Computational Prediction of Muon Stopping Sites Using Ab Initio Random Structure Searching (AIRSS)

The stopping site of the muon in a muon-spin relaxation experiment ({\mu}+SR) is in general unknown. There are some techniques that can be used to guess the muon stopping site, but they often rely on approximations and are not generally applicable to all cases. In this work, we propose a purely theoretical method to predict muon stopping sites in crystalline materials from first principles. The method is based on a combination of ab initio calculations, random structure searching and machine learning, and it has successfully predicted the MuT and MuBC stopping sites of muonium in Si, Diamond and Ge, as well as the muonium stopping site in LiF, without any recourse to experimental results. The method makes use of Soprano, a Python library developed to aid ab-initio computational crystallography, that was publicly released and contains all the software tools necessary to reproduce our analysis

Revisiting the Van Vleck second moment for characterizing molecular motion in organic solids

Van Vleck’s classic theory of the second moment of lineshapes in 1H nuclear magnetic resonance (NMR) is reworked in a form that allows the effect of rapid molecular motion on second moments to be calculated in a semi-analytical fashion. This is much more efficient than existing approaches and also extends previous analyses of (non-dynamic) dipolar networks in terms of site-specific root-sum-square dipolar couplings. The non-local nature of the second moment means that it can discriminate between overall motions that are difficult to discriminate using alternative approaches, such as measurements of NMR relaxation. The value of reviving second moment studies is illustrated on the plastic solids diamantane and triamantane. In the case of triamantane, straightforward measurements of 1H lineshapes on milligram samples show that the molecules in the higher temperature phase undergo multi-axis jumps, information that is not accessible either to diffraction studies or to alternative NMR approaches. The efficiency of the computational methods means that the second moments can be calculated using a readily extensible and open-source Python code

Small and large scale segmental motion in polymers: Estimating cooperativity length by ordinary relaxation experiments

We derive a suitable expression for estimating the size of the cooperatively rearranging regions (CRRs) in supercooled polymer melts by fitting data worked out by ordinary relaxation experiments carried out in isothermal conditions. As an example, the average CRR size in poly(n-butyl methacrylate) in proximity to the glass transition temperature is derived from a stress relaxation experiment performed by means of an atomic force microscopy setup. Good agreement is found with results in the literature derived from measurements of temperature fluctuations (the so-called Donth method). The temperature dependence of the CRR size is explored for poly(butadiene); in this case the segmental relaxation function is derived through a novel method for the analysis of the efficiency with which free induction decay echoes are refocused in 1H NMR experiments. It is found that the CRR size increases upon cooling. The results derived from the analysis of the NMR data are found to be in satisfactory agreement with those worked out from broadband dielectric spectroscopy data in the literatur

Testing, tracing and isolation in compartmental models

Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computational efficiency is such that it can be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks

A Muon Spectroscopic and Computational Study of the Microscopic Electronic Structure in Thermoelectric Hybrid Silicon Nanostructures

Phenylacetylene-capped silicon nanoparticles (Phenyl-SiNPs) have attracted interest as a novel thermoelectric material. Here, we report a combined muon spectroscopic (μSR) and computational study of this material in solution to investigate the microscopic electronic structure of this system. For comparison, the model molecular compound tetrakis(2-phenylethynyl)silane has also been investigated. μSR measurements have shown that the muon isotropic hyperfine coupling constant, A μ, which depends on spin density at the muon, is greatly reduced for the Phenyl-SiNPs system when compared to the model compound. Results have also demonstrated that the temperature dependence of A μ for the Phenyl-SiNPs is of opposite sign and proportionally larger when compared to the model compound. Ab initio DFT methods have allowed us to determine the muon addition site in the model compound, while a wider computational study using both DFTB+ and CASTEP offers a qualitative explanation for the reduced coupling seen in the Phenyl-SiNPs system and also the contrasting temperature dependence of A μ for the two materials. Calculations suggest an increase in the density of electronic states at the energy level of the highest occupied molecular state for the Phenyl-SiNPs, even in the presence of an organic cap, suggesting a mechanism for enhanced electron transport in this system when compared to the tetrakis model compound

Mycobacterium tuberculosis epitope-specific interferon-g production in healthy Brazilians reactive and non-reactive to tuberculin skin test

The interferon (IFN)-gamma response to peptides can be a useful diagnostic marker of Mycobacterium tuberculosis (MTB) latent infection. We identified promiscuous and potentially protective CD4(+) T-cell epitopes from the most conserved regions of MTB antigenic proteins by scanning the MTB antigenic proteins GroEL2, phosphate-binding protein 1 precursor and 19 kDa antigen with the TEPITOPE algorithm. Seven peptide sequences predicted to bind to multiple human leukocyte antigen (HLA)-DR molecules were synthesised and tested with IFN-gamma enzyme-linked immunospot (ELISPOT) assays using peripheral blood mononuclear cells (PBMCs) from 16 Mantoux tuberculin skin test (TST)-positive and 16 TST-negative healthy donors. Eighty-eight percent of TST-positive donors responded to at least one of the peptides, compared to 25% of TST-negative donors. Each individual peptide induced IFN-gamma production by PBMCs from at least 31% of the TST-positive donors. the magnitude of the response against all peptides was 182 +/- 230 x 10(6) IFN-gamma spot forming cells (SFC) among TST-positive donors and 36 +/- 62 x 10(6) SFC among TST-negative donors (p = 0.007). the response to GroEL2 (463-477) was only observed in the TST-positive group. This combination of novel MTB CD4 T-cell epitopes should be tested in a larger cohort of individuals with latent tuberculosis (TB) to evaluate its potential to diagnose latent TB and it may be included in ELISPOT-based IFN-gamma assays to identify individuals with this condition.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Universidade Federal de São Paulo, Fac Med, Inst Coracao, Immunol Lab, São Paulo, BrazilUniversidade Federal de São Paulo, Fac Med, Dept Med, Div Imunol Clin & Alergia, São Paulo, BrazilFundacao Oswaldo Cruz, Lab Avancado Saude Publ, Salvador, BA, BrazilEscola Bahiana Med & Saude Publ, Salvador, BA, BrazilInst Invest Immunol, São Paulo, BrazilUniversidade Federal de São Paulo, Fac Med, Inst Coracao, Immunol Lab, São Paulo, BrazilUniversidade Federal de São Paulo, Fac Med, Dept Med, Div Imunol Clin & Alergia, São Paulo, BrazilWeb of Scienc