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Molecules where the energy of the lowest excited singlet state is found below the energy of the lowest triplet state (inverted singlet-triplet molecules) are extremely rare. It is particularly challenging to discover new ones through virtual screening because the required wavefunction-based methods are expensive and unsuitable for high-throughput calculations. Here, we devised a virtual screening approach where the molecules to be considered with advanced methods are pre-selected with increasingly more sophisticated filters that include the evaluation of the HOMO-LUMO exchange integral and approximate CASSCF calculations. A final set of 7 candidates (0.05\% of the initial 15000) were verified to possess inversion between singlet and triplet states with state-of-the-art multireference methods (MS--CASPT2). One of them is deemed of particular interest because it is unrelated to other proposals made in the literature.

Transparent conducting materials are an essential component of optoelectronic devices. It is proven difficult, however, to develop high-performance materials that combine the often-incompatible properties of transparency and conductivity, especially for p-type-doped materials. In this work, we have employed a large set of molecular semiconductors extracted from the Cambridge Structural Database to evaluate the likelihood of transparent conducting material technology based on p-type-doped molecular crystals. Candidates are identified imposing the condition of high highest occupied molecular orbital (HOMO) energy level (for the material to be easily dopable), high charge carrier mobility (for the material to display large conductivity when doped), and a high threshold for energy absorption (for the material to absorb radiation only in the ultraviolet). The latest condition is found to be the most stringent criterion in a virtual screening protocol on a database composed of structures with sufficiently wide two-dimensional (2D) electronic bands. Calculation of excited-state energy is shown to be essential as the HOMO-lowest unoccupied molecular orbital (LUMO) gap cannot be reliably used to predict the transparency of this material class. Molecular semiconductors with desirable mobility are transparent because they display either forbidden electronic transition(s) to the lower excited states or small exchange energy between the frontier orbitals. Both features are difficult to design but can be found in a good number of compounds through virtual screening.

We try to determine if machine learning (ML) methods, applied to the discovery of new materials on the basis of existing data sets, have the power to predict completely new classes of compounds (extrapolating) or perform well only when interpolating between known materials. We introduce the leave-one-group-out cross-validation, in which the ML model is trained to explicitly perform extrapolations of unseen chemical families. This approach can be used across materials science and chemistry problems to improve the added value of ML predictions, instead of using extrapolative ML models that were trained with a regular cross-validation. We consider as a case study the problem of the discovery of non-fullerene acceptors because novel classes of acceptors are naturally classified into distinct chemical families. We show that conventional ML methods are not useful in practice when attempting to predict the efficiency of a completely novel class of materials. The approach proposed in this work increases the accuracy of the predictions to enable at least the categorization of materials with a performance above and below the median value.

Singlet fission (SF) in organic molecular solids is an example of a process that is challenging to describe with the most common electronic structure approaches. It involves optically bright singlet excited states delocalized over many molecules, which could be efficiently treated by density functional theory, and multiexcitonic localized states that have to be studied with wavefunction methods, usually with small clusters considering their expensive computational costs. In this work, we propose a methodology to combine multiconfigurational wavefunction calculations with reduced Hamiltonian to investigate the electronic structure of large clusters or fully periodic systems. The method is applied to the prototypical SF materials tetracene and pentacene. The results allow one to study how states of different natures (excitonic, charge-transfer, and multiexcitonic) coexist and are contaminated by their couplings in large or periodic systems. Novel insights are therefore possible. For example, because the excitonic bands are relatively broad with respect to the multiexcitonic states, there are limited regions of the crystal momentum space where the transition between the two is more likely.

We present a review of the field of high-throughput virtual screening for organic electronics materials focusing on the sequence of methodological choices that determine each virtual screening protocol. These choices are present in all high-throughput virtual screenings and addressing them systematically will lead to optimised workflows and improve their applicability. We consider the range of properties that can be computed and illustrate how their accuracy can be determined depending on the quality and size of the experimental datasets. The approaches to generate candidates for virtual screening are also extremely varied and their relative strengths and weaknesses are discussed. The analysis of high-throughput virtual screening is almost never limited to the identification of top candidates and often new patterns and structure–property relations are the most interesting findings of such searches. The review reveals a very dynamic field constantly adapting to match an evolving landscape of applications, methodologies and datasets., We review how high throughput virtual screening can been used to navigate the landscape of materials for organic electronics.

