Automated Analysis of Soft Matter Interfaces, Interactions, and Self-Assembly with PySoftK.

Molecular dynamics simulations have become essential tools in the study of soft matter and biological macromolecules. The large amount of high-dimensional data associated with such simulations does not straightforwardly elucidate the atomistic mechanisms that underlie complex materials and molecular processes. Analysis of these simulations is complicated: the dynamics intrinsic to soft matter simulations necessitates careful application of specific, and often complex, algorithms to extract meaningful molecular scale understanding.

PUCHIK: A Python Package To Analyze Molecular Dynamics Simulations of Aspherical Nanoparticles.

Accurately describing a nanoparticle's interface is crucial for understanding its internal structure, interfacial properties, and ultimately, its functionality. While current computational methods provide reasonable descriptions for spherical and quasi-spherical nanoparticles, there remains a need for effective models for aspherical structures such as capsules and rod-like systems. This work introduces Python Utility for Characterizing Heterogeneous Interfaces and Kinetics (PUCHIK), a novel algorithm developed to describe both spherelike and aspherical nanoparticles.

Global Optimization of Molybdenum Subnanoclusters on Graphene: A Consistent Approach toward Catalytic Applications.

The development of novel subnanometer clusters (SNCs) catalysts with superior catalytic performance depends on the precise control of clusters' atomistic sizes, shapes, and accurate deposition onto surfaces. The intrinsic complexity of the adsorption process complicates the ability to achieve an atomistic understanding of the most relevant structure-reactivity relationships hampering the rational design of novel catalytic materials. In most cases, existing computational approaches rely on just a few structures to draw conclusions on clusters' reactivity thereby neglecting the complexity of the existing energy landscapes thus leading to insufficient sampling and, most likely, unreliable predictions.

Modular Software for Generating and Modeling Diverse Polymer Databases.

Machine learning methods offer the opportunity to design new functional materials on an unprecedented scale; however, building the large, diverse databases of molecules on which to train such methods remains a daunting task. Automated computational chemistry modeling workflows are therefore becoming essential tools in this data-driven hunt for new materials with novel properties, since they offer a means by which to create and curate molecular databases without requiring significant levels of user input. This ensures that well-founded concerns regarding data provenance, reproducibility, and replicability are mitigated.

Structural characterisation of nanoalloys for (photo)catalytic applications with the Sapphire library.

A non-trivial interplay rules the relationship between the structure and the chemophysical properties of a nanoparticle. In this context, characterization experiments, molecular dynamics simulations and electronic structure calculations may allow the variables that determine a given property to be pinpointed. Conversely, a rigorous computational characterization of the geometry and chemical ordering of metallic nanoparticles and nanoalloys enables discrimination of which descriptors could be linked with their stability and performance.

Conformational Heterogeneity and Interchain Percolation Revealed in an Amorphous Conjugated Polymer.

Conjugated polymers are employed in a variety of application areas due to their bright fluorescence and strong biocompatibility. However, understanding the structure of amorphous conjugated polymers on the nanoscale is extremely challenging compared to their related crystalline phases. Using a bespoke classical force field, we study amorphous poly(9,9-di--octylfluorene--benzothiadiazole) (F8BT) with molecular dynamics simulations to investigate the role that its nanoscale structure plays in controlling its emergent (and all-important) optical properties.

Scalable and Predictive Spectra of Correlated Molecules with Moment Truncated Iterated Perturbation Theory.

A reliable and efficient computation of the entire single-particle spectrum of correlated molecules is an outstanding challenge in the field of quantum chemistry, with standard density functional theory approaches often giving an inadequate description of excitation energies and gaps. In this work, we expand upon a recently introduced approach that relies on a fully self-consistent many-body perturbation theory coupled to a nonperturbative truncation of the effective dynamics at each step. We show that this yields a low-scaling and accurate method across a diverse benchmark test set that is capable of treating moderate levels of strong correlation effects, and we detail an efficient implementation for applications involving up to ∼1000 orbitals on parallel resources.

Fullerene Desymmetrization as a Means to Achieve Single-Enantiomer Electron Acceptors with Maximized Chiroptical Responsiveness.

Solubilized fullerene derivatives have revolutionized the development of organic photovoltaic devices, acting as excellent electron acceptors. The addition of solubilizing addends to the fullerene cage results in a large number of isomers, which are generally employed as isomeric mixtures. Moreover, a significant number of these isomers are chiral, which further adds to the isomeric complexity.

Switching between Local and Global Aromaticity in a Conjugated Macrocycle for High-Performance Organic Sodium-Ion Battery Anodes.

Aromatic organic compounds can be used as electrode materials in rechargeable batteries and are expected to advance the development of both anode and cathode materials for sodium-ion batteries (SIBs). However, most aromatic organic compounds assessed as anode materials in SIBs to date exhibit significant degradation issues under fast-charge/discharge conditions and unsatisfying long-term cycling performance. Now, a molecular design concept is presented for improving the stability of organic compounds for battery electrodes.

Molecular generation targeting desired electronic properties via deep generative models.

