Publications

2021

  • Improved Description of Atomic Environments using Low-cost Polynomial Functions with Compact Support
    Martin Peter Bircher, Andreas Singraber and Christoph Dellago, Mach. learn.: sci. technol. 2021, in press https://doi.org/10.1088/2632-2153/abf817 (open access)

  • Microswimmers learning chemotaxis with genetic algorithms
    Benedikt Hartl , Maximilian Hübla , Gerhard Kahl , and Andreas Zöttl, PNAS 2021, Vol. 118, No. xx e2019683118
    https://doi.org/10.1073/pnas.2019683118 (open access)

  • Transition Path Sampling as Markov Chain Monte Carlo of Trajectories: Recent Algorithms, Software, Applications, and Future Outlook
    Peter G. Bolhuis and David W. H. Swenson, Adv. Theory Simul. 2021, 2000237. DOI: https://doi.org/10.1002/adts.202000237 (open access)

    Abstract: The development of enhanced sampling methods to investigate rare but important events has always been a focal point in the molecular simulation field. Such methods often rely on prior knowledge of the reaction coordinate. However, the search for this reaction coordinate is at the heart of the rare event problem. Transition path sampling (TPS) circumvents this problem by generating an ensemble of dynamical trajectories undergoing the activated event. The reaction coordinate is extracted from the resulting path ensemble using variants of machine learning, making it an output of the method instead of an input. Over the last 20 years, since its inception, many extensions of TPS have been developed. Perhaps surprisingly, large‐scale TPS simulations on complex molecular systems have become possible only recently. Other important developments include the transition interface sampling (TIS) methodology to compute rate constants, the application to multiple states, and adaptive path sampling. The development of OpenPathSampling and PyRETIS has enabled easy and flexible use and implementation of these and other novel path sampling algorithms. In this progress report, a brief overview of recent developments, novel algorithms, and software is given. In addition, several application areas are discussed, and a future outlook for the next decade is given.

2020

  • Towards blood flow in the virtual human: efficient self-coupling of HemeLB
    J. W. S. McCullough, R. A. Richardson, A. Patronis, R. Halver, R. Marshall, M. Ruefenacht, B. J. N. Wylie, T. Odaker, M. Wiedemann, B. Lloyd, E. Neufeld, G. Sutmann, A. Skjellum, D. Kranzlmüller and P. V. Coveney
    Interface Focus 2020, 11: 20190119
    DOI: http://dx.doi.org/10.1098/rsfs.2019.0119 (open access)

    Abstract: Many scientific and medical researchers are working towards the creation of a virtual human—a personalized digital copy of an individual—that will assist in a patient’s diagnosis, treatment and recovery. The complex nature of living systems means that the development of this remains a major challenge. We describe progress in enabling the HemeLB lattice Boltzmann code to simulate 3D macroscopic blood flow on a full human scale. Significant developments in memory management and load balancing allow near linear scaling performance of the code on hundreds of thousands of computer cores. Integral to the construction of a virtual human, we also outline the implementation of a self-coupling strategy for HemeLB. This allows simultaneous simulation of arterial and venous vascular trees based on human-specific geometries.

  • Quantum Monte Carlo determination of the principal Hugoniot of deuterium
    Michele Ruggeri, Markus Holzmann, David M. Ceperley, and Carlo Pierleoni
    Phys. Rev. B 2020, 102, 144108
    DOI: https://doi.org/10.1103/PhysRevB.102.144108
    Open access version

    Abstract: We present coupled electron-ion Monte Carlo results for the principal Hugoniot of deuterium together with an accurate study of the initial reference state of shock-wave experiments. We discuss the influence of nuclear quantum effects, thermal electronic excitations, and the convergence of the potential energy surface by wave-function optimization within variational Monte Carlo and projection quantum Monte Carlo methods. Compared to a previous study, our calculations also include low pressure-temperature (P,T) conditions resulting in close agreement with experimental data, while our revised results at higher (P,T) conditions still predict a more compressible Hugoniot than experimentally observed.

  • Unfolding the prospects of computational (bio)materials modelling
    G. J. Agur Sevink, Jozef Adam Liwo, Pietro Asinari, Donal MacKernan, Giuseppe Milano, and Ignacio Pagonabarraga
    J. Chem. Phys. 2020, 153, 100901
    DOI: https://doi.org/10.1063/5.0019773
    Open access version

    Synopsis: This is a community-driven review on the history, developments, and challenges facing coarse graining (CG) and multiscale simulation (MS)  and a set of recommendations on how the latter may be addressed. 

