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. We have developed a versatile and flexible software package, PySoftK (Python Soft Matter at King's College London) that provides flexible, automated computational workflows to create, model, and curate libraries of polymers with minimal user intervention. PySoftK is available as an efficient, fully tested, and easily installable Python package. Key features of the software include the wide range of different polymer topologies that can be automatically generated and its fully parallelized library generation tools. It is anticipated that PySoftK will support the generation, modeling, and curation of large polymer libraries to support functional materials discovery in the nanotechnology and biotechnology arenas.

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. To this end, we introduce a modular and open-source library, Sapphire, which may classify the structural characteristics of a given nanoparticle through several structural analysis techniques and order parameters. A special focus is geared towards using geometrical descriptors to make predictions on a given nanoparticle's catalytic activity.

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-n-octylfluorene-alt-benzothiadiazole) (F8BT) with molecular dynamics simulations to investigate the role that its nanoscale structure plays in controlling its emergent (and all-important) optical properties. Notably, we show that a giant percolating cluster exists within amorphous F8BT, which has ramifications in understanding the nature of interchain species that drive the quantum yield reduction and bathochromic shift observed in conjugated polymer-based devices and nanostructures. We also show that distinct conformations can be unravelled from within the disordered structure of amorphous F8BT using a two-stage machine learning protocol, highlighting a link between molecular conformation and ring stacking propensity. This work provides predictive understanding by which to enhance the optical properties of next-generation conjugated polymer-based devices and materials by rational, simulation-led design principles.

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. We then use this method to characterize the spectral properties of the antimalarial drug molecule artemisinin, resolving discrepancies in previous works concerning the active sites of the lowest-energy fundamental excitations of the system.

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. The opportunities presented by single-isomer, and particularly single-enantiomer, fullerenes in organic electronic materials and devices are poorly understood however. Here, ten pairs of enantiomers are separated from the 19 structural isomers of bis[60]phenyl-C61-butyric acid methyl ester, using them to elucidate important chiroptical relationships and demonstrating their application to a circularly polarized light (CPL)-detecting device. Larger chiroptical responses are found, occurring through the inherent chirality of the fullerene. When used in a single-enantiomer organic field-effect transistor, the potential to discriminate CPL with a fast light response time and with a very high photocurrent dissymmetry factor (gph  = 1.27 ± 0.06) is demonstrated. This study thus provides key strategies to design fullerenes with large chiroptical responses for use as chiral components of organic electronic devices. It is anticipated that this data will position chiral fullerenes as an exciting material class for the growing field of chiral electronic technologies.

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. The molecular design of the investigated compound, [2.2.2.2]paracyclophane-1,9,17,25-tetraene (PCT), can stabilize the neutral state by local aromaticity and the doubly reduced state by global aromaticity, resulting in an anode material with extraordinarily stable cycling performance and outstanding performance under fast-charge/discharge conditions, demonstrating an exciting new path for the development of electrode materials for SIBs and other types of batteries.

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. The recurrent neural network learned how to produce novel donor-acceptor oligomers by trading off between selected atomic substitutions, such as halogenation or methylation, and molecular features such as the oligomer's size. The electronic and structural properties of the generated oligomers can be tuned by sampling from different subsets of the training database, which enabled us to enrich the library of donor-acceptors towards desired properties. We generated approximately 1700 new donor-acceptor oligomers with a recurrent neural network tuned to target oligomers with a HOMO-LUMO gap <2 eV and a dipole moment <2 Debye, which could have potential application in organic photovoltaics.

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. However, important factors such as the electric field profile, its possible time-dependency and the influence of temperature in the overall success of charge-transfer are relevant issues to be considered in the design of a reliable device. In this work, we theoretically study the role played by these processes in the overall intramolecular charge-transfer process. We have used a Landau-Zener (LZ) model, where different time-dependent electric field profiles have been simulated. The results have been further corroborated employing density functional tight-binding method. The role played by the nuclear motions in the electron-transfer process has been investigated beyond the Born-Oppenheimer approximation by computing the effect of the external electric field in the behavior of the potential energy surface. Hence, we demonstrate that the intramolecular charge-transfer process is a direct consequence of the coherent LZ nonadiabatic tunneling and the hybridization of the diabatic vibronic states which effectively reduces the trapping of the itinerant electron at the donor group.