Knowledge of the full phonon spectrum is essential to accurately calculate the dynamic disorder (σ) and hole mobility (μ

Apelin, a member of the adipokine family, is a novel endogenous peptide which regulates the male reproduction system of men and male laboratory animals by interacting with a specific receptor. Recent studies have highlighted that apelin may play a role in the regulation of reproduction by reducing testerone production and inhibiting LH secretion. To the best of our knowledge, there is no available data on the presence of the apelin and its receptor in canine testes. Therefore, the aim of this study was to reveal its presence and evaluate its distribution in the canine testes using immunohistochemical and RT-PCR techniques. For this purpose, five fertile and healthy male dogs were subjected to elective orchiectomy. The immunohistochemical reaction revealed the presence of apelin and its receptor in the canine testes. Apelin was localized in spermatids and spermatozoa with a positive signal in the “acrosomal bodies”. As regards the apelin receptor, a positive immunoreaction was detected in the cytoplasm of the cells localized near to the basal membrane of the seminiferous tubules and in the cytoplasm of Leydig cells. The RT-PCR analysis showed the presence of transcripts for apelin and apelin receptor in all of the samples under study. A 35 kDa band confirmed apelin receptor protein expression in all of the samples analysed. In conclusion, the paracrine and endocrine role of apelin and its cognate receptor on male reproduction reported in humans and laboratory animals, could also be hypothesized in dogs.

A series of candidates of thermally activated delayed fluorescence (TADF) materials, which have important applications in organic light emitting diodes devices, are identified by a high-throughput virtual screening of a database of known molecular materials. The first step of the screening identifies nearly 700 molecules that, in the X-ray geometry, have a sufficiently small gap between excitation energy of the lowest singlet and triplet states and acceptable oscillator strength of the singlet. After geometry optimization, 125 molecules continue to satisfy the energy criteria for potential TADF. Furthermore, the parameters of excited state dynamics including the reorganization energy, adiabatic excitation energy and spin–orbital coupling are calculated for a sample of molecules based on the optimized excited state geometries. The majority of the candidates are not known as TADF materials and could be considered promising lead compounds for the exploration of this materials class. Interestingly, it is found that some novel chromophores deviate from the current design rule for TADF materials, which are invariably based on a donor–acceptor molecular architecture. We also illustrate how to design completely new types of TADF materials using the results of this screening.

he diradical and multiradical characters of a large and diverse set of 241 predicted singlet fission candidates are determined by multiconfigurational wavefunction methods, specifically natural orbital occupation number (NOON) analysis using the CASSCF method. The ascertained multiradical character strongly supports the current prediction that a good singlet fission candidate, independent of its structure, will tend to be of the weak biradicaloid class as well as having very little tetraradical character. Although the rule remains robust, it is not absolute as a small portion of our potential candidates are predicted to be closed shell. Additionally, a smaller handful of outliers with apparent tetraradical characters are identified, suggesting there may be the possibility, albeit rare, of singlet fission amongst weak tetraradicaloids.

Leptin regulates body weight and several physiological processes including reproduction. We evaluated the circulating levels of leptin in pregnant and non-pregnant bitches as well as their correlation with body weight, food intake and number of foetuses. Nineteen healthy German shepherd bitches were used and divided in two groups (pregnant n=12 and non-pregnant n=7). Blood samples were collected every 15days starting from ovulation (Day 0) throughout pregnancy (pregnant group, P) or throughout luteal phase (non-pregnant group, NP) In pregnant bitches, leptin concentrations increased from the day of ovulation (1.32±0.06ng/ml) up to day 45 (1.51±0.06ng/ml; p&nbsp

