Neural network variational Monte Carlo for positronic chemistry

Quantum chemical calculations of the ground-state properties of positron-molecule complexes are challenging. The main difficulty lies in employing an appropriate basis set for representing the coalescence between electrons and a positron. Here, we tackle this problem with the recently developed Fermionic neural network (FermiNet) wavefunction, which does not depend on a basis set. We find that FermiNet produces highly accurate, in some cases state-of-the-art, ground-state energies across a range of atoms and small molecules with a wide variety of qualitatively distinct positron binding characteristics. We calculate the binding energy of the challenging non-polar benzene molecule, finding good agreement with the experimental value, and obtain annihilation rates which compare favourably with those obtained with explicitly correlated Gaussian wavefunctions. Our results demonstrate a generic advantage of neural network wavefunction-based methods and broaden their applicability to systems beyond the standard molecular Hamiltonian.Comment: 14 pages, 3 figure

z+: Neutron cross section separation from wide-angle uniaxial polarization analysis from wide-angle uniaxial polarization analysis

We introduce a simple method to extract the nuclear coherent and isotope incoherent, spin incoherent, and magnetic neutron scattering cross section components from powder scattering data measured using a single neutron beam polarization direction and a position-sensitive detector with large out-of-plane coverage. The method draws inspiration from polarized small-angle neutron scattering and contrasts with conventional so-called “ xyz” polarization analysis on wide-angle instruments, which requires measurements with three orthogonal polarization directions. The viability of the method is demonstrated on both simulated and experimental data for the classical “spin ice” system Ho2Ti2O7, the latter from the linear energy transfer direct geometry spectrometer at the International Science Information Service facility. The cross section components can be reproduced with good fidelity by either fitting the out-of-plane angle dependence around a Debye–Scherrer cone or grouping the data by angle and performing a matrix inversion. The limitations of the method and its practical uses are discussed

Discovering quantum phase transitions with fermionic neural networks

Deep neural networks have been extremely successful as highly accurate wave function ans\"atze for variational Monte Carlo calculations of molecular ground states. We present an extension of one such ansatz, FermiNet, to calculations of the ground states of periodic Hamiltonians, and study the homogeneous electron gas. FermiNet calculations of the ground-state energies of small electron gas systems are in excellent agreement with previous initiator full configuration interaction quantum Monte Carlo and diffusion Monte Carlo calculations. We investigate the spin-polarized homogeneous electron gas and demonstrate that the same neural network architecture is capable of accurately representing both the delocalized Fermi liquid state and the localized Wigner crystal state. The network is given no \emph{a priori} knowledge that a phase transition exists, but converges on the translationally invariant ground state at high density and spontaneously breaks the symmetry to produce the crystalline ground state at low density

Determining geophysical responses from burials in graveyards and cemeteries

Graveyards and cemeteries around the world are increasingly designated as full. Therefore, there is a requirement to identify vacant spaces for new burials or to identify existing ones to exhume and then reinter if necessary. Geophysical methods offer a potentially noninvasive target detection solution; however, there has been limited research to identify optimal geophysical detection methods against burial age. We have collected multifrequency (225–900 MHz) ground-penetrating radar (GPR), electrical resistivity, and magnetic susceptibility surface data over known graves with different burial ages and soil types in three UK church graveyards. Results indicate that progressively older burials are more difficult to detect, but this decrease is not linear and is site specific. Medium- to high-frequency GPR and magnetic susceptibility was optimal in clay-rich soils, medium- to high-frequency GPR and electrical resistivity in sandy soils, and electrical resistivity and low-frequency GPR in coarse sand and pebbly soils, respectively. A multigeophysical technique approach should be used by survey practitioners where grave locations are not known to maximize target detection success. Grave soil and grave cuts are important grave position indicators. Grave headstones were not always located where burials were located. We have determined the value of these techniques in grave detection and could potentially date burials from their geophysical responses

Novel spectrophotometric method for the determination of azithromycin in pharmaceutical formulations based on its charge transfer reaction with quinalizarin

This paper proposes a new method for simple and fast spectrophotometric determination of azithromycin in pharmaceutical formulations. The method is based on the charge transfer reaction between the azithromycin and quinalizarin in methanol medium. In order to achieve maximum sensitivity the effect of some chemical variables such as the type of solvent, reagent concentration and reaction time were evaluated. The reaction was characterized in terms of stability of the product formed and its stoichiometry, and the apparent molar absorptivity and association constant were derived. Best conditions for the analytical determination of azithromycin were observed in methanol medium with a quinalizarin concentration of 50 mg L-1. At these conditions, the radical anion (absorbing specie) was formed in the medium immediately after mixing of the reagents and showed maximum absorption at 564 nm. The method presented a limit of detection of 0.35 mg L-1 and a limit of quantification of 1.2 mg L-1. It was successfully applied in the determination of azithromycin in three commercial pharmaceutical formulations of azithromycin and no matrix interferences were observed

Gas-assisted spray coating of perovskite solar cells incorporating sprayed self-assembled monolayers

Self-assembled monolayers (SAMs) are becoming widely utilized as hole-selective layers in high-performance p-i-n architecture perovskite solar cells. Ultrasonic spray coating and airbrush coating are demonstrated here as effective methods to deposit MeO-2PACz; a carbazole-based SAM. Potential dewetting of hybrid perovskite precursor solutions from this layer is overcome using optimized solvent rinsing protocols. The use of air-knife gas-quenching is then explored to rapidly remove the volatile solvent from an MAPbI3 precursor film spray-coated onto an MeO-2PACz SAM, allowing fabrication of p-i-n devices with power conversion efficiencies in excess of 20%, with all other layers thermally evaporated. This combination of deposition techniques is consistent with a rapid, roll-to-roll manufacturing process for the fabrication of large-area solar cells

Network development in biological gels: role in lymphatic vessel development

In this paper, we present a model that explains the prepatterning of lymphatic vessel morphology in collagen gels. This model is derived using the theory of two phase rubber material due to Flory and coworkers and it consists of two coupled fourth order partial differential equations describing the evolution of the collagen volume fraction, and the evolution of the proton concentration in a collagen implant; as described in experiments of Boardman and Swartz (Circ. Res. 92, 801–808, 2003). Using linear stability analysis, we find that above a critical level of proton concentration, spatial patterns form due to small perturbations in the initially uniform steady state. Using a long wavelength reduction, we can reduce the two coupled partial differential equations to one fourth order equation that is very similar to the Cahn–Hilliard equation; however, it has more complex nonlinearities and degeneracies. We present the results of numerical simulations and discuss the biological implications of our model