Query: Ab initio search for novel bipolar

Candidate papers:

abstract: Very recently, the newest class of spintronic materials, where reversible spin polarization can be controlled by applying gate voltage: so called bipolar magnetic semiconductors (Xingxing Li et al. arXiv:1208.1355) was proposed. In this work, a novel way to creation of bipolar magnetic semiconductors by doping of non magnetic semiconducting 1111 phases with magnetic dn 10 atoms is discussed using ab initio calculations of layered YZnAsO doped with Fe and Mn. In addition, more complex materials with several spectral intervals with opposite 100% spin polarization where multiple gate controlled spin polarization can be expected are proposed.
author_names: V V Bannikov

Alexander L Ivanovskii
title: Ab initio search for novel bipolar magnetic semiconductors: Layered YZnAsO doped with Fe and Mn
year: 2013

abstract: We sampled potential energy surfaces of neutral and anionic B3Hy clusters using the Gradient Embedded Genetic Algorithm (GEGA) program at the B3LYP/3 21G level of theory. The lowest energy isomers were recalculated at the B3LYP/6 311++G* MP2/6 311++G* and CCSD(T)/6 311++G* levels of theory. We found a diverse set of global minimum structures and low lying isomers for the studied clusters. The Adaptive Natural Density Partitioning (AdNDP) method was then used for chemical bonding analysis for all global minimum structures and low lying isomers. The chemical bonding patterns revealed by the AdNDP analysis can easily explain the geometric structure of even very exotic isomers and global minima. 2
author_names: Jared K Olson
title: Ab Initio Search for Novel BxHy Building Blocks with Potential for Hydrogen Storage
year: 2010

abstract: To solve protein structure prediction (PSP) problems computationally, a plethora of template based methods exist. However, there are very few ab initio models for PSP. Template based modeling relies on the existing structures and therefore is not effective for non homologous sequence based structure prediction. Thus, ab initio modeling is indispensable in such cases, even though it is a challenging optimization problem. To cope, we utilize an effective energy function (called 3DIGARS) and an advanced search algorithm (called KGA) based ab initio PSP, called 3DIGARS PSP. To address critical search, the proposed genetic algorithm deploys two effective operators: angle rotation and segment translation. Further, propensities of torsion angle and secondary structure distribution have been utilized to guide the conformation search. Crucial features, such as sequence specific accessibility, hydrophobic hydrophilic properties and torsion angles of protein residues are mined to formulate an optimized energy function, which is then combined with the advanced sampling algorithm to explore critical conformational space. Consequently, 3DIGARS PSP performed well compared to the state of the art method for a set of low TMscore models from CASP data.
author_names: Avdesh Mishra

Md Tamjidul Hoque
title: 3DIGARS PSP: A Novel Statistical Energy Function and Effective Conformational Search Strategy based ab initio Protein Structure Prediction
venue: 2019 22nd International Conference on Computer and Information Technology (ICCIT)
year: 2019

abstract: To solve protein structure prediction (PSP) problems computationally, a plethora of template based methods exist. However, there are very few ab initio models exist. Template based modeling relies on the existing structures and therefore is not effective for non homologous sequence based structure prediction. Thus, ab initio modeling is indispensable in such cases, even though it is a challenging optimization problem. To cope, we utilize an effective energy function (called 3DIGARS) and advanced search algorithm (called KGA) based ab initio PSP, called 3DIGARS PSP. The proposed approach deploys a memory assisted genetic algorithm to sample the energy hypersurface of the protein folding process to search the native fold of the protein. To address critical search, the proposed genetic algorithm deploys two effective operators: angle rotation and segment translation. Further, propensities of torsion angle and secondary structure distribution have been utilized to guide the conformation search. Crucial features, such as sequence specific accessibility, hydrophobic hydrophilic properties and torsion angles of protein residues are mined to formulate an optimized energy function, which is then combined with the advanced sampling algorithm to explore critical conformational space. Consequently, 3DIGARS PSP performed well compared to the state of the art methods for a set of low TMscore models from CASP data and E. coli proteins.
author_names: Avdesh Mishra

