Density functional theory articles within Nature Communications

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  • Article
    | Open Access

    The transformation of CO2 with renewable hydrogen into high-value products presents a sustainable route for net-zero chemical manufacture. Here the authors introduce a LaFeO3 perovskite-mediated tandem conversion of CO2, achieving remarkable performance by separating the CO2 hydrogenation and C-C coupling domains in the catalyst system.

    • Guo Tian
    • , Zhengwen Li
    •  & Fei Wei

  • Article
    | Open Access

    Combining data science and organic synthesis to achieve the rapid and precise creation of complex molecules while controlling multiple selectivities is an emerging trend, but few successful examples are reported. Here, the authors develop an artificial neural network regression model using bond orbital data to predict chemical reactivities.

    • Shingo Harada
    • , Hiroki Takenaka
    •  & Tetsuhiro Nemoto

  • Article
    | Open Access

    Conventional ab initio calculations and machine learning provide limited information on catalytic activity and selectivity and often show discrepancy with experimental results. Here, the authors report a high-throughput virtual screening strategy to identify active and selective catalysts, leading to the discovery of Cu-Ga and Cu-Pd catalysts for CO2 electroreduction.

    • Dong Hyeon Mok
    • , Hong Li
    •  & Seoin Back

  • Article
    | Open Access

    The ability to selectively functionalize different sites on simple starting materials is a constant pursuit in organic chemistry. Here, the authors report a catalytic system to regioselectively differentiate and alkynylate different positions on azaarenes via rhodium catalysis.

    • Longlong Xi
    • , Minyan Wang
    •  & Zhuangzhi Shi

  • Article
    | Open Access

    Distinguishing the influence of oxygen functional groups in carbon materials is important but elusive. Here, the authors combine experimental and machine learning techniques and reveal that phenolic groups are more acidic than carboxylic groups.

    • Jiahua Zhou
    • , Piaoping Yang
    •  & Dionisios G. Vlachos

  • Article
    | Open Access

    The integrated CO2 capture and conversion (iCCC) technology has been booming for carbon neutrality. Here the authors optimized the Ni–CaO composite catalyst to promote iCCC involving consecutive high-temperature Calcium-looping and dry reforming of methane and illustrated their synergistic promotions at the suitable catalyst interface.

    • Bin Shao
    • , Zhi-Qiang Wang
    •  & Jun Hu

  • Article
    | Open Access

    DFT simulations may be inaccurate in modeling aqueous systems, with results depending on the choice of the exchange-correlation functional. Here, the authors present an integrative method called HF-r2SCAN-DC4 that provides near chemical accuracy in electronic structure information not only for pure water but also for molecules dissolved in it

    • Suhwan Song
    • , Stefan Vuckovic
    •  & Kieron Burke

  • Article
    | Open Access

    Density functional theory provides a formal map from the electron density to all observables of interest of a many-body system; however, maps for electronic excited states are unknown. Here, the authors demonstrate a data-driven machine learning approach for constructing multistate functionals.

    • Yuanming Bai
    • , Leslie Vogt-Maranto
    •  & William J. Glover

  • Article
    | Open Access

    Accurately computed chemisorption energies are essential for modeling catalytic conversions in heterogeneous catalysis, but are challenging to obtain. Here authors combine two approaches to improve this situation: standard DFT applied to the extended system, and small cluster models that can be treated with higher-level computational techniques to improve the description of chemical bonding.

    • Rafael B. Araujo
    • , Gabriel L. S. Rodrigues
    •  & Lars G. M. Pettersson

  • Article
    | Open Access

    Aqueous CO2 under nanoconfinement is of great importance to the carbon storage and transport in Earth. Here, the authors apply ab initio molecular dynamics simulations to study the effects of confinement and interfaces, and show that that CO(aq) reacts more in nanoconfinement than in bulk.

    • Nore Stolte
    • , Rui Hou
    •  & Ding Pan

  • Article
    | Open Access

    Energy transfer between the electromagnetic field and atoms or molecules is fundamentally interesting. Here the authors demonstrate stepwise energy transfer between broadband mid-infrared optical pulses and vibrating methylsulfonylmethane molecules in aqueous solution.

    • Martin T. Peschel
    • , Maximilian Högner
    •  & Ioachim Pupeza

  • Article
    | Open Access

    The reasons for which many low-coordinate complexes exhibit bent geometry, rather than a higher symmetry, are still under debate. Here, the authors use high-pressure crystallography to examine whether low-coordinate f-block molecules become more planar or pyramidal under pressure; which happens is dictated by the dipole moment of the complex and the volume of the planar form.

    • Amy N. Price
    • , Victoria Berryman
    •  & Polly L. Arnold

  • 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

    Catalytic ammonia synthesis continues to attract significant interest. Here, the authors develop a model to explain a large body of recent experimental data on new promoters. They find new promotion mechanism mediated by coupling between adsorption and spin polarization on the surface atoms of magnetic catalysts.

    • Ang Cao
    • , Vanessa J. Bukas
    •  & Jens K. Nørskov

  • Article
    | Open Access

    The current study explores by ab-initio molecular dynamics simuations the concept of hypervalency in amorphous chalcogenide materials, from which a unified conceptual framework for understanding chemical bonding, microscopic structures, and structure-property relationships is established.

    • T. H. Lee
    •  & S. R. Elliott

  • Article
    | Open Access

    Modelling the growth of carbon nanoclusters in shock experiments is computationally demanding. Here the authors employ a machine-learned reactive interatomic model to perform large-scale simulations of nanocarbon formation from prototypical shocked C/O-containing precursor.

