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Small-molecule-based amorphous organic semiconductors (OSCs) are essential components of organic photovoltaics and organic light-emitting diodes. The charge carrier mobility of these materials is an integral and limiting factor in regard to their performance. Integrated computational models for the hole mobility, taking into account structural disorder in systems of several thousand molecules, have been the object of research in the past. Due to static and dynamic contributions to the total structural disorder, efficient strategies to sample the charge transfer parameters become necessary. In this paper, we investigate the impact of structural disorder in amorphous OSCs on the transfer parameters and charge mobilities in different materials. We present a sampling strategy for incorporating static and dynamic structural disorder which are based on QM/MM methods using semiempirical Hamiltonians and extensive MD sampling. We show how the disorder affects the distributions of HOMO energies and intermolecular couplings and validate the results using kinetic Monte Carlo simulations of the mobility. We find that dynamic disorder causes an order of magnitude difference in the calculated mobility between morphologies of the same material. Our method allows the sampling of disorder in HOMO energies and couplings, and the statistical analysis enables us to characterize the relevant time scales on which charge transfer occurs in these complex materials. The findings presented here shed light on the interplay of the fluctuating amorphous matrix with charge carrier transport and aid in the development of a better understanding of these complex processes.

Coarse grained (CG) molecular dynamics simulations are widely used to accelerate atomistic simulations but generally lack a formalism to preserve the dynamics of the system. For spherical particles, the Mori-Zwanzig approach, while computationally complex, has ameliorated this problem. Here we present an anisotropic dissipative particle dynamics (ADPD) model as an extension of this approach, which accounts for the anisotropy for both conservative and nonconservative interactions. For a simple anisotropic system we parametrize the coarse grained force field representing ellipsoidal CG particles from the full-atomistic simulation. To represent the anisotropy of the system, both the conservative and dissipative terms are approximated using the Gay-Berne (GB) functional forms via a force-matching approach. We compare our model with other CG models and demonstrate that it yields better results in both static and dynamical properties. The inclusion of the anisotropic nonconservative force preserves the microscopic dynamical details, and hence the dynamical properties, such as diffusivity, can be better reproduced by the aspherical model. By generalizing the isotropic DPD model, this framework is effective and promising for the development of the CG model for polymers, macromolecules, and biological systems.

A mixed-ligand phthalocyanine/porphyrin yttrium(III) radical double-decker complex ( DD ) was synthesized using the custom-made 5,10,15-tris(4-methoxyphenyl)-20-(4-((trimethylsilyl)ethynyl)phenyl)porphyrin. The trimethylsilyl functionality was then used to couple two such complexes into biradicals through rigid tethers. Glaser coupling was used to synthesize a short-tethered biradical ( C1 ) and Sonogashira coupling to synthesize longer-tethered ones ( C2 and C3 ). Field-swept echo-detected (FSED), saturation recovery, and spin nutation-pulsed electron paramagnetic resonance experiments revealed marked similarities of the magnetic properties of DD with those of the parent [Y(pc) 2 ] • complex, both in the solid state and in CD 2 Cl 2 /CDCl 3 4:1 frozen glasses. FSED experiments on the biradicals C2 and C3 revealed a spectral broadening with respect to the spectra of DD and [Y(pc) 2 ] • assigned to the effect of dipolar interactions in solution. Apart from the main resonance, satellite features were also observed, which were simulated with dipole-dipole pairs of shortest distances, suggesting spin delocalization on the organic tether. FSED experiments on C1 yielded spectral line shapes that could not be simulated as the integration of the off-resonance echoes was complicated by field-dependent modulations. While, for all dimers, the on-resonance spin nutation experiments yielded Rabi oscillations of the same frequencies, off-resonance nutations on C1 yielded Rabi oscillations that could be assigned to a M S = -1 to M S = 0 transition within a S = 1 multiplet. The DFT calculations showed that the trans conformation of the complexes was significantly more stable than the cis one and that it induced a marked spin delocalization over the rigid organic tether. This "spin leakage" was most pronounced for the shortest biradical C1 .

Understanding the phenomena that lead to the formation of a specific helicity in helical polymers remains a challenge even today. Various polymers have been shown to assume different helical screw-senses depending on different stimuli. Acid-base chiral amines, for example, can induce helical conformations on cis-transoid poly(4-carboxyphenyl)acetylene yielding high-intensity circular dichroism signals. There have been many experimental attempts to elucidate the driving forces involved, but the induction process remains unclear. Here, we investigate the mechanism of helical polymer formation by both Molecular Dynamics (MD) and Density Functional Theory (DFT) approaches. We find that DFT calculations and the dissociation energies between 4 monomer polymers and amines show a clear trend in the affinity of R and S conformers with clockwise and counterclockwise polymer screw-senses, respectively. The charge analysis revealed that the local charge transfer effect plays a crucial role that leads to the helical polymer-amine induction.

