFT), which calculates the energy based on the density and on-top pair density obtained from a multiconfiguration wave function. In this work, we introduce localized-active-space PDFT, which uses a LAS wave function for subsequent PDFT calculations. The method is tested by computing spin-state energies and gaps in conjugated organic molecules and a bimetallic compound and comparing to the corresponding CAS-PDFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phylogenomics databases for facilitating functional genomics in rice

The completion of whole genome sequence of rice (Oryza sativa) has significantly accelerated functional genomics studies. Prior to the release of the sequence, only a few genes were assigned a function each year. Since sequencing was completed in 2005, the rate has exponentially increased. As of 2014, 1,021 genes have been described and added to the collection at The Overview of functionally characterized Genes in Rice online database (OGRO). Despite this progress, that number is still very low compared with the total number of genes estimated in the rice genome. One limitation to progress is the presence of functional redundancy among members of the same rice gene family, which covers 51.6 % of all non-transposable element-encoding genes. There remain a significant portion or rice genes that are not functionally redundant, as reflected in the recovery of loss-of-function mutants. To more accurately analyze functional redundancy in the rice genome, we have developed a phylogenomics databases for six large gene families in rice, including those for glycosyltransferases, glycoside hydrolases, kinases, transcription factors, transporters, and cytochrome P450 monooxygenases. In this review, we introduce key features and applications of these databases. We expect that they will serve as a very useful guide in the post-genomics era of research.

54 ENVIRONMENTAL SCIENCES↗

Estimate of Undulator Magnet Damage Due to Beam Finder Wire Measurements

Beam Finder Wire (BFW) devices will be installed at each break in the Undulator magnet line. These devices will scan small wires across the beam causing some electrons to lose energy through bremsstrahlung. The degraded electrons are subsequently detected downstream of a set of vertical dipole magnets after they pass through the vacuum chamber. This signal can then be used to accurately determine the beam position with respect to the BFW wire. The choice of the wire diameter, scan speed, and operating parameters, depends on the trade-off between the signal size and the radiation damage to the undulator magnets. In this note I estimate the rate of undulator magnet damage that results from scanning as a function of, wire size, scan speed, and average beam current. A separate analysis of the signal size was carried out by Wu. The damage estimate is primarily based on two sources: the first, Fasso, is used to estimate the amount of radiation generated and then absorbed by the magnets; the second, Alderman et. al., is used to estimate the amount of damage the magnet undergoes as a result of the absorbed radiation. Fasso performed a detailed calculation of the radiation, including neutron fluence, that results from a the electron beam passing through a 100 micron diamond foil inserted just in front of the undulator line. Fasso discussed the signficance of various types of radiation and stated that photoneutrons probably play a major role. The estimate in this paper assumes the neutron fluence is the only significant cause of radiation-induced demagnetization. The specific results I use from Fasso's paper are reproduced here in Figure 1, which shows the radial distribution of the integrated neutron fluence per day in the undulator magnets, and Figure 2, which shows the absorbed radiation dose all along the undulator line. In the longitudinal dimension, Fasso's calculation, (see Figure 2), shows that the radiation dose is widely distributed all along the undulator line, but is highest around 70 m from the front of the undulator line where the foil is. At the 70 m point, for the purpose of calculating the demagnetization, I chose a conservative estimate for the effective neutron flux of 1.0 x 10{sup 13} n/cm{sup 2}/day. As can be seen in Figure 1, this choice is representative of the flux nearest the beam where it is the highest. A less conservative estimate, but perhaps more accurate, estimate of the effective flux, would be the average flux in the magnet block, which is roughly one half as much.