  • PANNA: Properties from Artificial Neural Network Architectures
    Ruggero Lot, Franco Pellegrini, Yusuf Shaidu, Emine Küçükbenli
    Comput. Phys. Commun. 2020, 256, 107402
    DOI: https://doi.org/10.1016/j.cpc.2020.107402
    Open access version

    Abstract: Prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package ‘‘Properties from Artificial Neural Network Architectures’’ (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

  • A molecular perspective on Tully models for nonadiabatic dynamics
    Lea M. Ibele and Basile F. E. Curchod
    Phys. Chem. Chem. Phys. 2020, 22, 15183
    DOI: https://doi.org/10.1039/D0CP01353F (open access)

    Synopsis: Over the past decades, an important number of methods have been developed to simulate the nonadiabatic dynamics of molecules, that is, the dynamics of molecules beyond the Born–Oppenheimer approximation. These nonadiabatic methods differ in the way they approximate the dynamics emanating from the time-dependent molecular Schrödinger equation. In 1990, Tully devised a series of three one-dimensional model systems to test the approximations of the method called trajectory surface hopping. The Tully models were designed to probe different scenarios of nonadiabatic processes, such as single and multiple nonadiabatic (re)crossings. These one-dimensional models rapidly became the testbed for any new nonadiabatic dynamics strategy. In this work, we present a molecular perspective to the Tully models by highlighting a correspondence between these simple one-dimensional models and processes happening during the excited-state dynamics of molecules. More importantly, each of these nonadiabatic processes can be connected to a given exemplary molecular system, and we propose here three molecules that could serve as molecular Tully models, reproducing some of the key features of the original models but this time in a high-dimensional space. 

  • Automated high-throughput Wannierisation
    Valerio Vitale, Giovanni Pizzi, Antimo Marrazzo, Jonathan R. Yates, Nicola Marzari and Arash A. Mostofi, npj Comput Mater 2020, 6, 66
    DOI: https://doi.org/10.1038/s41524-020-0312-y (open access)

    Synopsis: Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space.

  • The CECAM Electronic Structure Library and the modular software development paradigm
    Micael J. T. Oliveira, Nick Papior, Yann Pouillon, Volker Blum, Emilio Artacho, Damien Caliste, Fabiano Corsetti, Stefano de Gironcoli, Alin M. Elena, Alberto Garcia, Victor M. Garcia-Suarez, Luigi Genovese, William P. Huhn, Georg Huhs, Sebastian Kokott, Emine Kucukbenli, Ask H. Larsen, Alfio Lazzaro, Irina V. Lebedeva, Yingzhou Li, David Lopez-Duran, Pablo Lopez-Tarifa, Martin Luders, Miguel A. L. Marques, Jan Minar, Stephan Mohr, Arash A. Mostofi, Alan O’Cais, Mike C. Payne, Thomas Ruh, Daniel G. A. Smith, Jose M. Soler, David A. Strubbe, Nicolas Tancogne-Dejean, Dominic Tildesley, Marc Torrent, Victor Wen-zhe Yu

    J. Chem. Phys. 2020, 153, 024117
    DOI: 10.1063/5.0012901
    Open access version

    Synopsis: The electronic structure library project is an initiative to stimulate, coordinate and amplify the efforts in library sharing already started within the electronic structure community. It was initiated by CECAM, which continues its support together with E-CAM, spearheading a push within the community for a better model of electronic structure software development which, it is hoped, will enhance dynamism, versatility, maintainability and optimisation of electronic structure codes. It is believed it will also allow the re-engineering efforts needed for deployment of electronic codes on novel computer architectures to be carried out more efficiently, widely, and by professionals close to hardware companies and HPC centres.

  • Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions
    Benedikt Hartl, Shubham Sharma, Oliver Brügner, Stijn F. L. Mertens, Michael Walter, and Gerhard Kahl
    J. Chem. Theory Comput. 2020, 16, 8, 5227–5243
    DOI: https://doi.org/10.1021/acs.jctc.9b01251 (open access)

    Synopsis: With this paper we propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on metallic surfaces under electrochemical conditions. 