Adsorption and desorption of molecules are key processes in extraction and purification of biomolecules, engineering of drug carriers, and designing of surface-specific coatings. To understand the adsorption process on the atomic scale, state-of-the-art quantum mechanical and classical simulation methodologies are widely used. However, studying adsorption using a full quantum mechanical treatment is limited to picoseconds simulation timescales, while classical molecular dynamics simulations are limited by the accuracy of the existing force fields. To overcome these challenges, we propose a systematic way to generate flexible, application-specific highly accurate force fields by training artificial neural networks. As a proof of concept, we study the adsorption of the amino acid alanine on graphene and gold (111) surfaces and demonstrate the force field generation methodology in detail. We find that a molecule-specific force field with Lennard-Jones type two-body terms incorporating the 3rd and 7th power of the inverse distances between the atoms of the adsorbent and the surfaces yields optimal results, which is surprisingly different from typical Lennard-Jones potentials used in traditional force fields. Furthermore, we present an efficient and easy-to-train machine learning model that incorporates system-specific three-body (or higher order) interactions that are required, for example, for gold surfaces. Our final machine learning-based force field yields a mean absolute error of less than 4.2 kJ/mol at a speed-up of ∼10 5 times compared to quantum mechanical calculation, which will have a significant impact on the study of adsorption in different research areas.

In amorphous organic semiconductor devices, electrons and holes are transported through layers of small organic molecules or polymers. The overall performance of the device depends both on the material and the device configuration. Measuring a single device configuration requires a large effort of synthesizing the molecules and fabricating the device, rendering the search for promising materials in the vast molecular space both nontrivial and time-consuming. This effort could be greatly reduced by computing the device characteristics from the first principles. Here, we compute transport characteristics of unipolar single-layer devices of prototypical hole- and electron-transporting materials, N , N '-di(1-naphthyl)- N , N '-diphenyl-(1,1'-biphenyl)-4,4'-diamine (α-NPD) and 2,2',2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1- H -benzimidazole) (TPBi) using a first-principles multiscale approach that requires only the molecular constituents and the device geometry. This approach of generating a digital twin of the entire device can be extended to multilayer stacks and enables the computer design of materials and devices to facilitate systematic improvement of organic light-emitting diode (OLED) devices.

Interactions of biomolecules with inorganic oxide surfaces such as silica in aqueous solutions are of profound interest in various research fields, including chemistry, biotechnology, and medicine. While there is a general understanding of the dominating electrostatic interactions, the binding mechanism is still not fully understood. Here, chromatographic zonal elution and flow microcalorimetry experiments were combined with molecular dynamic simulations to describe the interaction of different capped amino acids with the silica surface. We demonstrate that ion pairing is the dominant electrostatic interaction. Surprisingly, the interaction strength is more dependent on the repulsive carboxy group than on the attracting amino group. These findings are essential for conducting experimental and simulative studies on amino acids when transferring the results to biomolecule-surface interactions.

Noncovalent interactions (NCIs) play an essential role in soft matter and biomolecular simulations. The ab initio method symmetry-adapted perturbation theory allows a precise quantitative analysis of NCIs and offers an inherent energy decomposition, enabling a deeper understanding of the nature of intermolecular interactions. However, this method is limited to small systems, for instance, dimers of molecules. Here, we present a scale-bridging approach to systematically derive an intermolecular force field from ab initio data while preserving the energy decomposition of the underlying method. We apply the model in molecular dynamics simulations of several solvents and compare two predicted thermodynamic observables-mass density and enthalpy of vaporization-to experiments and established force fields. For a data set limited to hydrocarbons, we investigate the extrapolation capabilities to molecules absent from the training set. Overall, despite the affordable moderate quality of the reference ab initio data, we find promising results. With the straightforward data set generation procedure and the lack of target data in the fitting process, we have developed a method that enables the rapid development of predictive force fields with an extra dimension of insights into the balance of NCIs.

Organic semiconductors are indispensable for today's display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i . e ., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design.

The ionization potential, electron affinity, and cation/anion polarization energies (IP, EA, P (+) , P (-) ) of organic molecules determine injection barriers, charge carriers balance, doping efficiency, and light outcoupling in organic electronics devices, such as organic light-emitting diodes (OLEDs). Computing IP and EA of isolated molecules is a common task for quantum chemistry methods. However, once molecules are embedded in an amorphous organic matrix, IP and EA values change, and accurate predictions become challenging. Here, we present a revised quantum embedding method [Friederich et al. J. Chem. Theory Comput. 2014, 10 (9), 3720-3725] that accurately predicts the dielectric permittivity and ionization potentials in three test materials, NPB, TCTA, and C60, and allows straightforward interpretation of their nature. The method paves the way toward reliable virtual screening of amorphous organic semiconductors with targeted IP/EA, polarization energies, and relative dielectric permittivity.