Apelin, a member of the adipokine family, is a new endogenous peptide and it’s involved, by interacting with a specific receptor, in the control of human and laboratory animals’male reproduction. As far as we know, no data is available about the presence of the apelinergic system in dog testicles. Therefore the aim of this study was to show, for the first time, its presence and distribution in the canine testis by immunoistochemistry and molecular biology studies. For this purpose, five fertile and healthy male dogs were used and subjected to elective orchiectomy. The immunohistochemical reaction evidenced the presence of apelin and its receptor in the canine testis. In particular, apelin appeared localized in spermatids and spermatozoa with a positive signal in the “acrosomal bodies”. Regarding to the apelin receptor, a positive immunoreaction was evidenced in the cytoplasm of the cells localized in the basal portion of the seminiferous tubules, likely Sertoli’s cells, and in the cytoplasm of Leydig cells. The RT-PCR analysis showed the presence of transcripts for apelin and apelin receptor in all the samples examined. In conclusion our result allows us to hypothesize that the role of the paracrine and endocrine apelinergic system reported in laboratory animals can also be found in the dog.

Reproductive physiology and breeding have fascinated scientist since ancient times, and it is not surprising that explorations in these fields are included among the oldest and most well-documented branches of veterinary medicine [...]

Whether or not specific ion effects determine the charge storage properties of aqueous graphene and graphite-based supercapacitors remains a highly debated topic. In this work we present a multiscale quantum mechanics classical molecular dynamics investigation of aqueous mono- and divalent salt electrolytes in contact with fully polarizable charged graphene sheets. By computing both the electrochemical double layer and quantum capacitance we observe a constant electrode specific capacitance with cationic radii and charge. Counterintuitively, we determine that a switch in the cation adsorption mechanism from inner to outer Helmholtz layers leads to negligible changes to the EDL capacitance, this appears to be due to the robust electronic structure of the graphene electrodes. However, the ability of ions (such as K+) with a relatively low hydration free energy to penetrate the inner Helmholtz plane and adsorb directly on the electrode surface is found to slow their diffusion parallel to the interface. Ions in the outer Helmholtz layer are found to have higher diffusivity at the surface due to their position in ion channels between water layers. Our results show that surface effects such as the surface polarization and the partial dehydration and local structuring of ions on the surface underpin the behaviour of cations at the interface and add a vital new perspective on trends in ion mobilities seen under confinement., Comment: 23 pages, 5 figures 4 tables

Simple Summary Diabetes mellitus is a disorder affecting millions of people worldwide. History of gestational diabetes is a proven risk factor, while diet may be a strategy for its prevention. Goji berry is the fruit of Lycium barbarum and a traditional medicinal herb with potential antidiabetic and hypoglycemic effects. This study evaluated the effect of two doses of Goji berry dietary supplementations on insulin sensitivity in rabbit does during pregnancy by using fasting and intravenous glucose tolerance test-derived indices. A long-term effect on the offspring was also hypothesised. The rabbit was a good experimental model for this study of insulin sensitivity as the tolerance test was feasible and sensitive to dietary modifications. The higher dose of Goji berry supplementation reduced the maximum glucose concentration after bolus administration, suggesting an improvement in the insulin response. Conversely, the present study could not support the effect of maternal diet on the adult offspring’s insulin sensitivity. The use of nutraceuticals as well as the hypothesis of foetal programming of metabolic diseases deserve further study. Abstract This study investigated the effects of Goji berry (Lycium barbarum) dietary supplementation during pregnancy on insulin sensitivity of rabbit does and their offspring. Starting from two months before the artificial insemination, 75 New Zealand White does were fed only commercial standard diet (C) or supplemented with 1% (G1) and 3% (G3) of Goji berries. Their offspring received a standard diet but kept the nomenclature of the mother’s group. Fasting and intravenous glucose tolerance test-derived indices were estimated at 21 days of pregnancy on rabbit does and at 90 days of age on the offspring. No difference was found in the fasting indices, while the diet modulated the response to glucose load of rabbit does. In particular, G3 group had the lowest glucose concentrations 5 min after the bolus administration (p < 0.05) and, as a result, differed in the parameters calculated during the elimination phase such as the elimination rate constant (Kel), the half-life of the exogenous glucose load (t1/2), and apparent volume of distribution (Vd; for all, p < 0.05). The high dose of Goji supplementation could thus enhance the first-phase glucose-induced insulin secretion. Findings on the offspring were inconsistent and therefore a long-term effect of Goji supplementation during pregnancy could not be demonstrated. Further study on the effect of Goji on the secretory pathway of insulin could clarify its hypoglycaemic action, while different protocols are needed to investigate its potential effects on foetal programming.

