OPTiMaDe API specification 0.9.5

Designing new materials suitable for specific applications is a long, complex, and costly process. Researchers think of new ideas based on intuition and experience. Their synthesis and evaluation require a tremendous amount of trial and error. In the last few years, there has been a major game change in materials design. Thanks to the exponential growth of computer power and the development of robust first-principles electronic structure codes, it has become possible to perform large sets of calculations automatically. This is the burgeoning area of high-throughput ab initio computation. Such calculations have been used to create large databases containing the calculated properties of existing and hypothetical materials, many of which have appeared online: the AFLOW distributed materials property repository AiiDA the Harvard Clean Energy Project Database the Materials Project the NoMaD (Novel Materials Discovery) Repository the Open Quantum Materials Database the Computational Materials Repository the Data Catalyst Genome The aim of OPTiMaDe is to work in the direction of making these databases inter-operational by developing a common REST API. The version 0.9.5 (list of contributors 0.9.5) is now available. It can also be downloaded from GitHub, and which is available at $\href{https://github.com/Materials-Consortia/OPTiMaDe}{\text{https://github.com/Materials-Consortia/OPTiMaDe}}

Probabilistic design of a molybdenum-base alloy using a neural network

An artificial intelligence tool is exploited to discover and characterize a new molybdenum-base alloy that is the most likely to simultaneously satisfy targets of cost, phase stability, precipitate content, yield stress, and hardness. Experimental testing demonstrates that the proposed alloy fulfills the computational predictions, and furthermore the physical properties exceed those of other commercially available Mo-base alloys for forging-die applications.The authors acknowledge the financial support of Rolls-Royce plc, EPSRC under EP/H022309/1 and EP/H500375/1, the Royal Society, and Gonville & Caius College

Temporal fluctuation-induced order in conventional superconductors

Communal pairing in superconductors introduces variational freedom for Cooper pairs to share fermions. Temporal oscillations of the superconducting gap entropically drive communal pairing through the order by disorder phenomenology, stabilising a finite momentum space width of the superconducting gap that increases with interaction strength, creating a smooth evolution from the weakly interacting BCS state to the strongly interacting BEC state.Royal Society and the National University of Singapor

Pseudopotentials for an ultracold dipolar gas

A gas of ultracold molecules interacting via the long-range dipolar potential offers a highly controlled environment in which to study strongly correlated phases. However, at particle coalescence the divergent $1/r^3$ dipolar potential and associated pathological wavefunction hinder computational analysis. For a dipolar gas constrained to two dimensions we overcome these numerical difficulties by proposing a pseudopotential that is explicitly smooth at particle coalescence, resulting in a 2000-times speedup in diffusion Monte Carlo calculations. The pseudopotential delivers the scattering phase shifts of the dipolar interaction with an accuracy of $10^{-5}$ and predicts the energy of a dipolar gas to an accuracy of $10^{-4}E_\mathrm{F}$ in a diffusion Monte Carlo calculation.TMW acknowledges the financial support of the EPSRC [EP/J017639/1], and GJC acknowledges the financial support of the Royal Society and Gonville & Caius College. There is Open Access to this paper and data available at https://www.repository.cam.ac.uk.This is the author accepted manuscript. The final version is available at http://journals.aps.org/pra/abstract/10.1103/PhysRevA.93.022706

Materials data validation and imputation with an artificial neural network

We apply an artificial neural network to model and verify material properties. The neural network algorithm has a unique capability to handle incomplete data sets in both training and predicting, so it can regard properties as inputs allowing it to exploit both composition-property and property-property correlations to enhance the quality of predictions, and can also handle a graphical data as a single entity. The framework is tested with different validation schemes, and then applied to materials case studies of alloys and polymers. The algorithm found twenty errors in a commercial materials database that were confirmed against primary data sources