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. Our further ex-ph spectral density analysis and quantum dynamics simulation based on our ex-ph interaction model suggested a thermal-activated mechanism for SF in rubrene crystal via symmetry breaking by nuclear vibration, which is in agreement with recent experiments. It is also shown that thermal fluctuations of electronic couplings in both tetracene and rubrene are mostly in the same order of magnitude at room temperature, and this could be one of the reasons for both tetracene and rubrene to exhibit SF time scales within a close range (hundreds to thousands of femtoseconds) in experiments.

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. Indeed, we find that some low-frequency intramolecular modes are mixed with the rigid-molecule translations and rotations in the modes with the strongest electron-phonon coupling. To rationalize the results we propose a convenient decomposition of the delocalized lattice modes into molecular-based modes.

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. We rationalize the mechanism leading to NDR and antiresonances by providing a detailed analysis of transmission pathways and frontier molecular orbital distribution.

Efecto del suero autólogo en la reparación de la superficie ocular asociada a ojo seco / Effect of autologous serum in the repair of the ocular surface associated with dry eye

l daño de la superficie ocular asociado a la alteración de la película lagrimal causa múltiples síntomas y como tratamiento se usa el suero autólogo. Objetivos: comparar el efecto del suero autólogo sobre la reparación de la superficie ocular, preparado con dos concentraciones diferentes (80 y 20 %). Materiales y métodos: se realizó un estudio prospectivo cuasiexperimental en 25 pacientes diagnosticados con ojo seco, mediante el test de Schirmer, tbut y tinción con rosa de Bengala. Se administró colirio de suero autólogo al 80 % en el ojo derecho y al 20 % en el ojo izquierdo, y después de 30 días de utilización se realizaron nuevamente los tests. Para la preparación del suero autólogo se realizaron los procedimientos éticos y se siguió con el protocolo estandarizado de la Universidad de Lübeck, Alemania, de acuerdo con la guía Bundesãrztekammer y del Instituto Paul Ehrlich. Resultados: la aplicación de suero autólogo al 80 % y al 20 % presenta un aumentoignificativo tanto en el volumen lagrimal (Schirmer) ccomo en la estabilidad y calidad lagrimal (tbut) y se logra, además, reparación sobre la superficie ocular. No se encontraron diferencias significativas con las dos concentraciones, pero con mayores concentraciones se logra un mayor efecto sobre la producción y tiempo de ruptura de la película lagrimal (p<0,080). Conclusiones: la administración de suero autólogo como tratamiento para el ojo seco presenta reparación sobre la superficie ocular en concentraciones tanto del 20 % como del 80 %.

The ocular surface damage associated with the alteration of the tear film causes multiple symptoms, and autologous serum is used as treatment. Objectives: To compare the effect of autologous serum on the ocular surface repair, prepared with two different concentrations (80 y 20 %). Materials and methods: A quasi-experimental prospective study was carried out in 25 patients diagnosed with dry eye through the Schirmer test, tbut and Rose Bengal staining. Autologous serum eye drops were administered to 80% in the right eye and 20% in the left eye, and after 30 days of application, tests were once again performed. For the preparation of autologous serum, ethical procedures were performed and the standardized protocol at the University of Lübeck, Germany, was followed according to the Bundesãrztekammer guide and the Paul Ehrlich Institute. Results: The application of autologous serum to 80% and 20% showed a significant increase in both tear volume (Schirmer) and tear stability and quality (tbut) and, additionally, ocular surface repair is achieved. No significant differences were found with the two concentrations but with higher concentrations a greater effect on production and time of rupture of the tear film is achieved (p<0.080). Conclusions: The administration of autologous serum as a treatment for dry eye presents repair on the ocular surface in both concentrations of 80% and 20%.