Charge transfer and positron states at alkali-metal-covered nickel surfaces

We report calculations of the positron surface state on clean and alkali-metal- (Na,Cs) covered Ni surfaces. It is shown that the alkali adsorption increases the surface-state binding energy. With the lowering of the electron work function, this leads to positronium desorption energies which are weakly dependent on the alkali coverage, in agreement with the recent experiments of Gidley, Köymen, and Capehart. It is shown that the positron becomes mainly localized between the substrate and the overlayer, and that the lifetime is shorter for positrons on the alkali-metal-covered surface.Peer reviewe

Bayesian optimisation approach to quantify the effect of input parameter uncertainty on predictions of numerical physics simulations

An understanding of how input parameter uncertainty in the numerical simulation of physical models leads to simulation output uncertainty is a challenging task. Common methods for quantifying output uncertainty, such as performing a grid or random search over the model input space, are computationally intractable for a large number of input parameters, represented by a high-dimensional input space. It is therefore generally unclear as to whether a numerical simulation can reproduce a particular outcome (e.g. a set of experimental results) with a plausible set of model input parameters. Here, we present a method for efficiently searching the input space using Bayesian Optimisation to minimise the difference between the simulation output and a set of experimental results. Our method allows explicit evaluation of the probability that the simulation can reproduce the measured experimental results in the region of input space defined by the uncertainty in each input parameter. We apply this method to the simulation of charge-carrier dynamics in the perovskite semiconductor methyl-ammonium lead iodide MAPbI$_3$ that has attracted attention as a light harvesting material in solar cells. From our analysis we conclude that the formation of large polarons, quasiparticles created by the coupling of excess electrons or holes with ionic vibrations, cannot explain the experimentally observed temperature dependence of electron mobility

Bayesian parameter estimation for characterising mobile ion vacancies in perovskite solar cells

To overcome the challenges associated with poor temporal stability of perovskite solar cells, methods are required that allow for fast iteration of fabrication and characterisation, such that optimal device performance and stability may be actively pursued. Currently, establishing the causes of underperformance is both complex and time-consuming, and optimisation of device fabrication thus inherently slow. Here, we present a means of computational device characterisation of mobile halide ion parameters from room temperature current-voltage (J-V) measurements only, requiring $\sim 2$ hours of computation on basic computing resources. With our approach, the physical parameters of the device may be reverse modelled from experimental J-V measurements. In a drift-diffusion model, the set of coupled drift-diffusion partial differential equations cannot be inverted explicitly, so a method for inverting the drift-diffusion simulation is required. We show how Bayesian Parameter Estimation (BPE) coupled with a drift-diffusion perovskite solar cell model can determine the extent to which device parameters affect performance measured by J-V characteristics. Our method is demonstrated by investigating the extent to which device performance is influenced by mobile halide ions for a specific fabricated device. The ion vacancy density $N_0$ and diffusion coefficient $D_I$ were found to be precisely characterised for both simulated and fabricated devices. This result opens up the possibility of pinpointing origins of degradation by finding which parameters most influence device J-V curves as the cell degrades

Controlling ion kinetic energy distributions in laser produced plasma sources by means of a picosecond pulse pair

The next generation of lithography machines uses extreme ultraviolet (EUV) light originating from laser-produced plasma (LPP) sources, where a small tin droplet is ionized by an intense laser pulse to emit the requested light at 13.5 nm. Numerous irradiation schemes have been explored to increase conversion efficiency (CE), out of which a double-pulse approach comprising a weak picosecond Nd:YAG pre-pulse followed by a powerful pulse is considered to be very promising [1]. Nevertheless, even for such CE-optimized schemes, ion debris ejected from the plasma with kinetic energies up to several keV remain a factor that hampers the maximum performance of LPP sources. In this letter we propose a novel pre-pulse scheme consisting of a picosecond pulse pair at 1064 nm, which decreases the amount of undesirable fast ions, avoids back-reflections to the lasers and enables one to tailor the target shape.Comment: 12 pages, 3 figures, 45 reference

Expansion Dynamics After Laser-Induced Cavitation in Liquid Tin Microdroplets

The cavitation-driven expansion dynamics of liquid tin microdroplets is investigated, set in motion by the ablative impact of a 15-ps laser pulse. We combine high-resolution stroboscopic shadowgraphy with an intuitive fluid dynamic model that includes the onset of fragmentation, and find good agreement between model and experimental data for two different droplet sizes over a wide range of laser pulse energies. The dependence of the initial expansion velocity on these experimental parameters is heuristically captured in a single power law. Further, the obtained late-time mass distributions are shown to be governed by a single parameter. These studies are performed under conditions relevant for plasma light sources for extreme-ultraviolet nanolithography.Comment: 7 pages, 6 figure

Characteristics of white blood cell count in acute lymphoblastic leukemia : A COST LEGEND phenotype-genotype study