  • Gap variability upon packing in organic photovoltaics
    D. López-Durán , Etienne Plésiat, Michal Krompiec and Emilio Artacho, PLoS ONE 2020, 15(6): e0234115
    DOI: https://doi.org/10.1371/journal.pone.0234115 (open access)

    Abstract:
    The variation of the HOMO-LUMO band gap is explored for varying packing arrangements of the 4mod BT-4TIC donor-acceptor molecule pair, by means of a high-throughput ab-initio random structure search of packing possibilities. 350 arrangements of the dimer have been relaxed from initial random dispositions, using non-local density-functional theory. We find that the electronic band gap varies within 0.3 eV, and that this magnitude, the binding energy, and the geometry are not significantly correlated. A clearly favoured structure is found with a binding energy of 1.75±0.07 eV, with all but three other arrangements displaying values of less than one third of this highest binding one, which involves the aliphatic chain of 4TIC.

  • Adiabatic motion and statistical mechanics via mass-zero constrained dynamics
    Sara Bonella, Alessandro Coretti, Rodolphe Vuilleumier and Giovanni Ciccotti, Phys. Chem. Chem. Phys. 2020, 22, 10775-10785
    DOI: 10.1039/D0CP00163E
    Pre-print version (open access): https://arxiv.org/abs/2001.03556

    Abstract: In recent work [Coretti et al.J. Chem. Phys., 2018, 149, 191102], a new algorithm to solve numerically the dynamics of the shell model for polarization was presented. The approach, broadly applicable to systems involving adiabatically separated dynamical variables, employs constrained molecular dynamics to strictly enforce the condition that the force on the fast degrees of freedom, modeled as having zero mass, is null at each time step. The algorithm is symplectic and fully time reversible, and results in stable and efficient propagation. In this paper we complete the discussion of the mechanics of mass-zero constrained dynamics by showing how to adapt it to problems where the fast degrees of freedom must satisfy additional conditions. This extension includes, in particular, the important case of first principles molecular dynamics. We then consider the statistical mechanics of the mass-zero constrained dynamical system demonstrating that the marginal probability sampled by the dynamics in the physical phase space recovers the form of the Born–Oppenheimer probability density. The effectiveness of the approach and the favorable scaling of the algorithm with system size are illustrated in test calculations of solid Na via orbital-free density functional dynamics.

  • Towards extreme scale dissipative particle dynamics simulations using multiple GPGPUs
    J. Castagna, X. Guo, M. Seaton and A. O’Cais, Comput. Phys. Commun. 2020, 251, 107159
    DOI: 10.1016/j.cpc.2020.107159 (open access)

    Abstract: A multi-GPGPU development for Mesoscale Simulations using the Dissipative Particle Dynamics method is presented. This distributed GPU acceleration development is an extension of the DL_MESO package to MPI+CUDA in order to exploit the computational power of the latest NVIDIA cards on hybrid CPU–GPU architectures. Details about the extensively applicable algorithm implementation and memory coalescing data structures are presented. The key algorithms’ optimizations for the nearest-neighbour list searching of particle pairs for short range forces, exchange of data and overlapping between computation and communications are also given. We have carried out strong and weak scaling performance analyses with up to 4096 GPUs. A two phase mixture separation test case with 1.8 billion particles has been run on the Piz Daint supercomputer from the Swiss National Supercomputer Center. With CUDA aware MPI, proper GPU affinity, communication and computation overlap optimizations for multi-GPU version, the final optimization results demonstrated more than 94% efficiency for weak scaling and more than 80% efficiency for strong scaling. As far as we know, this is the first report in the literature of DPD simulations being run on this large number of GPUs. The remaining challenges and future work are also discussed at the end of the paper.

  • Wannier90 as a community code: new features and applications
    G. Pizzi, V. Vitale, N. Marzari, D. Vanderbilt, I. Souza, A. A Mostofi, J. R Yates, et al.
    J. Phys.: Condens. Matter 2020, 32 165902
    DOI: https://doi.org/10.1088/1361-648X/ab51ff (open access)

    Synopsis: In the past few years the development of Wannier90 has transitioned to a community-driven model; this has resulted in a number of new developments that have been recently released in Wannier90 v3.0. In this article we describe these new functionalities

2019

  • Atomistic insight into the kinetic pathways for Watson-Crick to Hoogsteen transitions in DNA
    Vreede J, Pérez de Alba Ortíz A, Bolhuis PG, and Swenson DWH, Nucleic Acids Research 2019, Vol. 47, No. 21, 11069–11076
    DOI: 10.1093/nar/gkz837 (open access)

