Search

Abstract Density functional theory is the workhorse of materials simulations. Unfortunately, the quality of results often varies depending on the specific choice of the exchange-correlation functional, which significantly limits the predictive power of this approach. Coupled cluster theory, including single, double, and perturbative triple particle-hole excitation operators, is widely considered the ‘gold standard' of quantum chemistry as it can achieve chemical accuracy for non-strongly correlated applications. Because of the high computational cost, the application of coupled cluster theory in materials simulations is rare, and this is particularly true if finite-temperature properties are of interest for which molecular dynamics simulations have to be performed. By combining recent progress in machine learning models with low data requirements for energy surfaces and in the implementation of coupled cluster theory for periodic materials, we show that chemically accurate simulations of materials are practical and could soon become significantly widespread. As an example of this numerical approach, we consider the calculation of the enthalpy of adsorption of CO2 in a porous material.

We present a robust strategy to numerically sample the Coulomb potential in reciprocal space for periodic Born–von Karman cells of general shape. Our approach tackles two common issues of plane-wave based implementations of Coulomb integrals under periodic boundary conditions: the treatment of the singularity at the Brillouin-zone center and discretization errors, which can cause severe convergence problems in anisotropic cells, necessary for the calculation of low-dimensional systems. We apply our strategy to the Hartree–Fock and coupled cluster (CC) theories and discuss the consequences of different sampling strategies on different theories. We show that sampling the Coulomb potential via the widely used probe-charge Ewald method is unsuitable for CC calculations in anisotropic cells. To demonstrate the applicability of our developed approach, we study two representative, low-dimensional use cases: the infinite carbon chain, for which we report the first periodic CCSD(T) potential energy surface, and a surface slab of lithium hydride, for which we demonstrate the impact of different sampling strategies for calculating surface energies. We find that our Coulomb sampling strategy serves as a vital solution, addressing the critical need for improved accuracy in plane-wave based CC calculations for low-dimensional systems. [ABSTRACT FROM AUTHOR]

We implement the phaseless auxiliary field quantum Monte Carlo method using the plane-wave based projector augmented wave method and explore the accuracy and the feasibility of applying our implementation to solids. We use a singular value decomposition to compress the two-body Hamiltonian and, thus, reduce the computational cost. Consistent correlation energies from the primitive-cell sampling and the corresponding supercell calculations numerically verify our implementation. We calculate the equation of state for diamond and the correlation energies for a range of prototypical solid materials. A down-sampling technique along with natural orbitals accelerates the convergence with respect to the number of orbitals and crystal momentum points. We illustrate the competitiveness of our implementation in accuracy and computational cost for dense crystal momentum point meshes compared to a well-established quantum-chemistry approach, the coupled-cluster ansatz including singles, doubles, and perturbative triple particle–hole excitation operators. [ABSTRACT FROM AUTHOR]

Since the advent of smartphones, work tasks shift progressively towards mobile phones. The main hurdle of this progression is the substantially slower input speed of smartphones in comparison with physical keyboards. This input speed could be improved by using keyboard layouts optimized for use with smartphones. As these keyboard layouts are not commonly used, switching to them results in a poor novice experience with an initially decreased text input speed. Previous investigations confirmed that this poor novice experience can be attenuated by using visual clues accentuating the most probable keys. This gives rise to the question of which visual impression leads to the best performance improvement. Therefore, this article evaluates the performance of six visual clues with different visual impressions via a user study conducted with 28 participants. The results showed that the visual clue with a pop-up animation and the visual clue with an increased font size performed the best with a 4% and 3%, respectively, typing performance improvement. Nonetheless, the questionnaire and personal preferences part of the user study showed that a 4% performance gain is not enough to crown one individual visual clue as the best visual clue to be used with every individual. This leads to the conclusion that functionality to choose one personal preference is more important than focusing on one specific best clue.

