GAMaterial-A genetic-algorithm software for material design and discovery

Genetic algorithms (GAs) are stochastic global search methods inspired by biological evolution. They have been used extensively in chemistry and materials science coupled with theoretical methods, ranging from force-fields to high-throughput first-principles methods. The methodology allows an accurate and automated structural determination for molecules, atomic clusters, nanoparticles, and solid surfaces, fundamental to understanding chemical processes in catalysis and environmental sciences, for instance. In this work, we propose a new genetic algorithm software, GAMaterial, implemented in Python3.x, that performs global searches to elucidate the structures of atomic clusters, doped clusters or materials and atomic clusters on surfaces. For all these applications, it is possible to accelerate the GA search by using machine learning (ML), the ML@GA method, to build subsequent populations. Results for ML@GA applied for the dopant distributions in atomic clusters are presented. The GAMaterial software was applied for the automatic structural search for the Ti₆ O₁₂ cluster, doping Al in Si₁₁ (4Al@Si₁₁ ) and Na₁₀ supported on graphene (Na₁₀ @graphene), where DFTB calculations were used to sample the complex search surfaces with reasonably low computational cost. Finally, the global search by GA of the Mo₈ C₄ cluster was considered, where DFT calculations were made with the deMon2k code, which is interfaced with GAMaterial.

Monomers of Glycine and Serine Have a Limited Ability to Hydrate in the Atmosphere

The role of atmospheric aerosols on climate change is one of the biggest uncertainties in most global climate models. Organic aerosols have been identified as potential cloud condensation nuclei (CCN), and amino acids are organic molecules that could serve as CCN. Amino acids make up a significant portion of the total organic material in the atmosphere, and herein we present a systematic study of hydration for two of the most common atmospheric amino acids, glycine and serine. We compute DLPNO/CCSD(T)//M08-HX/MG3S thermodynamic properties and atmospheric concentrations of Gly(H₂O)_n and Ser(H₂O)_n, where n = 1-5. We predict that serine-water clusters have higher concentrations at n = 1 and 5, while glycine-water clusters have higher concentrations at n = 2-4. However, both glycine and serine are inferred to exist primarily in their nonhydrated monomer forms in the absence of other species such as sulfuric acid.

Globally Optimal Catalytic Fields - Inverse Design of Abstract Embeddings for Maximum Reaction Rate Acceleration

The search for, and understanding of, good catalysts for chemical reactions is a central issue for chemists. Here, we present first steps toward developing a general computational framework to better support this task. This framework combines efficient, unbiased global optimization techniques with an abstract representation of the catalytic environment, to shrink the search space. To analyze the resulting catalytic embeddings, we employ dimensionality reduction and clustering techniques. This not only provides an inverse design approach to new catalytic embeddings but also illuminates the actual interactions behind catalytic effects. All this is illustrated here with a strictly electrostatic model for the environment and with two versions of a selected example reaction. We close with detailed discussions of future improvements of our framework.

Global structure search for molecules on surfaces: Efficient sampling with curvilinear coordinates

Efficient structure search is a major challenge in computational materials science. We present a modification of the basin hopping global geometry optimization approach that uses a curvilinear coordinate system to describe global trial moves. This approach has recently been shown to be efficient in structure determination of clusters [C. Panosetti et al., Nano Lett. 15, 8044-8048 (2015)] and is here extended for its application to covalent, complex molecules and large adsorbates on surfaces. The employed automatically constructed delocalized internal coordinates are similar to molecular vibrations, which enhances the generation of chemically meaningful trial structures. By introducing flexible constraints and local translation and rotation of independent geometrical subunits, we enable the use of this method for molecules adsorbed on surfaces and interfaces. For two test systems, trans-β-ionylideneacetic acid adsorbed on a Au(111) surface and methane adsorbed on a Ag(111) surface, we obtain superior performance of the method compared to standard optimization moves based on Cartesian coordinates.

Structural, dynamical, and transport properties of the hydrated halides: How do At(-) bulk properties compare with those of the other halides, from F(-) to I(-)?

The properties of halides from the lightest, fluoride (F(-)), to the heaviest, astatide (At(-)), have been studied in water using a polarizable force-field approach based on molecular dynamics (MD) simulations at the 10 ns scale. The selected force-field explicitly treats the cooperativity within the halide-water hydrogen bond networks. The force-field parameters have been adjusted to ab initio data on anion/water clusters computed at the relativistic Möller-Plesset second-order perturbation theory level of theory. The anion static polarizabilities of the two heaviest halides, I(-) and At(-), were computed in the gas phase using large and diffuse atomic basis sets, and taking into account both electron correlation and spin-orbit coupling within a four-component framework. Our MD simulation results show the solvation properties of I(-) and At(-) in aqueous phase to be very close. For instance, their first hydration shells are structured and encompass 9.2 and 9.1 water molecules at about 3.70 ± 0.05 Å, respectively. These values have to be compared to the F(-), Cl(-), and Br(-) ones, i.e., 6.3, 8.4, and 9.0 water molecules at 2.74, 3.38, and 3.55 Å, respectively. Moreover our computations predict the solvation free energy of At(-) in liquid water at ambient conditions to be 68 kcal mol(-1), a value also close the I(-) one, about 70 kcal mol(-1). In all, our simulation results for I(-) are in excellent agreement with the latest neutron- and X-ray diffraction studies. Those for the At(-) ion are predictive, as no theoretical or experimental data are available to date.

TD-DFT based fine-tuning of molecular excitation energies using evolutionary algorithms

An evolutionary de novo design method is presented to fine-tune the excitation energies of molecules calculated using time-dependent density functional theory (TD-DFT).

Bidirectional photocontrol of peptide conformation with a bridged azobenzene derivative

It goes both ways: A thiol-reactive cross-linker based on a bridged azobenzene derivative permits photoreversible control of peptide conformation on irradiation with violet (407 nm) and green (500-550 nm) light (see picture) through isomerization of the cross-linker. The large separation of the absorbance bands of the cis (yellow) and trans (red) isomers enables complete bidirectional photoswitching.