Quantum algorithm for alchemical optimization in material design

The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules obtainable from a set of atomic species grow exponentially with the size of the system, limiting the efficiency of classical sampling algorithms. On the other hand, quantum computers can provide an efficient solution to the sampling of the chemical compound space for the optimization of a given molecular property. In this work, we propose a quantum algorithm for addressing the material design problem with a favourable scaling. The core of this approach is the representation of the space of candidate structures as a linear superposition of all possible atomic compositions. The corresponding ‘alchemical’ Hamiltonian drives the optimization in both the atomic and electronic spaces leading to the selection of the best fitting molecule, which optimizes a given property of the system, e.g., the interaction with an external potential as in drug design. The quantum advantage resides in the efficient calculation of the electronic structure properties together with the sampling of the exponentially large chemical compound space. We demonstrate both in simulations and with IBM Quantum hardware the efficiency of our scheme and highlight the results in a few test cases. This preliminary study can serve as a basis for the development of further material design quantum algorithms for near-term quantum computers.

‘Alchemical’ quantum algorithm for the simultaneous optimisation of chemical composition and electronic structure for material design. By exploiting quantum mechanical principles this approach will boost drug discovery in the near future.     

Copper-catalyzed hydrostannation of activated alkynes

[reactions: see text] [(Ph3P)CuH]6 effectively catalyzes the hydrostannation of activated alkynes with exclusive regioselectivity for alpha-stannation. Syn hydrostannation is observed exclusively for alkynoates. Anti or syn hydrostannation adducts are obtained as products for alkynone substrates.     

Structurally Tunable 3‐Cyanoformazanate Boron Difluoride Dyes

The straightforward synthesis of a series of 3‐cyanoformazanate boron difluoride dyes is reported. Phenyl, 4‐methoxyphenyl and 4‐cyanophenyl N‐substituted derivatives were isolated and characterized by single‐crystal X‐ray crystallography, cyclic voltammetry, and UV/Vis spectroscopy. The compounds were demonstrated to possess tunable, substituent‐dependent absorption, emission, and electrochemical properties, which were rationalized through electronic structure calculations.     

Synthesis of Highly Functionalized Diaryl Ethers by Copper‐Mediated O‐Arylation of Phenols using Trivalent Arylbismuth Reagents

Highly functionalized diaryl ethers were prepared by copper(II) acetate mediated O‐arylation reaction of phenols using trivalent organobismuthanes. The reaction is performed under simple conditions and tolerates a wide diversity of functional groups on the phenol and on the organobismuth reagent. Substoichiometric amounts of catalyst can be used by performing the reaction under an oxygen atmosphere. The N‐arylation of pyridones is also reported.     

Linear algorithms for testing the sign stability of a matrix and for findingZ-maximum matchings in acyclic graphs

Summary Ann×n real matrixA=(a _ij ) isstable if each eigenvalue has negative real part, andsign stable (orqualitatively stable) if each matrix B with the same sign-pattern asA is stable, regardless of the magnitudes ofB's entries. Sign stability is of special interest whenA is associated with certain models from ecology or economics in which the actual magnitudes of thea _ij may be very difficult to determine. Using a characterization due to Quirk and Ruppert, and to Jeffries, an efficient algorithm is developed for testing the sign stability ofA. Its time-and-space-complexity are both 0(n ²), and whenA is properly presented that is reduced to 0(max{n, number of nonzero entries ofA}). Part of the algorithm involves maximum matchings, and that subject is treated for its own sake in two final sections.     

Thermoset modified with polyethersulfone: Characterization and control of the morphology

Thermoset (TS) epoxy resins can be toughened with a thermoplastic (TP) for high-performance applications. The final structure morphology has to be controlled to achieve high mechanical properties and high impact resistance. Four polyethersulfone-modified epoxy resins are considered. They consist of different epoxy monomer structure (TGAP, triglycidyl-p-aminophenol and TGDDM, tetraglycidyl diaminodiphenylmethane) and a fixed amount of thermoplastic, and they are cured with two different amounts of curing agent. A reaction-induced phase separation occurs for all formulations generating morphologies, different in shapes and scales. The aim is to control the final morphology and in particular its dominant length scale. This morphology depends on the phase separation process, from the initiation to its final stage. The initiation relies on the relative miscibility of the components and on the stoichiometry between epoxy and curing agent. The kinetics depends on the viscosity of the systems. The different morphologies are characterized by electron microscopy or neutron scattering. Dynamic mechanical analysis allows confirming the presence of a phase separation even when it is not observable by electron microscopy. Vermicular morphologies with few hundreds nanometer width are obtained for the systems containing the TGAP as epoxy monomer. Systems formulated with TGDDM presents morphologies on much smaller scale of order a few tens of nanometers. We interpret the different sizes of the morphologies as a consequence of a larger viscosity for the TGDDM systems as compared to the TGAP ones rather than by a latter initiation of phase separation.     

Linear Convergence Rates for Variants of the Alternating Direction Method of Multipliers in Smooth Cases

In the present paper, we propose a novel convergence analysis of the alternating direction method of multipliers, based on its equivalence with the overrelaxed primal–dual hybrid gradient algorithm. We consider the smooth case, where the objective function can be decomposed into one differentiable with Lipschitz continuous gradient part and one strongly convex part. Under these hypotheses, a convergence proof with an optimal parameter choice is given for the primal–dual method, which leads to convergence results for the alternating direction method of multipliers. An accelerated variant of the latter, based on a parameter relaxation, is also proposed, which is shown to converge linearly with same asymptotic rate as the primal–dual algorithm.