43 PARTICLE ACCELERATORS↗

Fourier band-power E/B-mode estimators for cosmic shear

We introduce new Fourier band-power estimators for cosmic shear data analysis and E/B-mode separation. We consider both the case where one performs E/B-mode separation and the case where one does not. The resulting estimators have several nice properties which make them ideal for cosmic shear data analysis. First, they can be written as linear combinations of the binned cosmic shear correlation functions. Secondly, they account for the survey window function in real-space. Thirdly, they are unbiased by shape noise since they do not use correlation function data at zero separation. Fourthly, the band-power window functions in Fourier space are compact and largely non-oscillatory. Fifthly, they can be used to construct band-power estimators with very efficient data compression properties. In particular, we find that all of the information on the parameters Ωm, σ8 and ns in the shear correlation functions in the range of ~10–400 arcmin for single tomographic bin can be compressed into only three band-power estimates. Finally, we can achieve these rates of data compression while excluding small-scale information where the modelling of the shear correlation functions and power spectra is very difficult. Given these desirable properties, these estimators will be very useful for cosmic shear data analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Estimation of reactive fluxes in gradient stochastic systems using an analogy with electric circuits

Highlights: •The MaxFlux functional should be called the resistivity functional. •A Hamilton–Jacobi approach for computing transition paths in collective variables. •Conversion of the network of reactive channels into an electric circuit. •Test on the Alanine-Dipeptide. Perfect agreement. •Application to the problem of CO escape from Myoglobin. -- Abstract: We propose an approach for finding dominant reactive channels and calculating percentages of reactive flux through each channel in chemical systems driven by a deterministic potential force and a small thermal noise. We assume that the temperature is low enough so that the reactive flux focuses around a finite number of paths connecting the reactant and the product states. These paths can be found in a systematic way by solving a Hamilton–Jacobi equation for the so called MaxFlux functional. We argue that the name “MaxFlux” is misleading: it should be called the resistivity functional instead. Once the network of transition paths is found, one can define an equivalent electric circuit and find the currents through each of its wires. These currents give estimates of the reactive flux along the corresponding transition paths. We test our approach on the problem of finding transition paths in the Alanine-Dipeptide with two dihedral angles where the reactive current can be computed exactly. The percentages of the reactive flux through each reactive channel given by our approach turn out to be in remarkable agreement with the exact ones. We apply this approach to the problem of finding escape paths of a CO molecule from a Myoglobin protein. We find a collection of exit locations and establish percentages of the reactive flux through each of them.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accuracy of first-principles interatomic interactions and predictions of ferroelectric phase transitions in perovskite oxides: Energy functional and effective Hamiltonian

While first-principles density functional theory (DFT)-based models have been effective in capturing the physics of ferroelectric phase transitions in BaTiO 3 , PbTiO 3 , and KNbO 3 , quantitative estimates of the transition temperatures (T C ) have errors that are believed to originate from the errors in estimating lattice constants obtained within the local density approximation (LDA) and generalized gradient approximation (GGA) of DFT. The recently developed strongly constrained and appropriately normed (SCAN) meta-GGA functional has been shown to be quite accurate in the estimation of lattice constants. Here, we present a quantitative analysis of the estimates of ferroelectric ground-state properties of eight perovskite oxides and transition temperatures of BaTiO 3 , PbTiO 3 , and KNbO 3 obtained with molecular dynamics simulations using an effective Hamiltonian derived from the SCAN meta-GGA-based DFT. Relative to LDA, we find an improvement in the estimates of T C , which arises from the changes in the calculated strain-phonon, anharmonic coupling constants, and strength of ferroelectric instabilities, i.e., frequencies of the soft modes. We also assess the errors in T C originating from approximately integrating out the high-energy phonons during construction of the model Hamiltonian through estimates of the effects of fourth-order couplings between the soft mode and higher-energy modes of BaTiO 3 , PbTiO 3 , and KNbO 3 . We find that inclusion of these anharmonic couplings results in deeper double-well energy functions of ferroelectric distortions and further improvement in the estimates of transition temperatures. Consistently improved estimates of lattice constants and transition temperatures with the SCAN meta-GGA calculations augur well for their use in simulations of superlattices or heterostructures of perovskite oxides, in which the effects of lattice matching are critical.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