The adsorption and desorption of nucleic acid to a solid surface is ubiquitous in various research areas like pharmaceutics, nanotechnology, molecular biology, and molecular electronics. In spite of this widespread importance, it is still not well understood how the negatively charged deoxyribonucleic acid (DNA) binds to the negatively charged silica surface in an aqueous solution. In this article, we study the adsorption of DNA to the silica surface using both modeling and experiments and shed light on the complicated binding (DNA to silica) process. The binding agent mediated DNA adsorption was elegantly captured by cooperative Langmuir model. Bulk-depletion experiments were performed to conclude the necessity of a positively charged binding agent for efficient DNA binding, which complements the findings from the model. A profound understanding of DNA binding will help to tune various processes for efficient nucleic acid extraction and purification. However, this work goes beyond the DNA binding and can shed light on other binding agent mediated surface-surface, surface-molecule, molecule-molecule interaction.

Metal-organic framework (MOF)-based separators in Li-ion batteries (LIBs) have the potential to improve the battery performance. The mobility and conduction of lithium and organic ionic liquids (ILs) in these materials acting as (quasi) solid-state electrolytes are crucial for the battery power output. Here, we investigate the mobility of a Li-based IL in MOF nanopores and unveil the details of the conduction mechanism by molecular dynamics (MD) simulations. A complex conductivity depending on the Li-IL loading and on the IL composition is observed. Most importantly, the presence of Li prevents the collapse of the conductivity at high IL loadings. The fully atomistic MD simulations including guest-guest and guest-host interactions elucidate the competing mechanisms: Li follows a Grotthuss-like conduction mechanism with large mobility. While at small pore fillings, the Li conduction is limited by the large distance between the anions facilitating the Grotthuss-like conduction; the conduction at high pore fillings is governed by field-induced concentration inhomogeneities. Because of the small MOF pore windows, which hinders the simultaneous passage of the large IL cations and anions in opposite directions, the IL shows field-induced MOF pore blocking and ion bunching. The regions of low anion concentration and high cation concentration represent barriers for Li, decreasing its mobility. In comparison to Li-free IL, the IL bunching effect is attenuated by the formation of charge-neutral Li-anion complexes, resulting in a tremendously increased conductivity at maximum pore filling. The exploitation of this mechanism may enhance the development of advanced batteries based on IL and nanoporous separators.

Helical wrapping by conjugated polymer has been demonstrated as a powerful tool for the sorting of single-walled carbon nanotubes (SWCNTs) according to their electronic type, chiral index, and even handedness. However, a method of one-step extraction of left-handed ( M ) and right-handed ( P ) semiconducting SWCNTs (s-SWCNTs) with subsequent cleavage of the polymer has not yet been published. In this work, we designed and synthesized one pair of acid cleavable polyfluorenes with defined chirality for handedness separation of s-SWCNTs from as-produced nanotubes. Each monomer contains a chiral center on the fluorene backbone in the 9-position, and the amino and carbonyl groups in the 2- and 7-positions maintain the head-to-tail regioselective polymerization resulting in polyimines with strictly all-( R ) or all-( S ) configuration. The obtained chiral polymers exhibit a strong recognition ability toward left- or right-handed s-SWCNTs from commercially available CoMoCAT SWCNTs with a sorting process requiring only bath sonication and centrifugation. Interestingly, the remaining polymer on each single nanotube, which helps to prevent aggregation, does not interfere with the circular dichroism signals from the nanotube at all. Therefore, we observed all four interband transition peaks (E 11 , E 22 , E 33 , E 44 ) in the circular dichroism (CD) spectra of the still wrapped optically enriched left-handed and right-handed (6,5) SWCNTs in toluene. Binding energies obtained from molecular dynamics simulations were consistent with our experimental results and showed a significant preference for one specific handedness from each chiral polymer. Moreover, the imine bonds along the polymer chains enable the release of the nanotubes upon acid treatment. After s-SWNT separation, the polymer can be decomposed into monomers and be cleanly removed under mild acidic conditions, yielding dispersant-free handedness sorted s-SWNTs. The monomers can be almost quantitatively recovered to resynthesize the chiral polymer. This approach enables high selective isolation of polymer-free s-SWNT enantiomers for their further applications in carbon nanotube (CNT) devices.

Understanding and controlling the driving forces for molecular alignment in optoelectronic thin-film devices is of crucial importance for improving their performance. In this context, the preferential orientation of organometallic iridium complexes is in the focus of research to benefit from their improved light-outcoupling efficiencies in organic light-emitting diodes (OLEDs). Although there has been great progress concerning the orientation behavior for heteroleptic Ir complexes, the mechanism behind the alignment of homoleptic complexes is still unclear yet. In this work, we present a sky-blue phosphorescent dye that shows variable alignment depending on systematic modifications of the ligands bound to the central iridium atom. From an optical study of the transition dipole moment orientation and the electrically accessible alignment of the permanent dipole moment, we conclude that the film morphology is related to both the aspect ratio of the dye and the local electrostatic interaction of the ligands with the film surface during growth. These results indicate a potential strategy to actively control the orientation of iridium-based emitters for the application in OLEDs.

