Efficient singlet exciton fission in pentacene prepared from a soluble precursor

Carrier multiplication using singlet exciton fission (SF) to generate a pair of spin-triplet excitons from a single optical excitation has been highlighted as a promising approach to boost the photocurrent in photovoltaics (PVs) thereby allowing PV operation beyond the Shockley-Queisser limit. The applicability of many efficient fission materials, however, is limited due to their poor solubility. For instance, while acene-based organics such as pentacene (Pc) show high SF yields (up to 200%), the plain acene backbone renders the organic molecule insoluble in common organic solvents. Previous approaches adding solubilizing side groups such as bis(tri-$\textit{iso}$-propylsilylethynyl) to the Pc core resulted in low vertical carrier mobilities due to reduction of the transfer integrals via steric hindrance, which prevented high efficiencies in PVs. Here we show how to achieve good solubility while retaining the advantages of molecular Pc by using a soluble precursor route. The precursor fully converts into molecular Pc through thermal removal of the solubilizing side groups upon annealing above 150 °C in the solid state. The annealed precursor shows small differences in the crystallinity compared to evaporated thin films of Pc, indicating that the Pc adopts the bulk rather than surface polytype. Furthermore, we identify identical SF properties such as sub-100 fs fission time and equally long triplet lifetimes in both samples.M.T. thanks the Gates Cambridge Trust and the Winton Programme for the Physics of Sustainability for funding. A.H.K. acknowledges the Cambridge Nehru Bursary, the Cambridge Bombay Society, a Trinity-Henry Barlow- and Haidar Scholarship as well as Rana Denim Pvt. Ltd. for financial support. K.B. and J.N. would like to thank Dr. Tom Arnold and Jakub Rozboril for assistance during the beam time at Diamond Light Source. Financial support for K.B. from Diamond Light Source, Swiss Light Source, and the German Research Foundation (Grant No. BR 4869/1-1) is gratefully acknowledged. M.L.B. is a research fellow of Christ’s College, Cambridge. This work was supported by the Engineering and Physical Sciences Research Council (Grant Nos. EP/M005143/1, EP/G060738/1 and Cambridge NanoDTC EP/G037221/1, EP/L015978/1)

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Developing Prognosis Tools to Identify Learning Difficulties in Children Using Machine Learning Technologies

The Mental Attributes Profiling System was developed in 2002 (Laouris and Makris, Proceedings of multilingual & cross-cultural perspectives on Dyslexia, Omni Shoreham Hotel, Washington, D.C, 2002), to provide a multimodal evaluation of the learning potential and abilities of young children’s brains. The method is based on the assessment of non-verbal abilities using video-like interfaces and was compared to more established methodologies in (Papadopoulos, Laouris, Makris, Proceedings of IDA 54th annual conference, San Diego, 2003), such as the Wechsler Intelligence Scale for Children (Watkins et al., Psychol Sch 34(4):309–319, 1997). To do so, various tests have been applied to a population of 134 children aged 7–12 years old. This paper addresses the issue of identifying a minimal set of variables that are able to accurately predict the learning abilities of a given child. The use of Machine Learning technologies to do this provides the advantage of making no prior assumptions about the nature of the data and eliminating natural bias associated with data processing carried out by humans. Kohonen’s Self Organising Maps (Kohonen, Biol Cybern 43:59–69, 1982) algorithm is able to split a population into groups based on large and complex sets of observations. Once the population is split, the individual groups can then be probed for their defining characteristics providing insight into the rationale of the split. The characteristics identified form the basis of classification systems that are able to accurately predict which group an individual will belong to, using only a small subset of the tests available. The specifics of this methodology are detailed herein, and the resulting classification systems provide an effective tool to prognose the learning abilities of new subjects

Molecular and phenotypic characterisation of paediatric glioma cell lines as models for preclinical drug development.