    • Rebecca K. Lindsey
    • , Nir Goldman
    •  & Sorin Bastea

  • Article
    | Open Access

    Dissolution of minerals in water is ubiquitous in nature, its mechanism at the atomic level still under debate. Here, the authors investigate the dissolution mechanism of tricalcium silicate at early stage by ab initio molecular dynamics and metadynamics simulations.

    • Yunjian Li
    • , Hui Pan
    •  & Zongjin Li

  • Article
    | Open Access

    Reinforcement learning algorithms are emerging as powerful machine learning approaches. This paper introduces a novel machine-learning approach for learning in continuous action space and applies this strategy to the generation of high dimensional potential models for a wide variety of materials.

    • Sukriti Manna
    • , Troy D. Loeffler
    •  & Subramanian K. R. S. Sankaranarayanan

  • Article
    | Open Access

    Methods to functionalize inert C–H bonds are a critical focus of synthetic organic chemistry. In this work the authors use computations and experiments to uncover the mechanisms of palladium-catalysed C–H lactonizations in aromatic carboxylic acids, and explain the origin of an observed preference for functionalization of a C(sp3)–H bond over a C(sp2)–H bond in a recent report.

    • Li-Ping Xu
    • , Shaoqun Qian
    •  & Djamaladdin G. Musaev

  • Article
    | Open Access

    Although computational simulation-based natural product syntheses are in their initial stages of development, this concept can potentially become an indispensable resource in the field of organic synthesis. Here the authors report asymmetric total syntheses of several resveratrol dimers based on a comprehensive computational simulation of their biosynthetic pathways.

    • Masaya Nakajima
    • , Yusuke Adachi
    •  & Tetsuhiro Nemoto

  • Article
    | Open Access

    This combined experimental and theoretical study reveals the nature of electron transfer at graphene as grown on copper. The authors find that outer-sphere electron transfer occurs adiabatically with slower kinetics for multi- than for monolayer graphene.

    • Dan-Qing Liu
    • , Minkyung Kang
    •  & Patrick R. Unwin

  • Article
    | Open Access

    No existing density functional correctly describes the properties of water across the entire phase diagram. The authors report a data-driven many-body potential energy function based on density-corrected SCAN functional that quantitatively reproduces the energetics of gas-phase water clusters, and correctly predicts the properties of liquid water.

    • Saswata Dasgupta
    • , Eleftherios Lambros
    •  & Francesco Paesani

  • Article
    | Open Access

    Layered boron compounds attract enormous interest in applications. This work reports first-principles calculations coupled with global optimization to show that the outer boron surface in MgB2 nanosheets undergo disordering and clustering, which is experimentally confirmed in synthesized MgB2 nanosheets.

    • Sichi Li
    • , Harini Gunda
    •  & Brandon C. Wood

  • Article
    | Open Access

    Developments in the field of two-dimensional van der Waals materials offer big promise for device applications. This study reports a first-principle investigation on the dielectric properties of 32 exfoliable two-dimensional layered dieletrics for assessing the prospects of these materials in devices.

    • Mehrdad Rostami Osanloo
    • , Maarten L. Van de Put
    •  & William G. Vandenberghe

  • Article
    | Open Access

    The conversion of N2 and CO2 into urea through electrochemical reactions under ambient conditions represents a novel green urea synthesis method. Here, the authors demonstrate that two-dimensional transition metal borides can serve as effective catalysts for electrochemical urea synthesis.

    • Xiaorong Zhu
    • , Xiaocheng Zhou
    •  & Yafei Li

  • Article
    | Open Access

    Electrocatalytic conversion of nitrogen oxides to value-added chemicals is a promising strategy for mitigating the imbalance in the global nitrogen cycle. Here, the authors present iron–nitrogen-doped carbon as an efficient and durable electrocatalyst for selective nitric oxide reduction to hydroxylamine.

    • Dong Hyun Kim
    • , Stefan Ringe
    •  & Chang Hyuck Choi

  • Article
    | Open Access

    Spiroaromatic compounds are advantageous platforms for designing expanded aromatic systems. Herein, the authors present a tris‐spiro metalla‐aromatic Vanadium compound which forms a 40π Craig‐Möbius aromatic system.

    • Zhe Huang
    • , Yongliang Zhang
    •  & Zhenfeng Xi

  • Article
    | Open Access

    Colloidal CdSe nanocrystals hold great promise in applications due to their tunable optical spectrum. Using hybrid time-dependent density functional theory, the authors show that colloidal CdSe nanocrystals are inherently defective with a low energy spectrum dominated by dark, surface-associated excitations.

    • Tamar Goldzak
    • , Alexandra R. McIsaac
    •  & Troy Van Voorhis

  • Article
    | Open Access

    Complex interatomic interactions and diverse structures make computing the phase diagram of water very challenging. Here, a combination of machine learning and advanced free-energy methods at three levels of hybrid DFT enables the prediction of the phase diagram in close agreement with experiment.

    • Aleks Reinhardt
    •  & Bingqing Cheng

  • Article
    | Open Access

    Machine learning potentials do not account for long-range charge transfer. Here the authors introduce a fourth-generation high-dimensional neural network potential including non-local information of charge populations that is able to provide forces, charges and energies in excellent agreement with DFT data.

    • Tsz Wai Ko
    • , Jonas A. Finkler
    •  & Jörg Behler

  • Article
    | Open Access

    Semilocal density functionals, while computationally efficient, do not account for non-local correlation. Here, the authors propose a machine-learning approach to DFT that leads to non-local and transferable functionals applicable to non-covalent, ionic and covalent interactions across system of different sizes.

    • Johannes T. Margraf
    •  & Karsten Reuter

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