Lipoprotein(a) [Lp(a)] concentrations are regulated by the LPA gene mainly via the large kringle IV-type 2 (KIV-2) copy number variation and multiple causal variants. Early studies suggested an effect of long pentanucleotide repeat (PNR) alleles (10 and 11 repeats, PNR10 and PNR11) in the LPA promoter on gene transcription and found an association with lower Lp(a). Subsequent in vitro studies showed no effects on mRNA transcription, but the association with strongly decreased Lp(a) remained consistent. We investigated the isolated and combined effect of PNR10, PNR11, and the frequent splice site variant KIV-2 4925G>A on Lp(a) concentrations in the Cooperative Health Research in the Region of Augsburg F4 study by multiple quantile regression in single-SNP and joint models. Data on Lp(a), apolipoprotein(a) Western blot isoforms, and variant genotypes were available for 2,858 individuals. We found a considerable linkage disequilibrium between KIV-2 4925G>A and the alleles PNR10 and PNR11. In single-variant analysis adjusted for age, sex, and the shorter apo(a) isoform, we determined that both PNR alleles were associated with a highly significant Lp(a) decrease (PNR10: β = −14.43 mg/dl, 95% CI: −15.84, −13.02, P = 3.33e-84; PNR11: β = −17.21 mg/dl, 95% CI: −20.19, −14.23, P = 4.01e-29). However, a joint model, adjusting the PNR alleles additionally for 4925G>A, abolished the effect on Lp(a) (PNR10: β = +0.44 mg/dl, 95% CI: −1.73, 2.60, P = 0.69; PNR11: β = −1.52 mg/dl, 95% CI: −6.05, 3.00, P = 0.51). Collectively, we conclude that the previously reported Lp(a) decrease observed in pentanucleotide alleles PNR10 or PNR11 carriers results from a linkage disequilibrium with the frequent splicing mutation KIV-2 4925G>A.

Here, the authors characterize the spectroscopic and transport properties of heterojunctions composed of quasi-metallic and semiconducting graphene nanoribbons (GNRs) with different widths, showing a predominant quantum tunnelling mechanism. The GNR heterojunctions can also be used to realize adsorbate sensors with high sensitivity.

We investigate the reliability of two cost-effective coupled-cluster methods for computing spin-state energetics and spin-related properties of a set of open-shell transition-metal complexes. Specifically, we employ the second-order approximate coupled-cluster singles and doubles (CC2) method and projection-based embedding that combines equation-of-motion coupled-cluster singles and doubles (EOM-CCSD) with density functional theory (DFT). The performance of CC2 and EOM-CCSD-in-DFT is assessed against EOM-CCSD. The chosen test set includes two hexaaqua transition-metal complexes containing Fe(II) and Fe(III), and a large Co(II)-based single-molecule magnet with a non-aufbau ground state. We find that CC2 describes the excited states more accurately, reproducing EOM-CCSD excitation energies within 0.05 eV. However, EOM-CCSD-in-DFT excels in describing transition orbital angular momenta and spin–orbit couplings. Moreover, for the Co(II) molecular magnet, using EOM-CCSD-in-DFT eigenstates and spin–orbit couplings, we compute spin-reversal energy barriers, as well as temperature-dependent and field-dependent magnetizations and magnetic susceptibilities that closely match experimental values within spectroscopic accuracy. These results underscore the efficiency of CC2 in computing state energies of multi-configurational, open-shell systems and highlight the utility of the more cost-efficient EOM-CCSD-in-DFT for computing spin–orbit couplings and magnetic properties of complex and large molecular magnets. [ABSTRACT FROM AUTHOR]

When the rate of shot noise is controlled by on–off states we speak of intermittent shot noise. The on–off states lead to alternately occurring clusters of events and intermissions, respectively. We derive the power spectrum of the intermittent shot noise by applying the Wiener-Khinchin theorem. Besides reduced shot noise, we obtain excess noise, which depends on the parameters of the on–off states. We calculate the excess noise for power-law distributed on-states; within the scaling region, the excess noise is excellently approximated by C∕fb. The behavior of the slope b and of the amplitude C in dependence of the on–off times is investigated. For large scaling regions, we find a preference for a pure 1/f shape. Finally, we regard the variance of events occurring within a time interval. In the presence of 1/f fluctuations, the variance of counts attains extreme values which are accompanied by an extreme property of slope b. [ABSTRACT FROM AUTHOR]