    Synopsis: DNA predominantly contains Watson–Crick (WC) base pairs, but a non-negligible fraction of base pairs are in the Hoogsteen (HG) hydrogen bonding motif at any time. In the HG motif, the purine is “upside down” compared to the WC motif. Two classes of mechanism have been proposed for the transition between these motifs: one where the base pair stays inside the confines of the helical backbone, and one where one base flips outside of the helical backbone before returning in the “upside down” HG conformation. The transitions between WC and HG may play a role in recognition and replication, but are difficult to investigate because they occur quickly, but only rarely. To gain insight into the mechanisms for this process, researchers performed transition path sampling simulations on a model nucleotide sequence in which an adenine-thymine base pair changes from WC to HG, and found that the outside transition was strongly preferred. Simulated rates and free energy differences agree with experiments, the simulations provide highly detailed insights into the mechanisms of this process.

  • Local control theory for supercomputing qubits
    M. Mališ, P. KI. Barkoutsos, M. Ganzhorn, S. Filipp, D. J. Egger, S. Bonella and I. Tavernelli, Phys. Rev. A 99, 052316
    DOI: 10.1103/PhysRevA.99.052316 (open access)

    Synopsis: In this work, we develop a method to design control pulses for fixed-frequency superconducting qubits coupled via tunable couplers based on local control theory, an approach commonly employed to steer chemical reactions. Local control theory provides an algorithm for the monotonic population transfer from a selected initial state to a desired final state of a quantum system through the on-the-fly shaping of an external pulse. The method, which only requires a unique forward time-propagation of the system wavefunction, can serve as starting point for additional refinements that lead to new pulses with improved properties. Among others, we propose an algorithm for the design of pulses that can transfer population in a reversible manner between given initial and final states of coupled fixed-frequency superconducting qubits.

  • The Fluctuation−Dissipation Theorem as a Diagnosis and Cure for Zero-Point Energy Leakage in Quantum Thermal Bath Simulations
    Etienne Mangaud, Simon Huppert, Thomas Plé, Philippe Depondt, Sara Bonella, Fabio Finocchi, J. Chem. Theory Comput. 2019, 15, 2863-2880
    DOI: 10.1021/acs.jctc.8b01164

    Synopsis: Quantum thermal bath (QTB) simulations reproduce statistical nuclear quantum effects via a Langevin equation with a coloured random force. Although this approach has proven efficient for a variety of chemical and condensed-matter problems, the QTB, as many other semiclassical methods, suffers from zero-point energy leakage (ZPEL). The absence of a reliable criterion to quantify the ZPEL without resorting to demanding comparisons with path integral based calculations has so far hindered the use of the QTB for the simulation of real systems. In this work, we establish a quantitative connection between ZPEL in the QTB framework and deviations from the quantum fluctuation-dissipation theorem (FDT) that can be monitored along the simulation. This provides a rigorous general criterion to detect and quantify the ZPEL without any a priori knowledge of the system under study.

  • Sampling the thermal Wigner density via a generalized Langevin dynamics
    Thomas Plé, Simon HuppertFabio FinocchiPhilippe Depondt, and  Sara Bonella
    J. Chem. Phys. 2019, 151, 114114
    DOI: https://doi.org/10.1063/1.5099246
    Open access version

    Synopsis: The Wigner thermal density is a function of considerable interest in the area of approximate (linearized or semiclassical) quantum dynamics where it is employed to generate initial conditions for the propagation of appropriate sets of classical trajectories. In this paper, we propose an original approach to compute the Wigner density based on a generalized Langevin equation.

  • ESPResSo++ 2.0: Advanced methods for multiscale molecular simulation
    Horacio V. Guzman, Nikita Tretyakov, Hideki Kobayashi, Aoife C. Fogarty, Karsten Kreis, Jakub Krajniak, Christoph Junghans, Kurt Kremer, Torsten Stuehn, Computer Physics Communications 2019, 238, 66–76
    DOI: 10.1016/j.cpc.2018.12.017
    Open access version

    Abstract: Molecular simulation is a scientific tool used in many fields including material science and biology. This requires constant development and enhancement of algorithms within molecular simulation software packages. Here, we present computational tools for multiscale modeling developed and implemented within the ESPResSo++ package. These include the latest applications of the adaptive resolution scheme, the hydrodynamic interactions through a lattice Boltzmann solvent coupled to particle-based molecular dynamics, the implementation of the hierarchical strategy for equilibrating long-chained polymer melts and a heterogeneous spatial domain decomposition. The software design of ESPResSo++ has kept its highly modular C++ kernel with a Python user interface. Moreover, it has been enhanced by automatic scripts that parse configurations from other established packages, providing scientists with the ability to rapidly set up their simulations.