Lanthanide-based crystalline coatings have a great potential for energy-conversion devices, but until now luminescent surface-anchored materials were difficult to fabricate. Thin films, called lanthanides surface-mounted metal-organic frameworks (SURMOFs) with tetrasubstituted halide (fluorine, chlorine, and bromine) terephthalic acid derivative linkers as a basic platform for optical devices, exhibit a high quantum yield of fluorescence visible to the naked eyes under ambient light. We show that we can tune the luminescent properties in thin films by halide substitution, which affords control over the molecular structure of the material. We rationalize the mechanism for the modulation of the photophysical properties by "antenna effect", which controls the energy transfer and quantum yields using experimental and theoretical techniques for chelated lanthanides as a function of the type of atom substitutions at the phenyl rings and the resulting dihedral angle between phenyl rings in the linkers and carboxylate groups.

We combine top-down and bottom-up nanolithography to optimize the coupling of small molecular spin ensembles to 1.4 GHz on-chip superconducting resonators. Nanoscopic constrictions, fabricated with a focused ion beam at the central transmission line, locally concentrate the microwave magnetic field. Drops of free-radical molecules have been deposited from solution onto the circuits. For the smallest ones, the molecules were delivered at the relevant circuit areas by means of an atomic force microscope. The number of spins N eff effectively coupled to each device was accurately determined combining Scanning Electron and Atomic Force Microscopies. The collective spin-photon coupling constant has been determined for samples with N eff ranging between 2 × 10 6 and 10 12 spins, and for temperatures down to 44 mK. The results show the well-known collective enhancement of the coupling proportional to the square root of N eff . The average coupling of individual spins is enhanced by more than 4 orders of magnitude (from 4 mHz up to above 180 Hz), when the transmission line width is reduced from 400 μm down to 42 nm, and reaches maximum values near 1 kHz for molecules located on the smallest nanoconstrictions.

1-Hexyne monomers were potentiostatically electropolymerized upon confinement in 1D channels of a surface-mounted metal-organic framework Cu(BDC) (SURMOF-2). A layer-by-layer deposition method allowed for SURMOF depostition on substrates with prepatterned electrodes, making it possible to characterize electrical conductivity in situ, i.e., without having to delaminate the conductive polymer thin film. Successful polymerization was evidenced by mass spectroscopy, and the electrical measurements demonstrated an increase of the electrical conductivity of the MOF material by 8 orders of magnitude. Extensive DFT calculations revealed that the final conductivity is limited by electron hopping between the conductive oligomers.

Photonic crystals are solids with regular structures having periodicities comparable to the wavelength of light. Here, we showcase the photomodulation of the refractive index of a crystalline material and present a quasi-one-dimensional photonic crystal with remote-controllable optical properties. The photonic material is composed of layers of TiO 2 and films of a nanoporous metal-organic framework (MOF) with azobenzene side groups. While the rigid MOF lattice is unaffected, the optical density is reversibly modified by the light-induced trans - cis -azobenzene isomerization. Spectroscopic ellipsometry and precise DFT calculations show the optical-density change results from the different orbital localizations of the azobenzene isomers and their tremendously different oscillator strengths. The photomodulation of the MOF refractive index controls the optical properties of the quasi-one-dimensional photonic crystal with Bragg reflexes reversibly shifted by more than 4 nm. This study may path the way to photoswitchable photonic materials applied in advanced, tunable optical components and lens coatings and in light-based information processing.

Owing to their extraordinary magnetic properties and low-cost production, iron oxide nanoparticles (IONs) are in the focus of research. In order to better understand interactions of IONs with biomolecules, a tool for the prediction of the propensity of different peptides to interact with IONs is of great value. We present an effective implicit surface model (EISM), which includes several interaction models. Electrostatic interactions, van der Waals interactions, and entropic effects are considered for the theoretical calculations. However, the most important parameter, a surface accessible area force field contribution term, derives directly from experimental results on the interactions of IONs and peptides. Data from binding experiments of ION agglomerates to different peptides immobilized on cellulose membranes have been used to parameterize the model. The work was carried out under defined environmental conditions; hence, effects because of changes, for example structure or solubility by changing the surroundings, are not included. EISM enables researchers to predict the binding of peptides to IONs, which we then verify with further peptide array experiments in an iterative optimization process also presented here. Negatively charged peptides were identified as best binders for IONs in Tris buffer. Furthermore, we investigated the constitution of peptides and how the amount and position of several amino acid side chains affect peptide-binding. The incorporation of glycine leads to higher binding scores compared to the incorporation of cysteine in negatively charged peptides.