We present a data set of 48182 organic semiconductors, constituted of molecules that were prepared with a documented synthetic pathway and are stable in solid state. We based our search on the Cambridge Structural Database, from which we selected semiconductors with a computational funnel procedure. For each entry we provide a set of electronic properties relevant for organic materials research, and the electronic wavefunction for further calculations and/or analyses. This data set has low bias because it was not built from a set of materials designed for organic electronics, and thus it provides an excellent starting point in the search of new applications for known materials, with a great potential for novel physical insight. The data set contains molecules used as benchmarks in many fields of organic materials research, allowing to test the reliability of computational screenings for the desired application, “rediscovering” well-known molecules. This is demonstrated by a series of different applications in the field of organic materials, confirming the potential for the repurposing of known organic molecules.

The microscopic structure of high mobility semiconducting polymers is known to be essential for their performance but it cannot be easily deduced from the available experimental data. A series of short oligomers of diketopyrrolopyrrole (DPP)-based materials that display high charge mobility are studied by molecular dynamics simulations to understand their local structuring at an atomic level. Different analyses are proposed to compare the ability of different oligomers to form large aggregates and their driving force. The simulations show that the tendency for this class of materials to form aggregates is driven by the interaction between DPP fragments, but this is modulated by the other conjugated fragments of the materials which affect the rigidity of the polymer and, ultimately, the size of the aggregates that are formed. The main structural features and the electronic structure of the oligomers are fairly similar above the glass transition temperature and at room temperature.

We developed a rapid method to calculate the average electronic structure properties of large ensembles of conjugated polymer chains sampling their conformational space. This is achieved by using the localized molecular orbital (MO) method to rapidly compute the MOs and their energies for isolated polymer chains and through using a calibration scheme to further correct the obtained energies by comparison with a few accurate calculations. The method is applied to the study of the density of states and orbital localization characteristics for five polymers. It is shown that all key properties of the individual chain related to the charge mobility can be rationalized in terms of the properties of the constituent monomers, their interaction, and the conformational flexibility of the chain. More specifically we identify the features that lead to greater charge delocalization. Finally, we discuss the prospect of using this method for a computational high-throughput screening of conjugated polymers.

When existing experimental data are combined with machine learning (ML) to predict the performance of new materials, the data acquisition bias determines ML usefulness and the prediction accuracy. In this context, the following two conditions are highly common: (i) constructing new unbiased data sets is too expensive and the global knowledge effectively does not change by performing a limited number of novel measurements; (ii) the performance of the material depends on a limited number of physical parameters, much smaller than the range of variables that can be changed, albeit such parameters are unknown or not measurable. To determine the usefulness of ML under these conditions, we introduce the concept of simulated research landscapes, which describe how datasets of arbitrary complexity evolve over time. Simulated research landscapes allow us to use different discovery strategies to compare standard materials exploration with ML-guided explorations, i.e. we can measure quantitatively the benefit of using a specific ML model. We show that there is a window of opportunity to obtain a significant benefit from ML-guided strategies. The adoption of ML can take place too soon (not enough information to find patterns) or too late (dense datasets only allow for negligible ML benefit), and the adoption of ML can even slow down the discovery process in some cases. We offer a qualitative guide on when ML can accelerate the discovery of new best-performing materials in a field under specific conditions. The answer in each case depends on factors like data dimensionality, corrugation and data collection strategy. We consider how these factors may affect the ML prediction capabilities and discuss some general trends.