  • Molecular Dynamics of Open Systems: Construction of a Mean‐Field Particle Reservoir
    Luigi Delle Site, Christian Krekeler, John Whittaker, Animesh Agarwal, Rupert Klein, Felix Höfling, Adv. Theory Simul. 2019, 1900014
    DOI: 10.1002/adts.201900014 (Open access)

    Synopsis: A procedure for the construction of a particle and energy reservoir for the simulation of open molecular systems is presented. The reservoir is made of non‐interacting particles (tracers), embedded in a mean‐field. The tracer molecules acquire atomistic resolution upon entering the atomistic region, while atomistic molecules become tracers after crossing the atomistic boundary.

  • OpenPathSampling: A Python Framework for Path Sampling Simulations. 1. Basics
    David W. H. Swenson, Jan-Hendrik Prinz, Frank Noe, John D. Chodera, and Peter G. Bolhuis, J. Chem. Theory Comput. 2019, 15, 813-836
    DOI: 10.1021/acs.jctc.8b00626 (Open access)

    Synopsis: OpenPathSampling (OPS) is a software package to perform path sampling simulations and other trajectory-based approaches to study rare events. The methods implemented in OPS can be used to study many kinds of problems, including drug binding and unbinding, self-assembly processes, conformational changes in biomolecules, and chemical reactions. OPS is designed to be used as a library in standard Python scripts, allowing the user to create simulation suited to study their problem. It can be run interactively with tools such as Jupyter notebooks. This paper introduces the terminology used in OPS and shows how to use OPS to perform common path sampling simulations.

  • OpenPathSampling: A Python Framework for Path Sampling Simulations. 2. Building and Customizing Path Ensembles and Sample Schemes 
    David W. H. Swenson, Jan-Hendrik Prinz, Frank Noe, John D. Chodera, and Peter G. Bolhuis, J. Chem. Theory Comput. 2019, 15, 837-856
    DOI: 10.1021/acs.jctc.8b00627 (Open access)

    Synopsis: Path sampling involves sampling many trajectories from a given “path ensemble,” which defines a set of conditions the trajectories must satisfy. As more path sampling methods have been developed, more and more types of path ensembles have been created. OpenPathSampling (OPS) introduces a new formalism to describe path ensembles, which unifies all of them under one framework. This paper describes this formalism, as well as other tools in OPS that could be useful to methods developers.

2018

  • The asymmetric Wigner bilayer
    Moritz Antlanger, Gerhard Kahl, Martial Mazars, Ladislav Samaj, Emmanuel Trizac, J. Chem. Phys. 2018, 149, 244904
    DOI: 10.1063/1.5053651
    Open access version

    Synopsis: We present a comprehensive discussion of the so-called asymmetric Wigner bilayer system, where mobile point charges, all of the same sign, are immersed into the space left between two parallel, homogeneously charged plates (with possibly different charge densities). At vanishing temperatures, the particles are expelled from the slab interior; they necessarily stick to one of the two plates, and form there ordered sublattices. Using complementary tools (analytic and numerical) we study systematically the self-assembly of the point charges into ordered ground state configurations as the inter-layer separation and the asymmetry in the charge densities are varied. The overwhelming plethora of emerging Wigner bilayer ground states can be understood in terms of the competition of two strategies of the system: the desire to guarantee net charge neutrality on each of the plates and the effort of the particles to self-organise into commensurate sublattices. 