Room-temperature ionic liquids (ILs) are a unique, novel class of designer solvents and materials with exclusive properties, attracting substantial attention in fields like energy storage and supercapacitors as well as in ion-based signal processing and electronics. For most applications, ILs need to be incorporated or embedded in solid materials like porous hosts. We investigate the dynamic structure of ILs embedded in well-defined pores of metal-organic frameworks (MOFs). The experimental data combined with molecular dynamics simulations unveil astonishing dynamic properties of the IL in the MOF nanoconfinement. At low IL loadings, the ions drift in the pores along the electric field, whereas at high IL loadings, collective field-induced interactions of the cations and anions lead to blocking the transport, thus suppressing the ionic mobility and tremendously decreasing the conductivity. The mutual pore blockage causes immobilized ions in the pores, resulting in a highly inhomogeneous IL density and bunched-up ions at the clogged pores. These results provide novel molecular-level insights into the dynamics of ILs in nanoconfinement, significantly enhancing the tunability of IL material properties.

Many molecules used to fabricate organic semiconductor devices carry an intrinsic dipole moment. Anisotropic orientation of such molecules in amorphous organic thin films during the deposition process can lead to the spontaneous buildup of an electrostatic potential perpendicular to the film. This so-called giant surface potential (GSP) effect can be exploited in organic electronics applications and was extensively studied in experiment. However, presently, an understanding of the molecular mechanism driving the orientation is lacking. Here, we model the physical vapor deposition process of seven small organic molecules employed in organic light-emitting diode applications with atomistic simulations. We are able to reproduce experimental results for a wide range of strength of the GSP effect. We find that the electrostatic interaction between the dipole moments of the molecules limits the GSP strength and identify short-range van der Waals interactions between the molecule and the surface during deposition as the driving force behind the anisotropic orientation. We furthermore show how the GSP effect influences the energy levels responsible for charge transport, which is important for the design of organic semiconductors and devices.

In the past, nanoporous metal-organic frameworks (MOFs) have been mostly studied for their huge potential with regard to gas storage and separation. More recently, the discovery that the electrical conductivity of a widely studied, highly insulating MOF, HKUST-1, improves dramatically when loaded with guest molecules has triggered a huge interest in the charge carrier transport properties of MOFs. The observed high conductivity, however, is difficult to reconcile with conventional transport mechanisms: neither simple hopping nor band transport models are consistent with the available experimental data. Here, we combine theoretical results and new experimental data to demonstrate that the observed conductivity can be explained by an extended hopping transport model including virtual hops through localized MOF states or molecular superexchange. Predictions of this model agree well with precise conductivity measurements, where experimental artifacts and the influence of defects are largely avoided by using well-defined samples and the Hg-drop junction approach.

The origin of the astonishing properties of recently discovered ultrastable nanoglasses is presently not well understood. Nanoglasses appear to exhibit density variations not common in bulk glasses and differ significantly in thermal, magnetic, biocompatible, and mechanic properties from the bulk materials of the same composition. Here, we investigate a generic model system that permits modeling of both the physical vapor deposition process (PVD) of the nanoparticles and their consolidation into a nanoglass. We performed molecular dynamics simulations to investigate the PVD process generating nanometer-sized noncrystalline clusters and the formation of the PVD-nanoglass when these nanoclusters are consolidated. In agreement with the experiments, we find that the resulting PVD-nanoglass consists of two structural components: noncrystalline nanometer-sized cores and interfacial regions that are formed during the consolidation process. The interfacial regions were found to have an atomic structure and an internal energy that differ from the structure and internal energy of the corresponding melt-quenched glass. The resulting material represents a noncrystalline state that differs from a bulk glass with the same chemical composition and a glass obtained from nanoparticles derived from the bulk glass.

We describe the fabrication of hybrid yet well-ordered porous nanoparticle (NP) arrays with full three-dimensional periodicity by embedding nanometer-sized metal-organic clusters (MOCs) into metal-organic frameworks (MOFs). Although conventional NP@MOF encapsulation procedures failed for these fairly large (1.66 nm diameter) NPs, we achieved maximum loading efficiency (one NP per pore) by using a modified liquid phase epitaxy (LPE) layer-by-layer approach to grow and load the MOF. The preformed NPs, homochiral Ti4(OH)4(R/S-BINOL)6 clusters (Ti-MOC, BINOL = 1,1'-bi-2-naphthol), formed a regular lattice inside the pores of an achiral HKUST-1 (or Cu3(BTC)2, BTC = 1,3,5-benzenetricarboxylate) MOF thin film. Exposure to the different enantiomers of methyl lactate revealed that the NP@MOF metacrystal is quite efficient regarding enantiomer recognition and separation. The approach presented here is also suited for other MOF types and expected to provide a substantial stimulus for the fabrication of metacrystals, crystalline solids made from nanoparticles instead of atoms.

A fast and accurate scheme has been developed to evaluate two key molecular parameters (on-site energies and transfer integrals) that govern charge transport in organic supramolecular architecture devices. The scheme is based on a constrained density functional theory (CDFT) approach implemented in the linear-scaling BigDFT code that exploits a wavelet basis set. The method has been applied to model disordered structures generated by force-field simulations. The role of the environment on the transport parameters has been taken into account by building large clusters around the active molecules involved in the charge transfer.