Background White blood cell count (WBC) as a measure of extramedullary leukemic cell survival is a well-known prognostic factor in acute lymphoblastic leukemia (ALL), but its biology, including impact of host genome variants, is poorly understood. Methods We included patients treated with the Nordic Society of Paediatric Haematology and Oncology (NOPHO) ALL-2008 protocol (N = 2347, 72% were genotyped by Illumina Omni2.5exome-8-Bead chip) aged 1-45 years, diagnosed with B-cell precursor (BCP-) or T-cell ALL (T-ALL) to investigate the variation in WBC. Spline functions of WBC were fitted correcting for association with age across ALL subgroups of immunophenotypes and karyotypes. The residuals between spline WBC and actual WBC were used to identify WBC-associated germline genetic variants in a genome-wide association study (GWAS) while adjusting for age and ALL subtype associations. Results We observed an overall inverse correlation between age and WBC, which was stronger for the selected patient subgroups of immunophenotype and karyotypes (rho(BCP-ALL )= -.17, rho(T-ALL )= -.19; p < 3 x 10(-4)). Spline functions fitted to age, immunophenotype, and karyotype explained WBC variation better than age alone (rho = .43, p << 2 x 10(-6)). However, when the spline-adjusted WBC residuals were used as phenotype, no GWAS significant associations were found. Based on available annotation, the top 50 genetic variants suggested effects on signal transduction, translation initiation, cell development, and proliferation. Conclusion These results indicate that host genome variants do not strongly influence WBC across ALL subsets, and future studies of why some patients are more prone to hyperleukocytosis should be performed within specific ALL subsets that apply more complex analyses to capture potential germline variant interactions and impact on WBC.Peer reviewe

Can Machine Learning Models Predict Asparaginase-associated Pancreatitis in Childhood Acute Lymphoblastic Leukemia

Publisher Copyright: © 2021 Lippincott Williams and Wilkins. All rights reserved.Asparaginase-associated pancreatitis (AAP) frequently affects children treated for acute lymphoblastic leukemia (ALL) causing severe acute and persisting complications. Known risk factors such as asparaginase dosing, older age and single nucleotide polymorphisms (SNPs) have insufficient odds ratios to allow personalized asparaginase therapy. In this study, we explored machine learning strategies for prediction of individual AAP risk. We integrated information on age, sex, and SNPs based on Illumina Omni2.5exome-8 arrays of patients with childhood ALL (N=1564, 244 with AAP aged 1.0 to 17.9 y) from 10 international ALL consortia into machine learning models including regression, random forest, AdaBoost and artificial neural networks. A model with only age and sex had area under the receiver operating characteristic curve (ROC-AUC) of 0.62. Inclusion of 6 pancreatitis candidate gene SNPs or 4 validated pancreatitis SNPs boosted ROC-AUC somewhat (0.67) while 30 SNPs, identified through our AAP genome-wide association study cohort, boosted performance (0.80). Most predictive features included rs10273639 (PRSS1-PRSS2), rs10436957 (CTRC), rs13228878 (PRSS1/PRSS2), rs1505495 (GALNTL6), rs4655107 (EPHB2) and age (1 to 7 y). Second AAP following asparaginase re-exposure was predicted with ROC-AUC: 0.65. The machine learning models assist individual-level risk assessment of AAP for future prevention trials, and may legitimize asparaginase re-exposure when AAP risk is predicted to be low.Peer reviewe

Genome-Wide Association Meta-Analysis of Single-Nucleotide Polymorphisms and Symptomatic Venous Thromboembolism during Therapy for Acute Lymphoblastic Leukemia and Lymphoma in Caucasian Children

Symptomatic venous thromboembolism (VTE) occurs in five percent of children treated for acute lymphoblastic leukemia (ALL), but whether a genetic predisposition exists across different ALL treatment regimens has not been well studied. Methods: We undertook a genome-wide association study (GWAS) meta-analysis for VTE in consecutively treated children in the Nordic/Baltic acute lymphoblastic leukemia 2008 (ALL2008) cohort and the Australian Evaluation of Risk of ALL Treatment-Related Side-Effects (ERASE) cohort. A total of 92 cases and 1481 controls of European ancestry were included. Results: No SNPs reached genome-wide significance (p <5 x 10(-8)) in either cohort. Among the top 34 single-nucleotide polymorphisms (SNPs) (p <1 x 10(-6)), two loci had concordant effects in both cohorts: ALOX15B (rs1804772) (MAF: 1%; p = 3.95 x 10(-7)) that influences arachidonic acid metabolism and thus platelet aggregation, and KALRN (rs570684) (MAF: 1%; p = 4.34 x 10(-7)) that has been previously associated with risk of ischemic stroke, atherosclerosis, and early-onset coronary artery disease. Conclusion: This represents the largest GWAS meta-analysis conducted to date associating SNPs to VTE in children and adolescents treated on childhood ALL protocols. Validation of these findings is needed and may then lead to patient stratification for VTE preventive interventions. As VTE hemostasis involves multiple pathways, a more powerful GWAS is needed to detect combination of variants associated with VTE.Peer reviewe