Shared metadata for data-centric materials science.

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles () must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments.

Molecular Simulation Strategies for Understanding the Degradation Mechanisms of Acrylic Polymers.

Acrylic polymers, commonly used in paints, can degrade over time by several different chemical and physical mechanisms, depending on structure and exposure conditions. While exposure to UV light and temperature results in irreversible chemical damage, acrylic paint surfaces in museums can also accumulate pollutants, such as volatile organic compounds (VOCs) and moisture, that affect their material properties and stability. In this work, we studied the effects of different degradation mechanisms and agents on properties of acrylic polymers found in artists' acrylic paints for the first time using atomistic molecular dynamics simulations.

Sampling rare event energy landscapes via birth-death augmented dynamics.

A common problem that affects simulations of complex systems within the computational physics and chemistry communities is the so-called sampling problem or rare event problem where proper sampling of energy landscapes is impeded by the presences of high kinetic barriers that hinder transitions between metastable states on typical simulation time scales. Many enhanced sampling methods have been developed to address this sampling problem and more efficiently sample rare event systems. An interesting idea, coming from the field of statistics, was introduced in a recent work [Lu, Lu, and Nolen, Accelerating Langevin sampling with birth-death, arXiv:1905.

The Crucial Role of Solvation Forces in the Steric Stabilization of Nanoplatelets.

The steric stability of inorganic colloidal particles in an apolar solvent is usually described in terms of the balance between three contributions: the van der Waals attraction, the free energy of mixing, and the ligand compression. However, in the case of nanoparticles, the discrete nature of the ligand shell and the solvent has to be taken into account. Cadmium selenide nanoplatelets are a special case.

Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations.

Enhanced sampling methods are indispensable in computational chemistry and physics, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods works by identifying a few slow degrees of freedom, termed collective variables (CVs), and enhancing the sampling along these CVs. Selecting CVs to analyze and drive the sampling is not trivial and often relies on chemical intuition.

Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials.

Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede the proper sampling of the free energy landscapes when using conventional molecular dynamics simulations. One such method is variationally enhanced sampling (VES), which is based on a variational principle where a bias potential in the space of some chosen slow degrees of freedom, or collective variables, is constructed by minimizing a convex functional. In practice, the bias potential is taken as a linear expansion in some basis function set.

Acrylic Paints: An Atomistic View of Polymer Structure and Effects of Environmental Pollutants.

Most of the artwork and cultural heritage objects are stored in museums under conditions that are difficult to monitor. While advanced technologies aim to control and prevent the degradation of cultural heritage objects in line with preventive conservation measures, there is much to be learned in terms of the physical processes that lead to the degradation of the synthetic polymers that form the basis of acrylic paints largely used in contemporary art. In museums, stored objects are often exposed to temperature and relative humidity fluctuations as well as airborne pollutants such as volatile organic compounds (VOCs).

Multiscale Reweighted Stochastic Embedding: Deep Learning of Collective Variables for Enhanced Sampling.

Machine learning methods provide a general framework for automatically finding and representing the essential characteristics of simulation data. This task is particularly crucial in enhanced sampling simulations. There we seek a few generalized degrees of freedom, referred to as collective variables (CVs), to represent and drive the sampling of the free energy landscape.

Erratum: Enhancing Entropy and Enthalpy Fluctuations to Drive Crystallization in Atomistic Simulations [Phys. Rev. Lett. 119, 015701 (2017)].

This corrects the article DOI: 10.1103/PhysRevLett.119.

Free-energy landscape of polymer-crystal polymorphism.

Polymorphism rationalizes how processing can control the final structure of a material. The rugged free-energy landscape and exceedingly slow kinetics in the solid state have so far hampered computational investigations. We report for the first time the free-energy landscape of a polymorphic crystalline polymer, syndiotactic polystyrene.

Mg Sensing by an RNA Fragment: Role of Mg-Coordinated Water Molecules.

RNA molecules selectively bind to specific metal ions to populate their functional active states, making it important to understand their source of ion selectivity. In large RNA systems, metal ions interact with the RNA at multiple locations, making it difficult to decipher the precise role of ions in folding. To overcome this complexity, we studied the role of different metal ions (Mg, Ca, and K) in the folding of a small RNA hairpin motif (5'-ucCAAAga-3') using unbiased all-atom molecular dynamics simulations.