It is an outstanding challenge to model the electronic properties of organic amorphous materials utilized in organic electronics. Computation of the charge carrier mobility is a challenging problem as it requires integration of morphological and electronic degrees of freedom in a coherent methodology and depends strongly on the distribution of polaron energies in the system. Here we represent a QM/QM model to compute the polaron energies combining density functional methods for molecules in the vicinity of the polaron with computationally efficient density functional based tight binding methods in the rest of the environment. For seven widely used amorphous organic semiconductor materials, we show that the calculations are accelerated up to 1 order of magnitude without any loss in accuracy. Considering that the quantum chemical step is the efficiency bottleneck of a workflow to model the carrier mobility, these results are an important step toward accurate and efficient disordered organic semiconductors simulations, a prerequisite for accelerated materials screening and consequent component optimization in the organic electronics industry.

Disordered organic materials have a wide range of interesting applications, such as organic light emitting diodes, organic photovoltaics, and thin film electronics. To model electronic transport through such materials it is essential to describe the energy distribution of the available electronic states of the carriers in the material. Here, we present a self-consistent, linear-scaling first-principles approach to model environmental effects on the electronic properties of disordered molecular systems. We apply our parameter free approach to calculate the energy disorder distribution of localized charge states in a full polaron model for two widely used benchmark-systems (tris(8-hydroxyquinolinato)aluminum (Alq3) and N,N'-bis(1-naphthyl)-N,N'-diphenyl-1,1'-biphenyl-4,4'-diamine (α-NPD)) and accurately reproduce the experimental charge carrier mobility over a range of 4 orders of magnitude. The method can be generalized to determine electronic and optical properties of more complex systems, e.g. guest-host morphologies, organic-organic interfaces, and thus offers the potential to significantly contribute to de novo materials design.

In spin crossover phenomena, the magnetic moment of a molecule is switched by external means. Here we theoretically predict that several 5d-transition metals (TMs) adsorbed on finite graphene flakes undergo a spin crossover, resulting from multiple adsorption minima, that are absent in the zero-dimensional limit of benzene and the two-dimensional limit of graphene. The different spin states are stable at finite temperature and can be reversibly switched with an electric field. The system undergoes a change in magnetic anisotropy upon spin crossover, which facilitates read-out of the spin state. The TM-decorated nanoflakes thus act as fully controlled single-ion magnetic switches.

Fourteen different "hairy-rod" conjugated polymers, 9,9-dioctylfluorene derivatives entailing 1,2,3-triazole, azomethine, ethynyle, biphenyle, stilbene, and azobenzene lateral units, are synthesized via modular conjugation and are systematically investigated with respect to their ability to selectively disperse SWCNTs. Four polymers of the azomethine type, with unprecedented selectivity toward dispersing (8,7), (7,6), and (9,5) SWCNT species, have been identified. In particular, azomethine polymers, herein applied for the first time for SWCNT dispersion, have been evidenced to be very effective in the highly selective solubilization of SWCNTs. The experimentally observed selectivity results are unambiguously supported by molecular dynamics simulations that account for the geometrical properties and deformation energy landscape of the polymer. Specifically, the calculations accurately and with high precision predict the experimentally observed selectivity for the (7,6) and (9,5) conformations.

In wetland-adapted plants, such as rice, it is typically root apexes, sites of rapid entry for water/nutrients, where radial oxygen losses (ROLs) are highest. Nutrient/toxic metal uptake therefore largely occurs through oxidized zones and pH microgradients. However, the processes controlling the acquisition of trace elements in rice have been difficult to explore experimentally because of a lack of techniques for simultaneously measuring labile trace elements and O2/pH. Here, we use new diffusive gradients in thin films (DGT)/planar optode sandwich sensors deployed in situ on rice roots to demonstrate a new geochemical niche of greatly enhanced As, Pb, and Fe(II) mobilization into solution immediately adjacent to the root tips characterized by O2 enrichment and low pH. Fe(II) mobilization was congruent to that of the peripheral edge of the aerobic root zone, demonstrating that the Fe(II) mobilization maximum only developed in a narrow O2 range as the oxidation front penetrates the reducing soil. The Fe flux to the DGT resin at the root apexes was 3-fold higher than the anaerobic bulk soil and 27 times greater than the aerobic rooting zone. These results provide new evidence for the importance of coupled diffusion and oxidation of Fe in modulating trace metal solubilization, dispersion, and plant uptake.

Implicit solvent models are one of the standard tools in computational biophysics. While Poisson-Boltzmann methods offer highly accurate results within this framework, generalized Born models have been used due to their higher computational efficiency in many (bio)molecular simulations, where computational power is a limiting factor. In recent years, there have been remarkable advances to reduce some deficiencies in the generalized Born models. On the other hand, these advances come at an increased computational cost that contrasts the reasons for choosing generalized Born models over Poisson-Boltzmann methods. To address this performance issue, we present a new algorithm for Born radii computation, one performance critical part in the evaluation of generalized Born models, which is based on a Barnes-Hut tree code scheme. We show that an implementation of this algorithm provides accurate Born radii and polar solvation free energies in comparison to Poisson-Boltzmann computations, while delivering up to an order of magnitude better performance over existing, similarly accurate methods. The C++ implementation of this algorithm will be available at http://www.int.kit.edu/nanosim/ .