As we seek to discover new functional materials, we need ways to explore the vast chemical space of precursor building blocks, not only generating large numbers of possible building blocks to investigate, but trying to find non-obvious options, that we might not suggest by chemical experience alone. Artificial intelligence techniques provide a possible avenue to generate large numbers of organic building blocks for functional materials, and can even do so from very small initial libraries of known building blocks. Specifically, we demonstrate the application of deep recurrent neural networks for the exploration of the chemical space of building blocks for a test case of donor-acceptor oligomers with specific electronic properties.

Exploring the write-in process in molecular quantum cellular automata: a combined modelingand first-principle approach.

The molecular quantum cellular automata paradigm (m-QCA) offers a promising alternative framework to current CMOS implementations. A crucial aspect for implementing this technology concerns the construction of a device which effectively controls intramolecular charge-transfer processes. Tentative experimental implementations have been developed in which a voltage drop is created generating the forces that drive a molecule into a logic state.

Exciton-Phonon Interaction Model for Singlet Fission in Prototypical Molecular Crystals.

In singlet fission (SF), a spin-conserving splitting of one singlet exciton into two triplet excitation states, the transition between localized electronic states can be controlled and modulated by delocalized lattice phonons. In this work, we built an exciton-phonon (ex-ph) interaction model accounting local electronic states coupled with both local molecular vibrations and low frequency intermolecular phonon modes for SF in crystalline tetracene and rubrene. On the basis of the calculated electronic couplings at the equilibrium structure of the molecular dimer, a superexchange path for SF was found for tetracene while couplings between the triplet pair (TT) state and other diabatic states are zero for rubrene due to the high symmetry.

Self-Assembled Two-Dimensional Supramolecular Networks Characterized by Scanning Tunneling Microscopy and Spectroscopy in Air and under Vacuum.

We combine ambient (air) and ultrahigh vacuum (UHV) scanning tunneling microscopy (STM) and spectroscopy (STS) investigations together with density functional theory (DFT) calculations to gain a subnanometer insight into the structure and dynamic of two-dimensional (2D) surface-supported molecular networks. The planar tetraferrocene-porphyrin molecules employed in this study undergo spontaneous self-assembly via the formation of hydrogen bonded networks at the gold substrate-solution interface. To mimic liquid phase ambient deposition conditions, film formation was accomplished in UHV by electro-spraying a solution of the molecule in chloroform onto an Au(111) substrate, thereby providing access to the full spectroscopic capabilities of STM that can be hardly attained under ambient conditions.

Nonlocal Electron-Phonon Coupling in Prototypical Molecular Semiconductors from First Principles.

A substantial amount of evidence indicates a relevant role played by the nonlocal electron-phonon couplings in the mechanism of charge transport in organic semiconductors. In this work, we compute the nonlocal electron-phonon coupling for the prototypical molecular semiconductors rubrene and tetracene using the phonon modes obtained from ab initio methods. We do not make the rigid molecular approximation allowing a mixing of intra- and intermolecular modes, and we use a supercell approach to sample the momentum space.

Discrete polygonal supramolecular architectures of isocytosine-based Pt(ii) complexes at the solution/graphite interface.

Polygonal supramolecular architectures of a Pt(ii) complex including trimers, tetramers, pentamers and hexamers were self-assembled via hydrogen bonding between isocytosine moieties; their structure at the solid/liquid interface was unravelled by in situ scanning tunneling microscopy imaging. Density functional theory calculations provided in-depth insight into the thermodynamics of their formation by exploring the different energy contributions attributed to the molecular self-assembly and adsorption processes.

Switchable Negative Differential Resistance Induced by Quantum Interference Effects in Porphyrin-based Molecular Junctions.

Charge transport signatures of a carbon-based molecular switch consisting of different tautomers of metal-free porphyrin embedded between graphene nanoribbons is studied by combining electronic structure and nonequilibrium transport. Different low-energy and low-bias features are revealed, including negative differential resistance (NDR) and antiresonances, both mediated by subtle quantum interference effects. Moreover, the molecular junctions can display moderate rectifying or nonlinear behavior depending on the position of the hydrogen atoms within the porphyrin core.

Guanosine-based hydrogen-bonded 2D scaffolds: metal-free formation of G-quartet and G-ribbon architectures at the solid/liquid interface.

We report on the synthesis and self-assembly of three novel lipophilic guanosine derivatives exposing a ferrocene moiety in the C(5') position of the sugar unit. Their self-association in solution, and at the solid/liquid interface, can be tuned by varying the size and nature of the C(8)-substituent, leading to the generation of either G-ribbons, lamellar G-dimer based arrays or the G4 cation-free architectures.

Structural distortions in molecular-based quantum cellular automata: a minimal model based study.

Molecular-based quantum cellular automata (m-QCA), as an extension of quantum-dot QCAs, offer a novel alternative in which binary information can be encoded in the molecular charge configuration of a cell and propagated via nearest-neighbor Coulombic cell-cell interactions. Appropriate functionality of m-QCAs involves a complex relationship between quantum mechanical effects, such as electron transfer processes within the molecular building blocks, and electrostatic interactions between cells. The influence of structural distortions of single m-QCA are addressed in this paper within a minimal model using an diabatic-to-adiabatic transformation.