  • Lithium Adsorption on Graphene at finite-temperature
    Yusuf Shaidu, Emine Küçükbenli, Stefano de Gironcoli, J. Phys. Chem. C 2018, 122, 36, 20800-20808
    DOI: 10.1021/acs.jpcc.8b05689
    Open access version

    Synopsis: Graphene has been proposed as a possible alternative in Li-ion batteries to state-of-the-art graphitic anode but a first principle study of its Li-adsorption behaviour at finite temperature was still lacking. We thoroughly characterised Li adsorption on graphene,  both at zero and finite temperatures by means of density functional theory (DFT), accounting for van der Waals (vdW) interactions, Monte Carlo and  cluster expansion methods to sample the system phase space. Our calculations reveal two distinct types of orderings of Li on graphene, Li-gas (dispersed Li-ion) and Licluster phases. Even when vdW is included, the Li−graphene interaction is mainly electrostatic and phase separation to pristine graphene and bulk Li is energetically favourable. However, at finite temperatures, entropy allows the lesser-ordered Li-gas and Li-cluster states to be more favourable at sufficiently low concentrations: at temperatures below 400 K and concentrations below 1Li:6C, Li-gas and Li-cluster phases coexist whereas at higher concentrations, only clusters remain stable. At temperatures above 400 K, Li-gas phase can be stabilised with respect to Li cluster or Li bulk at higher concentrations. 

  • Unimolecular FRET sensors: Simple linker designs and properties
    Shourjya Sanyal, David F. Coker, Donal MacKernan, Nano Communication Networks 2018, 18, 44–50
    DOI: 10.1016/j.nancom.2018.10.003
    Open access version

    Synopsis: The measurement of biomarkers and ligands are increasingly used to study transport, signalling, and communication in cells, and as diagnostics/prognostics of disease, or the presence of pathogens, allergens and pollutants in foods, and the environment. Accurate measurement in assays or cellular environments is important, and protein-based biosensors can be used in this context. Using simple Coarse-Grained (CG) models of unimolecular fusion protein based FRET sensors of target ligands, the authors address important questions in this paper including: Can simple CG models reproduce qualitatively experimental results? Is there an advantage in replacing flexible protein linkers with hinge-like peptides? The answers to these and other questions are disclosed in the paper.

  • Adaptive resolution molecular dynamics technique: Down to the essential
    Christian Krekeler, Animesh Agarwal, Christoph Junghans, Matej Praprotnik, and Luigi Delle Site, J. Chem. Phys. 2018, 149, 024104
    DOI: 10.1063/1.5031206
    Open access version

    Synopsis: In this paper the authors study the application of the thermodynamic force in the coupling region of an adaptive resolution molecular dynamics simulation (AdResS) approach which assures thermodynamic equilibrium and proper exchange of molecules between atomistically resolved and coarse-grained regions.


  • Probing spatial locality in ionic liquids with the grand canonical adaptive resolution molecular dynamics technique
    B. Shadrack Jabes, C. Krekeler, R. Klein, and L. Delle Site, J. Chem. Phys.  148, 193804 (2018)
    DOI: 10.1063/1.5009066
    Open access version

  • Force Field Parametrization of Metal Ions from Statistical Learning Techniques
    Francesco Fracchia, Gianluca Del Frate, Giordano Mancini, Walter Rocchia, and Vincenzo Barone, J. Chem. Theory Comput.2018, 14, 255−273
    DOI: 10.1021/acs.jctc.7b00779
    Open access version

2017

  • The opposing effects of isotropic and anisotropic attraction on association kinetics of proteins and colloids
    Arthur C. Newton, Ramses Kools, David W. H. Swenson, and Peter G. Bolhuis, J. Chem. Phys.147, 155101(2017)
    DOI: 10.1063/1.5006485
    Open access version

  • ζ-Glycine: insight into the mechanism of a polymorphic phase transition
    Craig L. Bull, Giles Flowitt-Hill, Stefano de Gironcoli, Emine Küçükbenli, Simon Parsons, Cong Huy Pham, Helen Y. Playforda and Matthew G. Tucker
    IUCrJ, (2017). 4, 569–574
    DOI: 10.1107/S205225251701096X
    Open access version

  • A parallel orbital-updating based plane-wave basis method for electronic structure calculations
    Yan Pan, Xiaoying Dai, Stefano de Gironcoli, Xin-Gao Gong, Gian-Marco Rignanese and Aihui Zhou, J. Comput. Phys.2017, 348, 482-492
    DOI: 10.1016/j.jcp.2017.07.033
    Open access version




2016


  • Equilibrium structures of anisometric, quadrupolar particles confined to a monolayer
    Thomas HeinemannMoritz AntlangerMartial MazarsSabine H. L. Klapp, and Gerhard Kahl
    J. Chem. Phys. 2016, 144, 074504
    DOI: https://doi.org/10.1063/1.4941585
    Open access version
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