A series of 7-alkyl-3-benzylcoumarins was designed, synthesized, and tested at cannabinoid CB(1) and CB(2) receptors in radioligand binding and cAMP accumulation studies. 7-Alkyl-3-benzylcoumarins were found to constitute a versatile scaffold for obtaining potent CB receptor ligands with high potency at either CB(1) or CB(2) and a broad spectrum of efficacies. Fine-tuning of compound properties was achieved by small modifications of the substitution pattern. The most potent compounds of the present series include 5-methoxy-3-(2-methylbenzyl)-7-pentyl-2H-chromen-2-one (19a, PSB-SB-1201), a selective CB(1)antagonist (K(i) CB(1) 0.022 μM), 5-methoxy-3-(2-methoxybenzyl)-7-pentyl-2H-chromen-2-one (21a, PSB-SB-1202), a dual CB(1)/CB(2)agonist (CB(1)K(i) 0.032 μM, EC(50) 0.056 μM; CB(2)K(i) 0.049 μM, EC(50) 0.014 μM), 5-hydroxy-3-(2-hydroxybenzyl)-7-(2-methyloct-2-yl)-2H-chromen-2-one (25b, PSB-SB-1203), a dual CB(1)/CB(2) ligand that blocks CB(1) but activates CB(2) receptors (CB(1)K(i) 0.244 μM; CB(2)K(i) 0.210 μM, EC(50) 0.054 μM), and 7-(1-butylcyclopentyl)-5-hydroxy-3-(2-hydroxybenzyl)-2H-chromen-2-one (27b, PSB-SB-1204), a selective CB(2) receptor agonist (CB(1)K(i) 1.59 μM; CB(2)K(i) 0.068 μM, EC(50) 0.048 μM).

The medical and socioeconomic relevance of thromboembolic disorders promotes an ongoing effort to develop new anticoagulants. Heparin is widely used as activator of antithrombin but incurs side effects. We screened a large database in silico to find alternative molecules and predicted d-myo-inositol 3,4,5,6-tetrakisphosphate (TMI) to strongly interact with antithrombin. Isothermal titration calorimetry confirmed a TMI affinity of 45 nM, higher than the heparin affinity (273 nM). Functional studies, fluorescence analysis, and citrullination experiments revealed that TMI induced a partial activation of antithrombin that facilitated the interaction with heparin and low affinity heparins. TMI improved antithrombin inhibitory function of plasma from homozygous patients with antithrombin deficiency with a heparin binding defect and also in a model with endothelial cells. Our in silico screen identified a new, non-polysaccharide scaffold able to interact with the heparin binding domain of antithrombin. The functional consequences of this interaction were experimentally characterized and suggest potential anticoagulant therapeutic applications.

Evolution has selected a protein's sequence to be consistent with the native state geometry, as this configuration must be both thermodynamically stable and kinetically accessible to prevent misfolding and loss of function. In simple protein geometries, such as coiled-coil helical bundles, symmetry produces a competing, globally different, near mirror image with identical secondary structure and similar native contact interactions. Experimental techniques such as circular dichroism, which rely on probing secondary structure content, cannot readily distinguish these folds. Here, we want to clarify whether the native fold and mirror image are energetically competitive by investigating the free energy landscape of three-helix bundles. To prevent a bias from a specific computational approach, the present study employs the structure prediction forcefield PFF01/02, explicit solvent replica exchange molecular dynamics (REMD) with the Amber94 forcefield, and structure-based simulations based on energy landscape theory. We observe that the native fold and its mirror image have a similar enthalpic stability and are thermodynamically competitive. There is evidence that the mirror fold has faster folding kinetics and could function as a kinetic trap. All together, our simulations suggest that mirror images might not just be a computational annoyance but are competing folds that might switch depending on environmental conditions or functional considerations.

Physico-chemical methods to sort single-walled carbon nanotubes (SWNTs) by chiral index are presently lacking but are required for in-depth experimental analysis and also for potential future applications of specific species. Here we report the unexpected selectivity of poly(N-decyl-2,7-carbazole) to almost exclusively disperse semiconducting SWNTs with differences of their chiral indices (n - m) ≥ 2 in toluene. The observed selectivity complements perfectly the dispersing features of the fluorene analogue poly(9,9-dialkyl-2,7-fluorene), which disperses semiconducting SWNTs with (n - m) ≤ 2 in toluene. The dispersed samples are further purified by density gradient centrifugation and analyzed by photoluminescence excitation spectroscopy. All-atom molecular modeling with decamer model compounds of the polymers and (10,2) and (7,6) SWNTs suggests differences in the π-π stacking interaction as origin of the selectivity. We observe energetically favored complexes between the (10,2) SWNT and the carbazole decamer and between the (7,6) SWNT and the fluorene decamer, respectively. These findings demonstrate that subtle structural changes of polymers lead to selective solvation of different families of carbon nanotubes. Furthermore, chemical screening of closely related polymers may pave the way toward simple, low-cost, and index-specific isolation of SWNTs.