Abstract Background The concentrations of the highly atherogenic lipoprotein(a) [Lp(a)] are mainly genetically determined by the LPA gene locus. However, up to 70% of the coding sequence is located in the complex so-called kringle IV type 2 (KIV-2) copy number variation, a region hardly accessible by common genotyping and sequencing technologies. Despite its size, little is known about genetic variants in this complex region. The R21X variant is a functional variant located in this region, but it has never been analyzed in large cohorts. Methods We typed R21X in 10,910 individuals from three European populations using a newly developed high-throughput allele-specific qPCR assay. R21X allelic location was determined by separating the LPA alleles using pulsed-field gel electrophoresis (PFGE) and typing them separately. Using GWAS data, we identified a proxy SNP located outside of the KIV-2. Linkage disequilibrium was determined both statistically and by long-range haplotyping using PFGE. Worldwide frequencies were determined by reanalyzing the sequencing data of the 1000 Genomes Project with a dedicated pipeline. Results R21X carriers (frequency 0.016–0.021) showed significantly lower mean Lp(a) concentrations (− 11.7 mg/dL [− 15.5; − 7.82], p = 3.39e−32). The variant is located mostly on medium-sized LPA alleles. In the 1000 Genome data, R21X mostly occurs in Europeans and South Asians, is absent in Africans, and shows varying frequencies in South American populations (0 to 0.022). Of note, the best proxy SNP was another LPA null mutation (rs41272114, D′ = 0.958, R 2 = 0.281). D′ was very high in all 1000G populations (0.986–0.996), although rs41272114 frequency varies considerably (0–0.182). Co-localization of both null mutations on the same allele was confirmed by PFGE-based long-range haplotyping. Conclusions We performed the largest epidemiological study on an LPA KIV-2 variant so far, showing that it is possible to assess LPA KIV-2 mutations on a large scale. Surprisingly, in all analyzed populations, R21X was located on the same haplotype as the splice mutation rs41272114, creating “double-null” LPA alleles. Despite being a nonsense variant, the R21X status does not provide additional information beyond the rs41272114 genotype. This has important implications for studies using LPA loss-of-function mutations as genetic instruments and emphasizes the complexity of LPA genetics.

Cesium atoms that are grown on intercalated bilayer graphene can create an ordered epitaxial film. Here, the authors report that such a strained film can host quantum well states with high electronic quality as characterized through angle-resolved photoemission spectroscopy.

Precision laser spectroscopy of the 229-thorium nuclear isomer transition in a solid-state environment would represent a significant milestone in the field of metrology, opening the door to the realization of a nuclear clock. Working toward this goal, experimental methods require knowledge of various properties of a large band-gap material, such as calcium fluoride doped with specific isotopes of the heavy elements thorium, actinium, cerium, neptunium, and uranium. By accurately determining the atomic structure of potential charge compensation schemes by using a generalized gradient approximation within the ab-initio framework of density functional theory, calculations of electric field gradients on the dopants become accessible, which cause a quadrupole splitting of the nuclear-level structure that can be probed experimentally. Band gaps and absorption coefficients in the range of the 229-thorium nuclear transition are estimated by using the G0W0 method and by solving the Bethe–Salpeter equation.

A first-principles study of the adsorption of a single water molecule on a layer of graphitic carbon nitride is reported employing an embedding approach for many-electron correlation methods. To this end, a plane-wave based implementation to obtain intrinsic atomic orbitals and Wannier functions for arbitrary localization potentials is presented. In our embedding scheme, the localized occupied orbitals allow for a separate treatment of short-range and long-range correlation contributions to the adsorption energy by a fragmentation of the simulation cell. In combination with unoccupied natural orbitals, the coupled cluster ansatz with single, double, and perturbative triple particle–hole excitation operators is used to capture the correlation in local fragments centered around the adsorption process. For the long-range correlation, a seamless embedding into the random phase approximation yields rapidly convergent adsorption energies with respect to the local fragment size. Convergence of computed binding energies with respect to the virtual orbital basis set is achieved employing a number of recently developed techniques. Moreover, we discuss fragment size convergence for a range of approximate many-electron perturbation theories. The obtained benchmark results are compared to a number of density functional calculations. [ABSTRACT FROM AUTHOR]

Environmental monitoring of aquatic systems is the key requirement for sustainable environmental protection and future drinking water supply. The quality of water resources depends on the effectiveness of water treatment plants to reduce chemical pollutants, such as nitrates, pharmaceuticals, or microplastics. Changes in water quality can vary rapidly and must be monitored in real-time, enabling immediate action. In this study, we test the feasibility of a deep UV Raman spectrometer for the detection of nitrate/nitrite, selected pharmaceuticals and the most widespread microplastic polymers. Software utilizing artificial intelligence, such as a convolutional neural network, is trained for recognizing typical spectral patterns of individual pollutants, once processed by mathematical filters and machine learning algorithms. The results of an initial experimental study show that nitrates and nitrites can be detected and quantified. The detection of nitrates poses some challenges due to the noise-to-signal ratio and background and related noise due to water or other materials. Selected pharmaceutical substances could be detected via Raman spectroscopy, but not at concentrations in the µg/l or ng/l range. Microplastic particles are non-soluble substances and can be detected and identified, but the measurements suffer from the heterogeneous distribution of the microparticles in flow experiments.

