Multiscale modeling of organic materials:from the Morphology Up

The field of organic electronics promises a host of thin, lightweight, flexible, and environmentally friendly electronic devices. Such devices are made possible by the use of organic materials, materials constituted by organic molecules which possibly possess interesting electronic properties. To fulfill this promise, scientists need to resolve one fundamental complication which finds its roots in the virtually infinite possibilities offered by organic molecules: master the relations between the molecular structure of the single molecules, their aggregate morphology and the performance of the resulting electronic device. In this context, the aim of this thesis is to demonstrate how information on the molecular organization of organic materials can be obtained by a multiscale modeling approach. The term “multiscale” designates the combined use of various modeling techniques with the aim of covering a large range of length and time scales, from the molecular-scale towards the device-scale. This allows to connect features of the single molecules to their collective structural organization and to understand how this, in turn, affects the electronic properties of the organic material, and thus of the resulting electronic device.This thesis enables multiple developments and extensions, including the possibility of simulating an ever-larger number of organic materials, while systematically connecting the obtained morphologies to the electronic properties which are fundamental to the functioning of the resulting electronic devices. Taken together, the findings of this thesis contribute to the route towards an age where the design of organic materials is based on computational models and simulations

Prediction of Electronic Properties of Radical-Containing Polymers at Coarse-Grained Resolutions

The properties of soft electronic materials depend on the coupling of electronic and conformational degrees of freedom over a wide range of spatiotemporal scales. Description of such properties requires multiscale approaches capable of, at the same time, accessing electronic properties and sampling the conformational space of soft materials. This could in principle be realized by connecting the coarse-grained (CG) methodologies required for adequate conformational sampling to conformationally-averaged electronic property distributions via backmapping to atomistic-resolution level models and repeated quantum-chemical calculations. Computational demands of such approaches, however, have hindered their application in high-throughput computer-aided soft materials discovery. Here, we present a method that, combining machine learning and CG techniques, can replace traditional backmapping-based approaches without sacrificing accuracy. We illustrate the method for an emerging class of soft electronic materials, namely non-conjugated, radical-containing polymers, promising materials for all-organic energy storage. Supervised machine learning models are trained to learn the dependence of electronic properties on polymer conformation at CG resolutions. We then parametrize CG models that retain electronic structure information, simulate CG condensed phases, and predict the electronic properties of such phases solely from the CG degrees of freedom. We validate our method by comparing it against a full backmapping-based approach, and find good agreement between both methods. This work demonstrates the potential of the proposed method to accelerate multiscale workflows, and provides a framework for the development of CG models that retain electronic structure information

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3

How ethylene glycol chains enhance the dielectric constant of organic semiconductors : molecular origin and frequency dependence

Incorporating ethylene glycols (EGs) into organic semiconductors has become the prominent strategy to increase their dielectric constant. However, EG’s contribution to the dielectric constant is due to nuclear relaxations, and therefore, its relevance for various organic electronic applications depends on the time scale of these relaxations, which remains unknown. In this work, by means of a new computational protocol based on polarizable molecular dynamics simulations, the time- and frequency-dependent dielectric constant of a representative fullerene derivative with EG side chains is predicted, the origin of its unusually high dielectric constant is explained, and design suggestions are made to further increase it. Finally, a dielectric relaxation time of ∼1 ns is extracted which suggests that EGs may be too slow to reduce the Coulombic screening in organic photovoltaics but are definitely fast enough for organic thermoelectrics with much lower charge carrier velocities

Crystal Field in Rare-Earth Complexes:From Electrostatics to Bonding

The flexibility of first-principles (ab initio) calculations with the SO-CASSCF (complete active space self-consistent field theory with a treatment of the spin-orbit (SO) coupling by state interaction) method is used to quantify the electrostatic and covalent contributions to crystal field parameters. Two types of systems are chosen for illustration: 1)The ionic and experimentally well-characterized PrCl3 crystal; this study permits a revisitation of the partition of contributions proposed in the early days of crystal field theory; and 2)a series of sandwich molecules [Ln(ηn-CnHn)2]q, with Ln=Dy, Ho, Er, and Tm and n=5, 6, and 8, in which the interaction between LnIII and the aromatic ligands is more difficult to describe within an electrostatic approach. It is shown that a model with three layers of charges reproduces the electrostatic field generated by the ligands and that the covalency plays a qualitative role. The one-electron character of crystal field theory is discussed and shown to be valuable, although it is not completely quantitative. This permits a reduction of the many-electron problem to a discussion of the energy of the seven 4f orbitals