Jastrow correlation factor for periodic systems

We propose a Jastrow factor for electron-electron correlations that interpolates between the radial symmetry of the Coulomb interaction at short inter-particle distance and the space-group symmetry of the simulation cell at large separation. The proposed Jastrow factor captures comparable levels of the correlation energy to current formalisms, is 40% quicker to evaluate, and offers benefits in ease of use, as we demonstrate in quantum Monte Carlo simulations.Engineering and Physical Sciences Research Council [Grant ID: EP/J017639/1], Gonville & Caius College, Royal SocietyThis is the author accepted manuscript. The final version is available from the American Physical Society via http://dx.doi.org/10.1103/PhysRevB.94.03515

Effective-range dependence of two-dimensional Fermi gases

The Feshbach resonance provides precise control over the scattering length and effective range of interactions between ultracold atoms. We propose the ultratransferable pseudopotential to model effective interaction ranges -1.5≤kF2Reff2≤0, where Reff is the effective range and kF is the Fermi wave vector, describing narrow to broad Feshbach resonances. We develop a mean-field treatment and exploit the pseudopotential to perform a variational and diffusion Monte Carlo study of the ground state of the two-dimensional Fermi gas, reporting on the ground-state energy, contact, condensate fraction, momentum distribution, and pair-correlation functions as a function of the effective interaction range across the BEC-BCS crossover. The limit kF2Reff2→- is a gas of bosons with zero binding energy, whereas ln(kFa)→- corresponds to noninteracting bosons with infinite binding energy.The authors acknowledge the financial support of the EPSRC Grant no. [EP/J017639/1], L.M.S. acknowledges financial support from the Cambridge European Trust, Cambridge Philosophical Society, VSB Fonds, and the Prins Bernhard Cultuurfonds, and G.J.C. acknowledges the financial support of the Royal Society and Gonville & Caius College. Computational facilities were provided by the University of Cambridge High Performance Computing Service

Direct evaluation of the force constant matrix in quantum Monte Carlo.

We develop a formalism to directly evaluate the matrix of force constants within a Quantum Monte Carlo calculation. We utilize the matrix of force constants to accurately relax the positions of atoms in molecules and determine their vibrational modes, using a combination of variational and diffusion Monte Carlo. The computed bond lengths differ by less than 0.007 Å from the experimental results for all four tested molecules. For hydrogen and hydrogen chloride, we obtain fundamental vibrational frequencies within 0.1% of experimental results and ∼10 times more accurate than leading computational methods. For carbon dioxide and methane, the vibrational frequency obtained is on average within 1.1% of the experimental result, which is at least 3 times closer than results using restricted Hartree-Fock and density functional theory with a Perdew-Burke-Ernzerhof functional and comparable or better than density functional theory with a semi-empirical functional

Communal pairing in spin-imbalanced Fermi gases

A spin-imbalanced Fermi gas with an attractive contact interaction forms a superconducting state whose underlying components are superpositions of Cooper pairs that share minority-spin fermions. This superconducting state includes correlations between all available fermions, making it energetically favorable to the Fulde--Ferrell--Larkin--Ovchinnikov superconducting state. The ratio of the number of up- and down-spin fermions in the instability is set by the ratio of the up- and down-spin density of states in momentum at the Fermi surfaces, to fully utilize the accessible fermions. We present analytical and complementary Diffusion Monte Carlo results for the state

Pseudopotential for the electron-electron interaction

We propose a pseudopotential for the electron-electron Coulomb interaction to improve the efficiency of many-body electronic structure calculations. The pseudopotential accurately replicates the scattering properties of the Coulomb interaction, and recovers the analytical solution for two electrons in a parabolic trap. A case study for the homogeneous electron gas using the diffusion Monte Carlo and configuration interaction methods recovers highly accurate values for the ground state energy, and the smoother potential reduces the computational cost by a factor of ~30. Finally, we demonstrate the use of the pseudopotential to study isolated lithium and beryllium atoms.GJC acknowledges the financial support of the Royal Society and Gonville & Caius College.This is the author accepted manuscript. The final version is available from APS via http://dx.doi.org/http://dx.doi.org/10.1103/PhysRevB.92.07510