Md Tamjidul Hoque
title: DIGARS PSP A Novel Statistical Energy Function and Effective Conformational Search Strategy based ab initio Protein Structure Prediction
year: 2018

abstract: Background MicroRNAs (miRNAs) play a vital role as post transcriptional regulators in gene expression. Experimental determination of miRNA sequence and structure is both expensive and time consuming. The next generation sequencing revolution, which facilitated the rapid accumulation of biological data has brought biology into the "big data" domain. As such, developing computational methods to predict miRNAs has become an active area of inter disciplinary research. Objective The objective of this systematic review is to focus on the developments of ab initio plant miRNA identification methods over the last decade. Data sources Five databases were searched for relevant articles, according to a well defined review protocol. Study selection The search results were further filtered using the selection criteria that only included studies on novel plant miRNA identification using machine learning. Data extraction Relevant data from each study were extracted in order to carry out an analysis on their methodologies and findings. Results Results depict that in the last decade, there were 20 articles published on novel miRNA identification methods in plants of which only 11 of them were primarily focused on plant microRNA identification. Our findings suggest a need for more stringent plant focused miRNA identification studies. Conclusion Overall, the study accuracies are of a satisfactory level, although they may generate a considerable number of false negatives. In future, attention must be paid to the biological plausibility of computationally identified miRNAs to prevent further propagation of biologically questionable miRNA sequences.
author_names: Buwani Manuweera

Gillian Reynolds

Indika Kahanda
title: Computational methods for the ab initio identification of novel microRNA in plants: a systematic review
venue: PeerJ Comput. Sci.
year: 2019

abstract: To address the searching problem of protein conformational space in ab initio protein structure prediction, a novel method using abstract convex underestimation (ACUE) based on the framework of evolutionary algorithm was proposed. Computing such conformations, essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. As a consequence, the dimension of protein conformational space should be reduced to a proper level. In this paper, the high dimensionality original conformational space was converted into feature space whose dimension is considerably reduced by feature extraction technique. And, the underestimate space could be constructed according to abstract convex theory. Thus, the entropy effect caused by searching in the high dimensionality conformational space could be avoided through such conversion. The tight lower bound estimate information was obtained to guide the searching direction, and the invalid searching area in which the global optimal solution is not located could be eliminated in advance. Moreover, instead of expensively calculating the energy of conformations in the original conformational space, the estimate value is employed to judge if the conformation is worth exploring to reduce the evaluation time, thereby making computational cost lower and the searching process more efficient. Additionally, fragment assembly and the Monte Carlo method are combined to generate a series of metastable conformations by sampling in the conformational space. The proposed method provides a novel technique to solve the searching problem of protein conformational space. Twenty small to medium structurally diverse proteins were tested, and the proposed ACUE method was compared with It Fix, HEA, Rosetta and the developed method LEDE without underestimate information. Test results show that the ACUE method can more rapidly and more efficiently obtain the near native protein structure.
author_names: Xiao-hu Hao

Gui-jun Zhang

Xiao-gen Zhou

Xufeng Yu
title: A Novel Method Using Abstract Convex Underestimation in Ab Initio Protein Structure Prediction for Guiding Search in Conformational Feature Space
venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics
year: 2016

abstract: By means of ab initio computations and the global minimum structure search method, we have investigated structural, mechanical, and electronic properties of D carbon, a crystalline orthorhombic sp3 carbon allotrope (space group Pmma D2h5 with 6 atoms per cell) Total energy calculations demonstrate that D carbon is energetically more favorable than the previously proposed T6 structure (with 6 atoms per cell) as well as many others. This novel phase is dynamically, mechanically, and thermally stable at zero pressure and more stable than graphite beyond 63.7 GPa. D carbon is a semiconductor with a bandgap of 4.33 eV, less than diamond's gap (5.47 eV) The simulated X ray diffraction pattern is in satisfactory agreement with previous experimental data in chimney or detonation soot, suggesting its possible presence in the specimen.
author_names: Dong Fan