Comparing Dimerization Free Energies and Binding Modes of Small Aromatic Molecules with Different Force Fields

Dimerization free energies are fundamental quantities that describe the strength of interaction of different molecules. Obtaining accurate experimental values for small molecules and disentangling the conformations that contribute most to the binding can be extremely difficult, due to the size of the systems and the small energy differences. In many cases, one has to resort to computational methods to calculate such properties. In this work, we used molecular dynamics simulations in conjunction with metadynamics to calculate the free energy of dimerization of small aromatic rings, and compared three models from popular online servers for atomistic force fields, namely G54a7, CHARMM36 and OPLS. We show that, regardless of the force field, the profiles for the dimerization free energy of these compounds are very similar. However, significant care needs to be taken when studying larger molecules, since the deviations from the trends increase with the size of the molecules, resulting in force field dependent preferred stacking modes; for example, in the cases of pyrene and tetracene. Our results provide a useful background study for using topology builders to model systems which rely on stacking of aromatic moieties, and are relevant in areas ranging from drug design to supramolecular assembly

Anti-carbamylated protein antibodies as a new biomarker of erosive joint damage in systemic lupus erythematosus

Background: The application of more sensitive imaging techniques, such as ultrasonography (US), changed the concept of non-erosive arthritis in systemic lupus erythematosus (SLE), underlining the need for biomarkers to identify patients developing the erosive phenotype. Anti-citrullinated peptide antibodies (ACPA), associated with erosions in inflammatory arthritis, have been identified in about 50% of patients with SLE with erosive arthritis. More recently, anti-carbamylated proteins antibodies (anti-CarP) have been associated with erosive damage in rheumatoid arthritis. We aimed to assess the association between anti-CarP and erosive damage in a large SLE cohort with joint involvement. Methods: We evaluated 152 patients (male/female patients 11/141; median age 46years, IQR 16; median disease duration 108months, IQR 168). All patients underwent blood draw to detect rheumatoid factor (RF) and ACPA (commercial enzyme-linked immunosorbent assay (ELISA) kit), and anti-CarP ("home-made" ELISA, cutoff 340aU/mL). The bone surfaces of the metacarpophalangeal and proximal interphalangeal joints were assessed by US: the presence of erosions was registered as a dichotomous value (0/1), obtaining a total score (0-20). Results: The prevalence of anti-CarP was 28.3%, similar to RF (27.6%) and significantly higher than ACPA (11.2%, p=0.003). Erosive arthritis was identified in 25.6% of patients: this phenotype was significantly associated with anti-CarP (p=0.004). Significant correlation between anti-CarP titer and US erosive score was observed (r=0.2, p=0.01). Conclusions: Significant association was identified between anti-CarP and erosive damage in SLE-related arthritis, in terms of frequency and severity, suggesting that these antibodies can represent a biomarker of severity in patients with SLE with joint involvement

Can the Dielectric Constant of Fullerene Derivatives Be Enhanced by Side-Chain Manipulation? A Predictive First-Principles Computational Study

The low efficiency of organic photovoltaic (OPV) devices has often been attributed to the strong Coulombic interactions between the electron and hole, impeding the charge separation process. Recently, it has been argued that by increasing the dielectric constant of materials used in OPVs, this strong interaction could be screened. In this work, we report the application of periodic density functional theory together with the coupled perturbed Kohn Sham method to calculate the electronic contribution to the dielectric constant for fullerene C-60 derivatives, a ubiquitous class of molecules in the field of OPVs. The results show good agreement with experimental data when available and also reveal an important undesirable outcome when manipulating the side chain to maximize the static dielectric constant: in all cases, the electronic contribution to the dielectric constant decreases as the side chain increases in size. This information should encourage both theoreticians and experimentalists to further investigate the relevance of contributions to the dielectric constant from slower processes like vibrations and dipolar reorientations for facilitating the charge separation, because electronically, enlarging the side chain of conventional fullerene derivatives only lowers the dielectric constant, and consequently, their electronic dielectric constant is upper bound by the one of C-60

Polyply:A python suite for facilitating simulations of macromolecules and nanomaterials

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle

Two decades of Martini:Better beads, broader scope

The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipid-based systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely high-throughput applications, systems with large complexity, and simulations approaching the scale of whole cells. This article is categorized under: Software > Molecular Modeling Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Computational Biochemistry and Biophysics