Structure prediction articles within Nature Communications

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  • Article
    | Open Access

    Normal mode analysis is a crucial step in structural biology, but is based on an expensive diagonalisation of the system’s Hessian. Here the authors present INCHING, a GPU-based approach to accelerate this task up to >250 times over current methods for macromolecular assemblies.

    • Jordy Homing Lam
    • , Aiichiro Nakano
    •  & Vsevolod Katritch

  • Article
    | Open Access

    Previous theoretical interpretations of the Rydberg spectra of dimethylpiperazine (DMP) debated the existence of a localized minimum on the surface of the DMP+ cation. Here, the authors show a substantial influence of the Rydberg electron on the molecular structure, restoring the localized minimum.

    • Marc Reimann
    • , Christoph Kirsch
    •  & Martin Kaupp

  • Article
    | Open Access

    The nucleation of calcium silicate hydrate is a crucial step in cement hydration, but is still a poorly understood process. Here the authors use atomistic simulations to study primary particles and their aggregation, revealing a potential C-S-H “basic building block”.

    • Xabier M. Aretxabaleta
    • , Jon López-Zorrilla
    •  & Hegoi Manzano

  • Article
    | Open Access

    Nitrogen can form a maximum of three shared electron-pair bonds to complete its octet, suggesting the maximum bond order of nitrogen is three. Here, the authors report a joint photoelectron spectroscopy and quantum chemical study, showing a quadruple bond between nitrogen and thorium in thorium nitride.

    • Zejie Fei
    • , Jia-Qi Wang
    •  & Jun Li

  • Article
    | Open Access

    Rare-earth and actinide complexes are critical for a wealth of clean-energy applications but Three dimensional (3D) structural generation and prediction for these organometallic systems remains challenging. Here, the authors propose a high-throughput in-silico synthesis code for s-, p-, d-, and f-block mononuclear organometallic complexes.

    • Michael G. Taylor
    • , Daniel J. Burrill
    •  & Ping Yang

  • Article
    | Open Access

    Exploration of metastable phases of a given elemental composition is a data-intensive task. Here the authors integrate first-principles atomistic simulations with machine learning and high-performance computing to allow a rapid exploration of the metastable phases of carbon.

    • Srilok Srinivasan
    • , Rohit Batra
    •  & Subramanian K.R.S. Sankaranarayanan

  • Article
    | Open Access

    Developing theoretical frameworks to predict new polymorphs is highly desirable. Here the authors present an ab initio based force-field approach for crystal structure prediction offering a dramatic computational speed-up over fully ab initio schemes.

    • Rahul Nikhar
    •  & Krzysztof Szalewicz

  • Article
    | Open Access

    Predicting crystal structure prior to experimental synthesis is highly desirable. Here the authors propose a machine-learning framework combining graph network and optimization algorithms for crystal structure prediction, which is about three orders of magnitude faster than DFT-based approach.

    • Guanjian Cheng
    • , Xin-Gao Gong
    •  & Wan-Jian Yin

  • Article
    | Open Access

    The present manuscript reports a Bayesian deep-learning approach for the automatic, robust classification of polycrystalline systems of both synthetic and experimental origin. The unsupervised analysis of the internal neural-network representations reveals physically understandable patterns.

    • Andreas Leitherer
    • , Angelo Ziletti
    •  & Luca M. Ghiringhelli

  • Article
    | Open Access

    High-nitrogen content polyhedral molecules are of fundamental interest for theory and for synthesis applications. The authors, using isomer selective, tunable soft photoionization reflectron time-of-flight mass spectrometry, identify the formation of a hitherto elusive prismatic P3N3 molecule during sublimation of PH3 and N2 ice mixtures exposed to energetic electrons.

    • Cheng Zhu
    • , André K. Eckhardt
    •  & Ralf I. Kaiser

  • Article
    | Open Access

    Ternary heterometallic clusters often display intriguing structures and bonding. Here the authors prepare four [Sn2Sb5]3−-based clusters stabilized by coordination of a transition metal ion; analysis of their electronic structure reveals that the resulting cluster displays globally aromatic or antiaromatic character depending on the transition metal ion.