In the last 50 years, density functional theory (DFT) has been the working horse of materials simulation.[1] DFT success comes from its relatively low computational cost compared to other electronic structure approaches and an often acceptable accuracy. QMC methods are employed to study adsorption energies of single atoms on graphite and graphene.[[10]] The obtained benchmark results can be employed to improve the accuracy of computationally more efficient approaches. The employed methods include DFT, quantum Monte Carlo (QMC), Green's function based approaches, and quantum chemical wavefunction based theories. [Extracted from the article]

The workhorse method of computational materials science is undeniably the density functional theory (DFT) in the Kohn-Sham framework of approximate exchange and correlation energy functionals. However, the need for highly accurate electronic structure theory calculations in materials science motivates the further development and exploration of alternative as well as complementary techniques. Among these alternative approaches, quantum chemical wavefunction based theories and in particular coupled cluster theory hold promise in filling the gap in the toolbox of computational materials scientists. Coupled cluster (CC) theory provides a compelling framework of approximate infinite-order perturbation theory, in the form of an exponential of cluster operators describing the true quantum many-body effects of the electronic wave function at a computational cost that, despite being significantly more expensive than DFT, scales polynomially with system size. The hierarchy of size-extensive approximate methods established in the framework of CC theory, achieves systematic improvability for many materials properties. This is in contrast to currently available density functionals that often suffer from uncontrolled approximations that limit the accuracy in the prediction of materials properties. In this tutorial-style review we will introduce basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the connection between coupled cluster theory and the random-phase approximation that is widely used in the field of solid-state physics. We will discuss various approaches to improve the computational performance without compromising on accuracy. These approaches include large-scale parallel design as well as techniques that reduce the pre-factor of the computational complexity. A central part of this article discusses the convergence of calculated properties to the thermodynamic limit, which is of significant importance for reliable predictions of materials properties and constitutes an additional challenge compared to calculations of large molecules. We mention technical aspects of computer code implementations of periodic coupled cluster theories in different numerical frameworks of the one-electron orbital basis; the projector-augmented-wave formalism using a plane wave basis set and the numeric atom-centered-orbital (NAO) with resolution-of-identity. We will discuss results and the possible scope of these implementations and how they can help advance the current state of the art in electronic structure theory calculations of materials.

We present a basis set correction scheme for the coupled-cluster singles and doubles (CCSD) method. The scheme is based on employing frozen natural orbitals (FNOs) and diagrammatically decomposed contributions to the electronic correlation energy, which dominate the basis set incompleteness error (BSIE). As recently discussed in the work of Irmler et al. [Phys. Rev. Lett. 123, 156401 (2019)], the BSIE of the CCSD correlation energy is dominated by the second-order Møller–Plesset (MP2) perturbation energy and the particle–particle ladder term. Here, we derive a simple approximation to the BSIE of the particle–particle ladder term that effectively corresponds to a rescaled pair-specific MP2 BSIE, where the scaling factor depends on the spatially averaged correlation hole depth of the coupled-cluster and first-order pair wavefunctions. The evaluation of the derived expressions is simple to implement in any existing code. We demonstrate the effectiveness of the method for the uniform electron gas. Furthermore, we apply the method to coupled-cluster theory calculations of atoms and molecules using FNOs. Employing the proposed correction and an increasing number of FNOs per occupied orbital, we demonstrate for a test set that rapidly convergent closed and open-shell reaction energies, atomization energies, electron affinities, and ionization potentials can be obtained. Moreover, we show that a similarly excellent trade-off between required virtual orbital basis set size and remaining BSIEs can be achieved for the perturbative triples contribution to the CCSD(T) energy employing FNOs and the (T*) approximation. [ABSTRACT FROM AUTHOR]

Zirconia (ZrO_{2}) has been well studied experimentally for decades, but still poses a severe challenge for computational approaches. We present thorough many-electron benchmark calculations within the random-phase approximation framework of the phase stabilities of the most common ZrO_{2} phases and assess the performance of various density functional theory (DFT) and beyond-DFT methods. We find that the commonly used DFT and hybrid functionals strongly overestimate both the energetic differences of the common phases and the stability of two metastable phases. The many-electron calculations offer a significantly improved description of the predicted bulk properties, especially of the bulk modulus B_{0}. On the DFT level, the van der Waals corrected meta-generalized-gradient approximation (SCAN-rVV10) provides much better agreement with the experimental values than other (semi)local and hybrid approaches.