We evaluated the potential usefulness of CEUS to assess fetal-maternal circulation during pregnancy in dogs. Nine bitches were examined at 23, 30, and 45 days of gestation using an ultrasound machine (LOGIQ E9) and SonoVue® contrast media as echo-signal enhancer. Qualitative and quantitative evaluation of contrast enhancement patterns of uterine artery and utero/placental vessels were performed on recorded images. Independently of the gestational periods, the qualitative evaluation showed the initial wash-in phase from the first appearance of the uterine artery to the rapid distribution in embryonic vesicles or placenta to the progressive washout, whilst there was no enhancement of either embryos or fetuses in any bitch. Independent of gestational age, parameters derived from quantitative analysis of time intensity-curves of contrast enhancement (peak intensity, time to peak, rise time, washout) did not vary between proximal placenta, distal placenta, and uterine artery. With the progression of gestation, AUC values did not change in both proximal and distal placenta, but in the uterine artery it was lower (P ≤ 0.05) at day 30 than at day 23 (464.8 ± 16.1 vs.596.4 ± 28.1, respectively). In conclusion, CEUS appears to safely permit evaluation of the maternal and fetal vessels in the first two third of gestation, without any clinically relevant adverse effects. Further studies in a larger number of bitches in different stages of pregnancy are needed to establish standard parameters for normal pregnancies that can be used to detect abnormalities of pregnancy.

The effect of polymorphism (i.e. the ability of accessing different packing structures) on the fluctuations of transfer integrals is quantified for a prototypical molecule, pentacene. Computed mobilities for different polymorphs match the broad range of measured mobilities in organic field-effect transistors (OFET), suggesting that the large spread of experimental values reported in the literature, even when resorting to the same experimental setup, can be related to polymorphism in the samples. This finding is especially significant in new materials, where polymorphism is not known, as it could lead to a spread of results across groups and processing conditions, ultimately slowing down the research towards better semiconductors. Additionally, our analysis shows for the first time that the non-local electron–phonon coupling changes with temperature, a key finding that must be taken into account when computing the temperature dependence of the mobility; it also highlights the possibility of identifying previously unexplored ranges of temperatures, where materials display higher performances. The method here presented can be used to rapidly screen many materials and design new ones thanks to its low computational cost and its accuracy.

We considered a database of tens of thousands of known organic semiconductors and identified those compounds with computed electronic properties (orbital energies, excited state energies, and oscillator strengths) that would make them suitable as nonfullerene electron acceptors in organic solar cells. The range of parameters for the desirable acceptors is determined from a set of experimentally characterized high-efficiency nonfullerene acceptors. This search leads to ∼30 lead compounds never considered before for organic photovoltaic applications. We then proceed to modify these compounds to bring their computed solubility in line with that of the best small-molecule nonfullerene acceptors. A further refinement of the search can be based on additional properties like the reorganization energy for chemical reduction. This simple strategy, which relies on a few easily computable parameters and can be expanded to a larger set of molecules, enables the identification of completely new chemical families to be explored experimentally.

The close link between nutrition management and reproductive efficiency is well known, but there is very little data available concerning this topic in canine species. The present study aimed to compare the effect of two different diets upon the follicular period and gestation in bitches. Eighteen pluriparus medium and large size bitches were recruited and divided into control (CTR) and experimental (EX) groups and fed, respectively, with a commercial kibble diet and a specially formulated diet from two months before the expected onset of proestrus up to the end of the trial. It was possible to observe how the EX group had a better clinical presentation of the estrous phase, a higher number of ovarian follicles (p &lt, 0.05), a lower percentage of fetal resorption (p &lt, 0.05), and lower oxidative status, expressed by d-ROMs (p &lt, 0.01), at the moment of pregnancy diagnosis compared to CTR group. Moreover, the EX group showed a lower fetal resorption rate and higher litter size (p &lt, 0.05). These results highlight how a diet characterized by high protein and fat content and richer in essential fatty acids can improve reproductive performance in dogs.