The presence of disulfide bonds leads to an interesting interplay between noncovalent intramolecular interactions and disulfide bond formation even in small proteins. Here we have investigated the folding mechanism of the 23-residue potassium channel blocker 1WQE and the 18-residue antimicrobial peptide protegrin-1 1PG1 , as two proteins containing disulfide bridges, in all-atom basin hopping simulations starting from completely extended conformations. The minimal-energy conformations deviate by only 2.1 and 1.2 A for 1WQE and 1PG1 , respectively, from their structurally conserved experimental conformations. A detailed analysis of their free energy surfaces demonstrates that the folding mechanism of disulfide-bridged proteins can vary dramatically from Levinthal's single-path scenario to a cooperative process consistent with the funnel paradigm of protein folding.

The controlled fabrication of actively switchable atomic-scale devices, in particular transistors, has remained elusive to date. Here, we explain the operation of an atomic-scale three-terminal device by a novel switching mechanism of bistable, self-stabilizing reconstruction of the electrode contacts at the atomic level: While the device is manufactured by electrochemical deposition, it operates entirely on the basis of mechanical effects of the solid-liquid interface. We analyze mechanically and thermally stable metallic junctions with a predefined quantized conductance of 1-5 G0 in experiment and atomistic simulation. Atomistic modeling of structural and conductance properties elucidates bistable electrode reconstruction as the underlying mechanism of the device. Independent room temperature operation of two transistors at low voltage demonstrates intriguing perspectives for quantum electronics and logics on the atomic scale.

While modern docking methods often predict accurate binding modes, affinity calculations remain challenging and enrichment rates of in silico screening methods unsatisfactory. Inadequate treatment of induced fit effects is one major shortcoming of existing in silico screening methods. Here we investigate enrichment rates of rigid-, soft- and flexible-receptor models for 12 diverse receptors using libraries containing up to 13000 molecules. For the rigid-receptor model, we observed high enrichment (EF1 > 20) only for four target proteins. A soft-receptor model showed improved docking rates at the expense of reduced enrichment rates. A flexible side-chain model with flexible dihedral angles for up to 12 amino acids (3-8 flexible side chains) increased both binding propensity and enrichment rates: EF1 values increased by approximately 35% on average with respect to rigid docking. We find on average 4 known ligands in the top 10 molecules in the rank-ordered databases for the receptors investigated.

Vitreous samples were prepared in the (100 - x)% NaPO(3)-x% MoO(3) (0

We report the predictive de novo folding of three two-helix proteins using the free-energy protein forcefield PFF01. Starting from random initial conformations 40-90% of the members of the simulated ensembles converge to near-native conformations. The energetically lowest conformations approach the conserved part of the native conformations to within 1.64, 1.86, and 1.84 Å for 1WQC, 1WQD, and 1WQE, respectively. An analysis of the low-lying conformations predicts the correct topology of the disulfide bridges, which are formed in additional simulations with a constraining potential. The free energy landscapes of these proteins are very simple, suggesting them as candidates for all-atom molecular dynamics simulations. In five independent simulations we find the formation of the correct secondary structure and several folding events into the tertiary structure.

We report the predictive all-atom folding of the 60 amino acid four-helix bacterial ribosomal protein (BRP) L20 with a stochastic evolutionary optimization method in a free-energy force field. The energetically best, as well as six of the 10 lowest conformations, converge to a near-native structure. All of the 10 best energy conformations share the secondary structure elements of the native conformation, but differ in their tertiary alignment. The best conformation has a backbone root-mean-square deviation of 4.6 A to the native conformation and reproduces most distance constraints of the NMR experiment to 1.5 A resolution. Starting from random initial conditions, the native content of the simulated population increases more than 60-fold in the course of the simulation. These data demonstrate the feasibility of predictive unbiased all-atom protein folding with present day computational resources for the BRP L20.

The crystalline peroxide 3a is the main product (out of 10 theoretically possible) from the aerial peroxidation of all-cis-2,4,6-trimethyltetrahydropyran (2a). It has a similar structure both in solution and in the crystal as shown by nuclear Overhauser effects and X-ray analysis, respectively. Theoretical calculations at a density functional theory level (B3LYP/6-31G) provide insight into the stabilities of the different stereoisomers of this peroxide, accounting for the facile, acid-catalyzed isomerization from the meso form to the racemate. Peroxide 3b, which is the 2-tert-butyl analogue of 3a, out of 22 theoretically possible isomers, crystallizes in a similar meso form. As a result of crystal packing effects and the intrinsically (axial) chiral peroxy "chromophore" that deviates slightly from the antiperiplanar conformation, both enantiomorphic forms of 3b are encountered in the lattice.