Search

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.

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]

We report on a many-electron wavefunction theory study for the reaction energetics of hydrogen dissociation on the Si(100) surface. We demonstrate that quantum chemical wavefunction based methods using periodic boundary conditions can predict chemically accurate results for the activation barrier and the chemisorption energy in agreement with experimental findings. These highly accurate results for the reaction energetics enable a deeper understanding of the underlying physical mechanism and make it possible to benchmark widely used density functional theory methods. [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]

We introduce a straightforward Gaussian process regression (GPR) model for the transition structure factor of metal periodic coupled cluster singles and doubles (CCSD) calculations. This is inspired by the method introduced by Liao and Grüneis for interpolating over the transition structure factor to obtain a finite size correction for CCSD [K. Liao and A. Grüneis, J. Chem. Phys. 145, 141102 (2016)] and by our own prior work using the transition structure factor to efficiently converge CCSD for metals to the thermodynamic limit [Mihm et al., Nat. Comput. Sci. 1, 801 (2021)]. In our CCSD-FS-GPR method to correct for finite size errors, we fit the structure factor to a 1D function in the momentum transfer, G. We then integrate over this function by projecting it onto a k-point mesh to obtain comparisons with extrapolated results. Results are shown for lithium, sodium, and the uniform electron gas. [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.

We present a method to correct for finite size errors in coupled cluster theory calculations of solids. The outlined technique shares similarities with electronic structure factor interpolation methods used in quantum Monte Carlo calculations. However, our approach does not require the calculation of density matrices. Furthermore we show that the proposed finite size corrections achieve chemical accuracy in the convergence of second-order Møller-Plesset perturbation and coupled cluster singles and doubles correlation energies per atom for insulating solids with two atomic unit cells using 2 × 2 × 2 and 3 × 3 × 3 k-point meshes only. [ABSTRACT FROM AUTHOR]

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.

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.

We employ Hartree-Fock, second-order Møller-Plesset perturbation, coupled cluster singles and doubles (CCSD) as well as CCSD plus perturbative triples (CCSD(T)) theory to study the pressure induced transition from the rocksalt to the cesium chloride crystal structure in LiH. We show that the calculated transition pressure converges rapidly in this series of increasingly accurate many-electron wave function based theories. Using CCSD(T) theory, we predict a transition pressure for the structural phase transition in the LiH crystal of 340 GPa. Furthermore, we investigate the potential energy surface for this transition in the parameter space of the Buerger path. [ABSTRACT FROM AUTHOR]