This study examined the effects of goji berries dietary supplementation on the energetic metabolism of doe. Thirty days before artificial insemination, 75 New Zealand White does were assigned to three different diets: commercial standard diet (C) and supplemented with 1% (LG) and 3% (HG) of goji berries, respectively. Body conditions, hormones and metabolites were monitored until weaning. Body weight and BCS were higher in HG than C (p &lt, 0.05). LG showed lower T3/T4 ratio and cortisol concentrations (p &lt, 0.05) and tended to have lower indices of insulin resistances (p &lt, 0.1) than HG. Compared to control, leptin was higher in HG at AI (p &lt, 0.01) and in LG during lactation (p &lt, 0.05). Two principal components were extracted by multivariate analysis describing the relationships between (1) non-esterified fatty acids, insulin and glucose levels, and (2) body conditions and leptin metabolism. The first component highlighted the energy deficit and the insulin resistance of the does during pregnancy and lactation. The second one showed that leptin, body weight and Body Condition Score (BCS) enhance as levels of goji berries in the diet increase. Thus, the effects of goji supplementation are dose-dependent: an improvement on energy metabolism was achieved with a low-dose while the highest dose could determine excessive fattening and insulin resistance in does.

In this work, we analyzed a dataset formed by 566 donor/acceptor pairs, which are part of organic solar cells recently reported. We explored the effect of different descriptors in machine learning ...

Charge dissociation in the active layer is one of the key factors for the power conversion efficiency of bulk heterojunction organic solar cells (OSCs). Numerous charge-transfer mechanisms have been proposed based on one of few microscopic models. Here, we would explore possible charge-transfer mechanisms for 155 models of donor/acceptor (D/A) interfaces, built via materials DCV-1 and C60 as the donor and acceptor, respectively. After the calculations of the key parameters related to the charge dissociation and a statistical analysis for the correlation between these parameters were carried out, we can obtain a more robust description of the charge dissociation in practical OSCs. The complicated relationship among the key parameters not only illustrates the important correlation between the D/A stacking pattern and charge-transfer mechanism but also suggests that different charge-transfer mechanisms take place more likely depending on the specific arrangements of the donor and acceptor.

We report a new Quantum Mechanical/Molecular Dynamics (QM/MD) simulation loop to model the coupling between the electron and atom dynamics in solid/liquid interfacial systems. The method can describe simultaneously both the quantum mechanical surface polarizability emerging from the proximity to the electrolyte, and the electrolyte structure and dynamics. In the current set up Density Functional Tight Binding calculations for the electronic structure calculations of the surface are coupled with classical molecular dynamics to simulate the electrolyte solution. The reduced computational cost of the QM part makes the coupling with a classical simulation engine computationally feasible and allows simulation of large systems for hundreds of nanoseconds. We tested the method by simulating both a non-charged graphene flake and a non-charged and charged infinite graphene sheet immersed in an NaCl electrolyte solution. We found that, when no bias is applied, ions preferentially remained in solution and only cations are mildly attracted to the surface of the graphene. This preferential adsorption of cations vs anions seems to persist also when the surface is moderately charged and rules out any substantial ions/surface charge transfer., Comment: 22 pages, 8 figures

Aglepristone was administered in bitches during the follicular phase to evaluate its effects on progesterone, estradiol-17β and LH serum concentrations. Ten German Shepherds were divided into two groups (treated n=5; control n=5). Treated bitches received 10mg/kg BW of aglepristone subcutaneously during the early follicular phase, 24hr after and then 7days later. The control group was injected, at the same time periods, with saline solution (0.3ml/kg BW). For the steroid evaluations, blood was collected daily from the onset of proestrus until the first day of cytological dioestrus. For LH base-line serum determination, blood was also collected every 20min for 2hr at the onset of proestrus. For LH surge identification, blood was collected daily (every 6hr) starting from the day of the first administration of aglepristone or saline solution until the first day of dioestrus. All animals ovulated but the treated group presented longer ovulation-dioestrus intervals than the control group (5.2±2.2days p&nbsp