BackgroundThe PlA1/A2 polymorphism of glycoprotein IIIa (GPIIIa) has been reported to be associated with risk of stroke in some studies, although other studies suggest no such association. This meta-analysis and systematic review was conducted to investigate the hypothesis that carriage of the PlA2 allele is a risk factor for stroke.MethodsElectronic databases (MEDLINE and EMBASE) were searched for all articles evaluating carriage of the PlA2 allele and the incidence of stroke. Pooled odds ratios (ORs) were calculated using fixed-effect and random-effect models.FindingsA total of 35 articles were eligible for inclusion, of which 25 studies were suitable for statistical analysis. For carriage of the PlA2 allele, OR 1.12 (n = 11,873; 95% CI = 1.03–1.22; p = 0.011) was observed for the incidence of stroke in adults, with subgroup analyses identifying the association driven by stroke of an ischaemic (n = 10,494; OR = 1.15, 95% CI = 1.05–1.27; p = 0.003) but not haemorrhagic aetiology (n = 2,470; OR = 0.90, 95% CI = 0.71–1.14; p = 0.398). This association with ischaemic stroke was strongest in individuals homozygous for the PlA2 allele compared to those homozygous for wild-type PlA1 (n = 5,906; OR = 1.74, 95% CI = 1.34–2.26; p<0.001). Subgroup analysis of ischaemic stroke subtypes revealed an increased association with stroke of cardioembolic (n = 1,271; OR 1.56, 95% CI 1.14–2.12; p = 0.005) and large vessel (n = 1,394; OR = 1.76, 95% CI 1.34–2.31; p<0.001) aetiology, but not those of small vessel origin (n = 1,356; OR = 0.99, 95% CI 0.74–1.33; p = 0.950). Egger's regression test suggested a low probability of publication bias for all analyses (p>0.05).ConclusionsThe totality of published data supports the hypothesis that carriage of the PlA2 polymorphism of GPIIIa is a risk factor for ischaemic strokes, and specifically those of cardioembolic and large vessel origin.

Multicomponent systems are defined as chemical systems that require a quantum mechanical description of two or more different types of particles. Non-Born-Oppenheimer electron-nuclear interactions in molecules, electron-hole interactions in electronically excited nanoparticles, and electron-positron interactions are examples of physical systems that require a multicomponent quantum mechanical formalism. The central challenge in the theoretical treatment of multicomponent systems is capturing the many-body correlation effects that exist not only between particles of identical types (electron-electron) but also between particles of different types (electron-nuclear and electron-hole). In this work, the development and implementation of multicomponent coupled-cluster (mcCC) theory for treating particle-particle correlation in multicomponent systems are presented. This method provides a balanced treatment of many-particle correlation effects in a general multicomponent system while maintaining a size-consistent and size-extensive formalism. The coupled-cluster ansatz presented here is an extension of the electronic structure CCSD formulation for multicomponent systems and is defined as |ΨmcCC⟩ = eT1I+T2I+T1II+T2II+T11I,II+T12I,II+T21I,II+T22I,II|0I0II⟩. The cluster amplitudes in the mcCC wave function were obtained by projecting the mcCC Schrödinger equation onto a direct product space of singly and doubly excited states of type I and II particles and then solving the resulting mcCC equations iteratively. These equations were derived using an automated application of the generalized Wick’s theorem and were implemented using a computer-assisted source code generation approach. The applicability of the mcCC method was demonstrated by calculating ground state energies of multicomponent Hooke's atom and positronium hydride systems as well as by calculating exciton and biexciton binding energies in multiexcitonic systems. For each case, the mcCC results were benchmarked against full configuration interaction (FCI) calculations and were found to be in excellent agreement with the FCI results. The effect of neglecting certain classes of multicomponent connected excitation terms from the mcCC wave function was also investigated. The results from this study demonstrate that connected cluster operators that generate simultaneous excitation in type I and type II space are critical for capturing electron-hole correlation in multiexcitonic systems.