Knowledge regarding the involvement of sweetness perception on energy intake is scarce. Here, the impact of glucose and sucrose sweetness, beyond their caloric load, on subsequent food intake and biomarkers of satiation was evaluated by co-administration of the sweet taste receptor inhibitor lactisole. A total of 27 healthy, male subjects received solutions of either 10% glucose w/o 60 ppm lactisole or 10% sucrose w/o 60 ppm lactisole. Subsequent food intake from a standardized breakfast was evaluated 2 h after receiving the respective test solution. Changes in postprandial plasma concentrations of cholecystokinin, ghrelin, and serotonin were determined over a period of 120 min, as was the body temperature. Administration of lactisole to the sucrose solution increased the energy intake from the subsequent standardized breakfast by 12.9 ± 5.8% (p = 0.04), led to a decreased Δ AUC of the body core temperature by 46 ± 20% (p = 0.01), and time-dependently reduced Δ serotonin plasma concentrations (−16.9 ± 6.06 ng/mL vs. −0.56 ± 3.7 ng/mL after sucrose administration, p = 0.03). The present study shows that lactisole increases energy intake and decreases plasma serotonin concentrations as well as body core temperature induced by sucrose, but not glucose. This finding may be associated with the different binding affinities of sucrose and glucose to the sweet taste receptor.

Since the advent of smartphones, work tasks shift progressively towards mobile phones. The main hurdle of this progression is the substantially slower input speed of smartphones in comparison with physical keyboards. This input speed could be improved by using keyboard layouts optimized for use with smartphones. As these keyboard layouts are not commonly used, switching to them results in a poor novice experience with an initially decreased text input speed. Previous investigations confirmed that this poor novice experience can be attenuated by using visual clues accentuating the most probable keys. This gives rise to the question of which visual impression leads to the best performance improvement. Therefore, this article evaluates the performance of six visual clues with different visual impressions via a user study conducted with 28 participants. The results showed that the visual clue with a pop-up animation and the visual clue with an increased font size performed the best with a 4% and 3%, respectively, typing performance improvement. Nonetheless, the questionnaire and personal preferences part of the user study showed that a 4% performance gain is not enough to crown one individual visual clue as the best visual clue to be used with every individual. This leads to the conclusion that functionality to choose one personal preference is more important than focusing on one specific best clue. [ABSTRACT FROM AUTHOR]

We present an implementation of the equation of motion coupled-cluster singles and doubles (EOM-CCSD) theory using periodic boundary conditions and a plane wave basis set. Our implementation of EOM-CCSD theory is applied to study F-centers in alkaline earth oxides employing a periodic supercell approach. The convergence of the calculated electronic excitation energies for neutral color centers in MgO, CaO, and SrO crystals with respect to the orbital basis set and system size is explored. We discuss extrapolation techniques that approximate excitation energies in the complete basis set limit and reduce finite size errors. Our findings demonstrate that EOM-CCSD theory can predict optical absorption energies of F-centers in good agreement with experiment. Furthermore, we discuss calculated emission energies corresponding to the decay from triplet to singlet states responsible for the photoluminescence properties. Our findings are compared to experimental and theoretical results available in the literature. [ABSTRACT FROM AUTHOR]

We present an embedding approach to treat local electron correlation effects in periodic environments. In a single consistent framework, our plane wave based scheme embeds a local high-level correlation calculation [here, Coupled Cluster (CC) theory], employing localized orbitals, into a low-level correlation calculation [here, the direct Random Phase Approximation (RPA)]. This choice allows for an accurate and efficient treatment of long-range dispersion effects. Accelerated convergence with respect to the local fragment size can be observed if the low-level and high-level long-range dispersions are quantitatively similar, as is the case for CC in RPA. To demonstrate the capabilities of the introduced embedding approach, we calculate adsorption energies of molecules on a surface and in a chabazite crystal cage, as well as the formation energy of a lattice impurity in a solid at the level of highly accurate many-electron perturbation theories. The absorption energy of a methane molecule in a zeolite chabazite is converged with an error well below 20 meV at the CC level. As our largest periodic benchmark system, we apply our scheme to the adsorption of a water molecule on titania in a supercell containing more than 1000 electrons. [ABSTRACT FROM AUTHOR]