Finding multiple reaction pathways of ligand unbinding.

Searching for reaction pathways describing rare events in large systems presents a long-standing challenge in chemistry and physics. Incorrectly computed reaction pathways result in the degeneracy of microscopic configurations and inability to sample hidden energy barriers. To this aim, we present a general enhanced sampling method to find multiple diverse reaction pathways of ligand unbinding through nonconvex optimization of a loss function describing ligand-protein interactions.

Frequency adaptive metadynamics for the calculation of rare-event kinetics.

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in contrast to free energies, depend on the route taken. For this reason, specific enhanced sampling methods are needed to calculate long-time scale kinetics.

Chemical potential calculations in non-homogeneous liquids.

The numerical computation of chemical potential in dense non-homogeneous fluids is a key problem in the study of confined fluid thermodynamics. To this day, several methods have been proposed; however, there is still need for a robust technique, capable of obtaining accurate estimates at large average densities. A widely established technique is the Widom insertion method, which computes the chemical potential by sampling the energy of insertion of a test particle.

Conformational Entropy as Collective Variable for Proteins.

Many enhanced sampling methods rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate descriptors has proven challenging. Here we suggest that the NMR S order parameter can be used to this effect.

Enhancing Entropy and Enthalpy Fluctuations to Drive Crystallization in Atomistic Simulations.

Crystallization is a process of great practical relevance in which rare but crucial fluctuations lead to the formation of a solid phase starting from the liquid. As in all first order first transitions, there is an interplay between enthalpy and entropy. Based on this idea, in order to drive crystallization in molecular simulations, we introduce two collective variables, one enthalpic and the other entropic.

Coarse graining from variationally enhanced sampling applied to the Ginzburg-Landau model.

A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method.

Variational Flooding Study of a S2 Reaction.

We have studied the reaction dynamics of a prototypical organic reaction using a variationally optimized truncated bias to accelerate transitions between educt and product reactant states. The asymmetric S2 nucleophilic substitution reaction of fluoromethane and chloromethane CHF + Cl ⇌ CHCl + F is considered, and many independent biased molecular dynamics simulations have been performed at 600, 900, and 1200 K, collecting several hundred transitions at each temperature. The transition times and relative rate constants have been obtained for both reaction directions.

Hierarchical Protein Free Energy Landscapes from Variationally Enhanced Sampling.

In recent work, we demonstrated that it is possible to obtain approximate representations of high-dimensional free energy surfaces with variationally enhanced sampling ( Shaffer, P.; Valsson, O.; Parrinello, M.

Electrostatic versus Resonance Interactions in Photoreceptor Proteins: The Case of Rhodopsin.

Light sensing in photoreceptor proteins is subtly modulated by the multiple interactions between the chromophoric unit and its binding pocket. Many theoretical and experimental studies have tried to uncover the fundamental origin of these interactions but reached contradictory conclusions as to whether electrostatics, polarization, or intrinsically quantum effects prevail. Here, we select rhodopsin as a prototypical photoreceptor system to reveal the molecular mechanism underlying these interactions and regulating the spectral tuning.

A variational approach to nucleation simulation.

We study by computer simulation the nucleation of a supersaturated Lennard-Jones vapor into the liquid phase. The large free energy barriers to transition make the time scale of this process impossible to study by ordinary molecular dynamics simulations. Therefore we use a recently developed enhanced sampling method [Valsson and Parrinello, Phys.

Bespoke Bias for Obtaining Free Energy Differences within Variationally Enhanced Sampling.

Obtaining efficient sampling of multiple metastable states through molecular dynamics and hence determining free energy differences is central for understanding many important phenomena. Here we present a new biasing strategy, which employs the recent variationally enhanced sampling approach (Valsson and Parrinello Phys. Rev.

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint.

Atomistic simulations play a central role in many fields of science. However, their usefulness is often limited by the fact that many systems are characterized by several metastable states separated by high barriers, leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on significantly longer timescales than one can simulate in practice.

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin.

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables.

Well-Tempered Variational Approach to Enhanced Sampling.

We propose a simple yet effective iterative scheme that allows us to employ the well-tempered distribution as a target distribution for the collective variables in our recently introduced variational approach to enhanced sampling and free energy calculations [ Valsson and Parrinello Phys. Rev. Lett.