Generation of biexcitons in semiconductor nanoparticles has important technological applications in designing efficient light-harvesting materials. Like excitons, the attractive electron–hole interaction terms are responsible for binding in biexcitonic systems. However, unlike excitons, electron–electron and hole–hole repulsive components also contribute to the overall interaction in a biexcitonic system. Consequently, a balanced treatment of many-body correlation associated with electron–electron, hole–hole, and electron–hole interactions is needed for understanding quaisparticle binding in biexcitons. This work presents a theoretical investigation of the effect of size and chemical composition on biexciton binding energies in semiconductor nanoparticles using the electron–hole multicomponent coupled-cluster theory (eh-mcCC). Exciton and biexciton binding energies for quantum dots with diameters 1–20 nm for four semiconductor materials (CdSe, CdS, CdTe, and PbS) were calculated using the eh-mcCC method. The calculated exciton and biexciton binding energies were found to be in good agreement with previously reported experimental results for quantum dots. The results from these calculations demonstrate that exciton and biexciton binding energies exhibit very different scaling behavior with respect to increasing dot diameter. Specifically, with increasing dot diameter, exciton binding energies were found to decrease following a power-law dependence. By contrast, the biexciton binding energies were found to decrease exponentially and decreased at a slower rate as compared to exciton binding energies. The dramatic difference between the scaling equations for the exciton and biexciton binding energies shows that the response of the biexcitonic system with respect to change in the confinement potential is fundamentally very different from the response shown by excitonic systems.

No abstract

Electron-hole or quasiparticle representation plays a central role in describing electronic excitations in many-electron systems. For charge-neutral excitation, the electron-hole interaction kernel is the quantity of interest for calculating important excitation properties such as optical gap, optical spectra, electron-hole recombination, and electron-hole binding energies. The electron-hole interaction kernel can be formally derived from the density-density correlation function using both Green's function and time-dependent density functional theory (TDDFT) formalism. The accurate determination of the electron-hole interaction kernel remains a significant challenge for precise calculations of optical properties in the GW+BSE formalism. From the TDDFT perspective, the electron-hole interaction kernel has been viewed as a path to systematic development of frequency-dependent exchange-correlation functionals. Traditional approaches, such as many-body perturbation theory formalism, use unoccupied states (which are defined with respect to Fermi vacuum) to construct the electron-hole interaction kernel. However, the inclusion of unoccupied states has long been recognized as the leading computational bottleneck that limits the application of this approach for larger finite systems. In this work, an alternative derivation that avoids using unoccupied states to construct the electron-hole interaction kernel is presented. The central idea of this approach is to use explicitly correlated geminal functions for treating electron-electron correlation for both ground and excited state wave functions. Using this ansatz, it is derived using both diagrammatic and algebraic techniques that the electron-hole interaction kernel can be expressed only in terms of linked closed-loop diagrams. It is proved that the cancellation of unlinked diagrams is a consequence of linked-cluster theorem in real-space representation. The electron-hole interaction kernel derived in this work was used to calculate excitation energies in many-electron systems, and results were found to be in good agreement with the EOM-CCSD and GW+BSE methods. The numerical results highlight the effectiveness of the developed method for overcoming the computational barrier of accurately determining the electron-hole interaction kernel to applications of large finite systems such as quantum dots and nanorods.

Recent degradation studies have highlighted the importance of considering cloud cover when calculating degradation rates, finding more reliable values when the data are restricted to clear sky periods. Several automated methods of determining clear sky periods have been previously developed, but parameterizing and testing the models has been difficult. In this paper, we use clear sky classifications determined from satellite data to develop an algorithm that determines clear sky periods using only measured irradiance values and modeled clear sky irradiance as inputs. This method is tested on global horizontal irradiance (GHI) data from ground collectors at six sites across the United States and compared against independent satellite-based classifications. First, 30 separate models were optimized on each individual site at GHI data intervals of 1, 5, 10, 15, and 30 min (sampled on the first minute of the interval). The models had an average F 0.5 score of 0.949 ± 0.035 on a holdout test set. Next, optimizations were performed by aggregating data from different locations at the same interval, yielding one model per data interval. This paper yielded an average F 0.5 of 0.946 ± 0.037. A final, "universal" optimization that was trained on data from all sites at all intervals provided an F 0.5 score of 0.943 ± 0.040. The optimizations all provide improvements on a prior, unoptimized clear sky detection algorithm that produces F 0.5 scores that average to 0.903 ± 0.067. Our paper indicates that a single algorithm can accurately classify clear sky periods across locations and data sampling intervals.

Characterization of photovoltaic (PV) module materials throughout different stages of service life is crucial to understanding and improving the durability of these materials. Currently the large-scale of PV modules (>1 m2) is imbalanced with the small-scale of most materials characterization tools (≤1 cm2). Furthermore, understanding degradation mechanisms often requires a combination of multiple characterization techniques. Here, we present adaptations of three standard materials characterization techniques to enable mapping characterization over moderate sample areas (≥25 cm2). Contact angle, ellipsometry, and UV–vis spectroscopy are each adapted and demonstrated on two representative samples: a commercial multifunctional coating for PV glass and an oxide combinatorial sample library. Best practices are discussed for adapting characterization techniques for large-area mapping and combining mapping information from multiple techniques.

No abstract