Shaohua Lu

Andrey A Golov

Artem A Kabanov

Xiaojun Hu
title: D carbon: Ab initio study of a novel carbon allotrope.
venue: The Journal of chemical physics
year: 2018

abstract: Intermetallic compounds made of alkali metals and gold have intriguing electronic and structural properties that have not been extensively explored. We perform a systematic study of the phase diagram of one binary system belonging to this family, namely NaxAu1?x, using the ab?initio minima hopping structural prediction method. We discover that the most stable composition is NaAu2, in agreement with available experimental data. We also confirm the crystal structures of NaAu2 and Na2Au, that were fully characterized in experiments, and identify a candidate ground state structure for the experimental stoichiometry NaAu. Moreover, we obtain three other stoichiometries, namely Na3Au2, Na3Au and Na5Au, that could be thermodynamically stable. We do not find any evidence for the existence of the experimentally proposed composition NaAu5. Finally, we perform phonon calculations to check the dynamical stability of all reported phases and we simulate x ray diffraction spectra for comparison with future experimental data.
author_names: Rafael Sarmiento-Perez

Tiago F T Cerqueira

Irais Valencia-Jaime

Maximilian Amsler

Stefan Goedecker

Silvana Botti

Miguel A L Marques

Aldo H Romero
title: Sodium gold binaries: novel structures for ionic compounds from an ab initio structural search
year: 2013

abstract: While the ongoing search to discover new high entropy systems is slowly expanding beyond metals, a rational and effective method for predicting "\textit{in silico}" the solid solution forming ability of multi component systems remains yet to be developed. In this article, we propose a novel high throughput approach for estimating the transition temperature of a solid solution: \textit{ab initio} energies are incorporated into a mean field statistical mechanical model where the relative entropy, Kullback Leibler divergence, is the key order parameter following the evolution of disorder. The method is corroborated by Monte Carlo simulations and the results from the current most reliable data for binary, ternary, quaternary and quinary systems (96.6% 90.7% 100% and 100% of correct solid solution predictions, respectively) By scanning through the many thousands of systems available in the \small{\mathrm{AFLOW} consortium repository, it is possible to predict a plethora of potential previously unknown quaternary and quinary solid solutions for future experimental validation.
author_names: Yoav Lederer

Cormac Toher

Kenneth S Vecchio

Stefano Curtarolo
title: The search for high entropy alloys: a high throughput \textit{ab initio} approach
year: 2017

abstract: Understanding magnetic anisotropy and specifically how to tailor it is crucial in the search for high temperature single ion magnets. Herein, we investigate the magnetic anisotropy in a six coordinated cobalt(II) compound that has a complex geometry and distinct triaxial magnetic anisotropy from the perspective of the electronic structure, using electronic spectra, ab initio calculations, and an experimental charge density, of which the latter two provides insight into the d orbital splitting. The analysis showed that the d orbital splitting satisfactorily predicted the complex triaxial magnetic anisotropy exhibited by the compound. Furthermore, a novel method to directly compare the ab initio results and the d orbital populations obtained from the experimental charge density was developed, while a topological analysis of the density provided insights into the metal ligand bonding. This work thus further establishes the validity of using d orbitals for predicting magnetic anisotropy in transition metal compounds while also pointing out the need for a more frequent usage of the term triaxial anisotropy in the field of single molecule magnetism.
author_names: Emil Damgaard-Moller

Lennard Krause

Helene Lassen

Lorraine A Malaspina

Simon Grabowsky

Heiko Bamberger

Jake McGuire

Haralampos N Miras

Stephen Sproules

Jacob Overgaard
title: Investigating Complex Magnetic Anisotropy in a Co(II) Molecular Compound: A Charge Density and Correlated Ab Initio Electronic Structure Study.
venue: Inorganic chemistry
year: 2020