    • Yu-He Xu
    • , Nikolay V. Tkachenko
    •  & Zhong-Ming Sun

  • Article
    | Open Access

    Determining the structure of amorphous solids is important for optimization of pharmaceutical formulations, but direct relation of molecular dynamics (MD) simulations and NMR to achieve this is challenging. Here, the authors use a machine learning model of chemical shifts to solve the atomic-level structure of the hydrated amorphous drug AZD5718 by combining dynamic nuclear polarization-enhanced solid-state NMR with predicted shifts for MD simulations of large systems.

    • Manuel Cordova
    • , Martins Balodis
    •  & Lyndon Emsley

  • Article
    | Open Access

    Controlling the electronic states of molecules is a fundamental challenge for future sub-nanoscale device technologies but the external dynamical control of these states still awaits experimental realization. Here, via quantum chemical calculations, the authors demonstrate that in-plane uniaxial strain of 2D covalently linked arrays of radical units induces controlled pairing of π-conjugated electrons in a reversible way.

    • Isaac Alcón
    • , Raúl Santiago
    •  & Stefan T. Bromley

  • Article
    | Open Access

    Citrate-stabilized metallic colloids are key materials towards chemosensing and catalysis applications. Here the authors introduce a new theoretical model to estimate how the stoichiometry of citrate molecules absorbed onto spherical metallic nanoparticles influences their aggregation phenomena.

    • Sebastian Franco-Ulloa
    • , Giuseppina Tatulli
    •  & Marco De Vivo

  • Article
    | Open Access

    Machine learning models insufficient for certain screening tasks can still provide valuable predictions in specific sub-domains of the considered materials. Here, the authors introduce a diagnostic tool to detect regions of low expected model error as demonstrated for the case of transparent conducting oxides.

    • Christopher Sutton
    • , Mario Boley
    •  & Matthias Scheffler

  • Article
    | Open Access

    The polyhedral skeletal electron pair theory (PESPT), also known as Wade-Mingos’ rules, defines a relationship between skeletal bonding electron pairs and structure of clusters. Here the authors report the synthesis, structure and computational studies of planar C2B4R4 carboranes that do not adhere to PESPT.

    • Wei Lu
    • , Dinh Cao Huan Do
    •  & Rei Kinjo

  • Article
    | Open Access

    Solid-state nuclear magnetic resonance combined with quantum chemical shift predictions is limited by high computational cost. Here, the authors use machine learning based on local atomic environments to predict experimental chemical shifts in molecular solids with accuracy similar to density functional theory.

    • Federico M. Paruzzo
    • , Albert Hofstetter
    •  & Lyndon Emsley

  • Article
    | Open Access

    The equilibrium structures and dynamics of a nanoscale system are regulated by a complex potential energy surface (PES), a key target of theoretical calculations but experimentally elusive. Here, the authors report the measurement of a key PES parameter for size-selected Au nanoclusters soft-landed on amorphous silicon nitride supports.

    • D. M. Foster
    • , R. Ferrando
    •  & R. E. Palmer

  • Article
    | Open Access

    Helium was long thought to be unable to form stable solid compounds, until a recent discovery that helium reacts with sodium at high pressure. Here, the authors demonstrate the driving force for helium reactivity, showing that it can form new compounds under pressure without forming any local chemical bonds.

    • Zhen Liu
    • , Jorge Botana
    •  & Mao-sheng Miao

  • Article
    | Open Access

    The thermodynamic stability of atomically precise, liganded metal nanoclusters remains poorly understood. Here, the authors use first-principles calculations to derive a new theory that rationalizes the stability of these nanoclusters as a function of their composition and morphology.

    • Michael G. Taylor
    •  & Giannis Mpourmpakis

  • Article
    | Open Access

    Pressure causes profound changes in the properties of atoms and chemical bonding leading to unusual materials. Here, the authors investigate the Ca-C system and find that it becomes increasingly complex and develops a multitude of phases with various compositions and new structures at higher pressures.

    • Yan-Ling Li
    • , Sheng-Nan Wang
    •  & Timothy A. Strobel

  • Article |

    It is commonly believed that pressure-induced crystallization in Ce-Al amorphous alloy is caused by Ce 4f orbital delocalization. Here, Wu et al. propose an alternative mechanism, whereby the crystallization is driven by a steric effect of dominant packing of cerium atoms at high pressure.

    • Min Wu
    • , John S. Tse
    •  & J.Z. Jiang

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