Although paediatric high grade gliomas resemble their adult counterparts in many ways, there appear to be distinct clinical and biological differences. One important factor hampering the development of new targeted therapies is the relative lack of cell lines derived from childhood glioma patients, as it is unclear whether the well-established adult lines commonly used are representative of the underlying molecular genetics of childhood tumours. We have carried out a detailed molecular and phenotypic characterisation of a series of paediatric high grade glioma cell lines in comparison to routinely used adult lines

The <i>Pratylenchus penetrans</i> transcriptome as a source for the development of alternative control strategies:mining for putative genes involved in parasitism and evaluation of <i>in planta</i> RNAi

The root lesion nematode Pratylenchus penetrans is considered one of the most economically important species within the genus. Host range studies have shown that nearly 400 plant species can be parasitized by this species. To obtain insight into the transcriptome of this migratory plant-parasitic nematode, we used Illumina mRNA sequencing analysis of a mixed population, as well as nematode reads detected in infected soybean roots 3 and 7 days after nematode infection. Over 140 million paired end reads were obtained for this species, and de novo assembly resulted in a total of 23,715 transcripts. Homology searches showed significant hit matches to 58% of the total number of transcripts using different protein and EST databases. In general, the transcriptome of P. penetrans follows common features reported for other root lesion nematode species. We also explored the efficacy of RNAi, delivered from the host, as a strategy to control P. penetrans, by targeted knock-down of selected nematode genes. Different comparisons were performed to identify putative nematode genes with a role in parasitism, resulting in the identification of transcripts with similarities to other nematode parasitism genes. Focusing on the predicted nematode secreted proteins found in this transcriptome, we observed specific members to be up-regulated at the early time points of infection. In the present study, we observed an enrichment of predicted secreted proteins along the early time points of parasitism by this species, with a significant number being pioneer candidate genes. A representative set of genes examined using RT-PCR confirms their expression during the host infection. The expression patterns of the different candidate genes raise the possibility that they might be involved in critical steps of P. penetrans parasitism. This analysis sheds light on the transcriptional changes that accompany plant infection by P. penetrans, and will aid in identifying potential gene targets for selection and use to design effective control strategies against root lesion nematodes

Self domestication and the evolution of language

We set out an account of how self-domestication plays a crucial role in the evolution of language. In doing so, we focus on the growing body of work that treats language structure as emerging from the process ofcultural transmission. We argue that a full recognition of the importance of cultural transmission fundamentally changes the kind ofquestionswe should be asking regarding the biological basis of language structure. If we think of language structure as reflecting an accumulated set of changes in our genome, then we might ask something like, "What are the genetic bases of language structure and why were they selected?" However, if cultural evolution can account for language structure, then this question no longer applies. Instead, we face the task of accounting for the origin of the traits that enabled that process of structure-creating cultural evolution to get started in the first place. In light of work on cultural evolution, then, the new question for biological evolution becomes, "How did those precursor traits evolve?" We identify two key precursor traits: (1) the transmission of the communication system throughlearning; and (2) the ability to infer thecommunicative intentassociated with a signal or action. We then describe two comparative case studies-the Bengalese finch and the domestic dog-in which parallel traits can be seen emerging followingdomestication. Finally, we turn to the role of domestication in human evolution. We argue that the cultural evolution of language structure has its origin in an earlier process of self-domestication.</p

Measurements of integrated and differential cross sections for isolated photon pair production in pp collisions at √s=8 TeV with the ATLAS detector

A measurement of the production cross section for two isolated photons in proton-proton collisions at a center-of-mass energy of √s=8 TeV is presented. The results are based on an integrated luminosity of 20.2 fb−1 recorded by the ATLAS detector at the Large Hadron Collider. The measurement considers photons with pseudorapidities satisfying |ηγ|40GeV and EγT,2>30 GeV for the two leading photons ordered in transverse energy produced in the interaction. The background due to hadronic jets and electrons is subtracted using data-driven techniques. The fiducial cross sections are corrected for detector effects and measured differentially as a function of six kinematic observables. The measured cross section integrated within the fiducial volume is 16.8 ± 0.8  pb . The data are compared to fixed-order QCD calculations at next-to-leading-order and next-to-next-to-leading-order accuracy as well as next-to-leading-order computations including resummation of initial-state gluon radiation at next-to-next-to-leading logarithm or matched to a parton shower, with relative uncertainties varying from 5% to 20%

Charged-particle distributions at low transverse momentum in √s=13 13 TeV pp interactions measured with the ATLAS detector at the LHC

Measurements of distributions of charged particles produced in proton–proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 μb −1 μb−1 . The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators