123 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    A synthetic population for agent-based modelling in Canada

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    In order to anticipate the impact of local public policies, a synthetic population reflecting the characteristics of the local population provides a valuable test bed. While synthetic population datasets are now available for several countries, there is no open-source synthetic population for Canada. We propose an open-source synthetic population of individuals and households at a fine geographical level for Canada for the years 2021, 2023 and 2030. Based on 2016 census data and population projections, the synthetic individuals have detailed socio-demographic attributes, including age, sex, income, education level, employment status and geographic locations, and are related into households. A comparison of the 2021 synthetic population with 2021 census data over various geographical areas validates the reliability of the synthetic dataset. Users can extract populations from the dataset for specific zones, to explore ‘what if’ scenarios on present and future populations. They can extend the dataset using local survey data to add new characteristics to individuals. Users can also run the code to generate populations for years up to 2042

    Filter-adapted spatiotemporal sampling for real-time rendering

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    Stochastic sampling techniques are ubiquitous in real-time rendering, where performance constraints force the use of low sample counts, leading to noisy intermediate results. To remove this noise, the post-processing step of temporal and spatial denoising is an integral part of the real-time graphics pipeline. The main insight presented in this paper is that we can optimize the samples used in stochastic sampling such that the post-processing error is minimized. The core of our method is an analytical loss function which measures post-filtering error for a class of integrands - multidimensional Heaviside functions. These integrands are an approximation of the discontinuous functions commonly found in rendering. Our analysis applies to arbitrary spatial and spatiotemporal filters, scalar and vector sample values, and uniform and non-uniform probability distributions. We show that the spectrum of Monte Carlo noise resulting from our sampling method is adapted to the shape of the filter, resulting in less noisy final images. We demonstrate improvements over state-of-the-art sampling methods in three representative rendering tasks: ambient occlusion, volumetric ray-marching, and color image dithering. Common use noise textures, and noise generation code is available at https://github.com/electronicarts/fastnoise.Comment: 18 pages, 12 figure

    Design of thin-film materials and explanation of their properties by atomic-level simulations

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    Disertační práce se zabývá teoretickým popisem pevných látek pomocí teorie funkcionálu hustoty. Studuje a rozvíjí vybrané prvky metodiky a předpovídá struktury a vlastnosti vybraných materiálů, převážně těch, jež jsou na katedře připravovány jako tenké vrstvy. Teoretické výsledky jsou proto často uváděny do souvislosti s experimentálními. Jednou ze skupin studovaných materiálů jsou kubické a hexagonální nitridy přechodových kovů včetně svých tuhých roztoků, ternárních nitridů (Hf,M)N (M = Y, Ho, Ta, Mo). Je zkoumána jejich stabilita a mechanické vlastnosti. Formovací energie roztoků závisí kromě krystalické struktury také na rozložení atomů Hf a M a pro některá složení a rozložení též na případném provedení geometrické optimalizace pozic atomů. Vypočítané vlastnosti krystalických MN and (Hf,M)N jsou dále vztaženy k vlastnostem amorfních Hf-M-Si-B-C-N, modelovaných pomocí ab initio molekulární dynamiky. Formovací energie MN je užitečnou měrou hybné síly k tvorbě vazeb M-N v Hf-M-Si-B-C-N. Její postupný nárůst s růstem číslem sloupce prvku M v periodické tabulce koreluje s poklesem podílu vazeb M-N na všech vazbách atomů M v Hf-M-Si-B-C-N či s delokalizací elektronových stavů a zúžením zakázaného pásu. Trend růstu kovovosti potvrzují i experimentální výsledky jako růst elektrické vodivosti a extinkčního koeficientu. Korelaci lze nalézt i mezi mechanickými vlastnostmi pro tenkovrstvé Hf-M-Si-B-C-N a modelované MN, a snadné výpočty vlastností MN tak jsou užitečnou metodu předpovědi trendů vlastností Hf-M-Si-B-C-N. Pro případ Hf-Y-Si-B-C-N je korelace modelu s experimentem prokázána také při rostoucím obsahu dusíku: vypočítaný pokles zastoupení vazeb neobsahujících N a vzdálení elektronových stavů od Fermiho meze vysvětlují pokles experimentálního extinkčního koeficientu a odpovídající rozšíření zakázaného pásu. Zvláštní pozornost je věnována magnetickému nitridu HoN. Výpočty ab initio týkající se elektronových struktur a souvisejících vlastností takového materiálu by měly správně reprodukovat jeho magnetický moment. Nejprve je určen počet neobsazených elektronových stavů, který zaručuje, že zjištěné energetické minimum je globální. Dále je vyvinuta metoda, která umožňuje, aby experimentální hodnota magnetizace tvořila energetické minimum, a je kladen důraz na příznivé rozložení spinů ve velké simulační buňce. Je prozkoumána závislost vybraných charakteristik HoN na velikosti buňky a magnetizaci. Tyto výsledky poskytují teoretický vhled do spinové struktury nitridů kovů vzácných zemin a umožňují použít správnou metodiku podobných výpočtů vlastností silně korelovaných materiálů. Pro bixbyitové Ta2N3 a Ta2N2O jsou vypočítány hustoty elektronových stavů, které jsou v případě Ta2N2O užity k vysvětlení jeho experimentálních vlastností, zejména existence jednoho optického a dvou elektrických zakázaných pásů. Je zkoumán také diborid (Ti,Zr,Hf,Ta)B2, zejména vliv poruch (jednak vakancí, a jednak atomů C, poruch relevantních pro četné experimenty) na charakteristiky materiálu. Jsou prozkoumány různé druhy, koncentrace i rozložení poruch a jsou rozpoznána uspořádání vedoucí na nejnižší formovací energie. Náhrada atomů B atomy C je méně výhodná než tvorba bórových vakancí. Vakance dále upřednostňují shlukování do rozsáhlejší plošné oblasti bez atomů, a minimalizují tak počet přerušených vazeb B-B, zatímco uhlíkové substituce na bórových pozicích shlukování neupřednostňují a mají sklon minimalizovat počet vazeb C-C. S koncentrací vakancí zároveň roste objem na atom. Tyto výsledky jsou využity k vysvětlení experimentálních jevů, jako je uvolnění kompresního pnutí při žíhání diboridů. Je kvantifikován také vliv vakancí na mechanické a elektronické vlastnosti.ObhájenoThe Ph.D. thesis deals with a theoretical description of the solid state by density-functional theory. It studies and develops selected components of the methodology and predicts the structures and properties of selected materials, predominantly those prepared as thin films at the department. Thus, the theoretical results are often associated to experimental ones. One class of the studied materials consists of cubic and hexagonal transition-metal nitrides, including their solid solutions, ternary nitrides (Hf,M)N (M = Y, Ho, Ta, Mo). We study their stability and mechanical properties. The solution formation energy depends not only on the crystal structure but also on the distribution of Hf and M atoms and, for some cases, on the decision to perform structural relaxation. The calculated properties of crystalline MN and (Hf,M)N are then associated with the properties of amorphous Hf-M-Si-B-C-N, modelled by ab initio molecular dynamics. Formation energy of MN is a useful measure of the driving force towards M-N bond formation in Hf-M-Si-B-C-N. Its increase with the M periodic-table group number correlates with the decrease in the ratio of the number of M-N bonds to the total number of M bonds in Hf-M-Si-B-C-N as well as with the delocalisation of electronic states and narrowing of the band gap. The growing trend in the metallicity is confirmed also by experimental results such as the growth of electrical conductivity and extinction coefficient. In addition, correlation is found between mechanical properties of thin-film Hf-M-Si-B-C-N and modelled MN, so the easy calculations of MN properties are a useful method for the prediction of the trends in the Hf-M-Si-B-C-N properties. For the case of Hf-Y-Si-B-C-N, the correlation of the model and experiment is proven also at growing nitrogen content: the calculated decrease in the number of N-less bonds and the retreat of the electronic states from the Fermi level explain the decrease of the experimental extinction coefficient and the corresponding band-gap broadening. Attention is paid to the magnetic nitride HoN. Ab initio calculations of electronic structures and related properties should correctly reproduce its magnetic moment. First, the number of unoccupied electronic states is identified which guarantees that the energy minimum identified is the global one. A method is then developed which allows the experimental magnetisation to constitute an energy minimum, emphasising the favourable spin distribution in a large simulation cell. The dependence of selected HoN characteristics on cell size and magnetisation is examined. These findings provide a theoretical insight into the spin structure of rare-earth metal nitrides and allow one to use the correct methodology of similar calculations of properties of strongly correlated materials. For bixbyite Ta2N3 and Ta2N2O, densities of electronic states are calculated and in the case of Ta2N2O used to explain experimental properties like the existence of one optical and two electrical band gaps. The diboride (Ti,Zr,Hf,Ta)B2 is studied, too, mainly the effect of defects (either vacancies or C atoms, both relevant for numerous experiments) on material characteristics. Different types, concentrations and distributions of defects are investigated, and the configurations leading to the lowest formation energies are identified. The replacement of B by C is more unfavourable than the formation of B vacancies. Furthermore, vacancies prefer to coalesce into a larger planar void, minimising the number of broken B-B bonds, while C substitutions at B sites do not prefer coalescence and minimise the number of C-C bonds. In parallel, the volume per atom increases with the vacancy concentration. These results are used to explain experimental phenomena such as the stress release during annealing. In addition, the effect of vacancies on mechanical and electronic properties is quantified

    Study of Radiation Damage and Defect Evolution in Nanostructured Metals Via Atomistic and Meso-Scale Simulation Techniques

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    This dissertation describes the computational studies that explore the atomistic mechanisms and characteristics of radiation damage formation, and how these properties and behaviors contribute to the radiation tolerance of nanostructured materials. The need for materials that can withstand radiation environments for extended periods of time has increased as we have developed more advanced nuclear technologies. Both experiments and computational simulations have shown that nanostructured materials with high densities of defect sinks such as grain boundaries or free surfaces have enhanced radiation tolerance, being able to withstand high radiation doses without accumulating radiation damage in the same ways as conventionally structured materials. What remains to be determined are the atomistic mechanisms that allow for these microstructures to inhibit the formation and accumulation of radiation damage, as well as a determination of how these microstructures will evolve under continued exposure to radiation environments. To that end, we have used computational techniques to study radiation damage across the range of length- and time-scales within which it develops, with an emphasis on considering the impact that microstructure and defect configuration have on the formation and evolution of radiation damage. Atomistic simulations were used to compute point defect energetics in single crystal niobium and uranium-zirconium alloys as well as to probe radiation damage mechanisms in niobium and gold nanostructures. Additionally, a phase field model was developed to simulate atomic segregation in binary alloys due to radiation-induced defect formation.Ph.D

    Defects in high-entropy alloys studied by atomic scale computer simulations

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    High-entropy alloys (HEAs) are a new class of metal alloys containing multiple principal elements in concentrations between 5-35 at%. Due to their inherent chemical complexity, they possess a wide range of interesting properties, which we explore in greater detail throughout this thesis. Reduced or sluggish diffusion has been discussed for HEAs since their inception. We perform time-scale bridging simulations on the pseudo-binary (CoCrFeMn)_(1-x)Ni_x HEA, combining atomistic simulations of the vacancy migration energies and equilibrium vacancy concentrations with kinetic Monte Carlo simulations of tracer diffusion trajectories. Here, we extend the established random alloy model to account for the local chemical fluctuations within the complex alloy matrix. The results compare favorably to experimental tracer diffusion measurements. Dislocations in HEAs also interact with chemical fluctuations in the random matrix. This leads to a meandering dislocation line shape and localized pinning during dislocation glide. We find a physically motivated descriptor for these pinning sites in the form of a per-atom Peierls force. This descriptor shows good spatial correlation with observed dislocation pinning sites during glide. Furthermore, we show that the density of strong pinning sites in an alloy correlates not only with the critical shear required to initiate dislocation glide but also the dislocation mobility. We report on the grain growth properties of a CoCuFeNi model HEA. Atomistic simulations give unique insights into the effects of random chemical fluctuations by comparison of the HEA to its average-atom counterpart. The average-atom is a virtual element which has the same long-range properties as the alloy but consists only of a single element. Additionally, solute segregation to grain boundaries (GBs) is considered. The comparison of two different samples, namely a Sigma 11 GB and a large-scale nanocrystalline sample, reveals that while grain growth is reduced in the HEA compared to other pure metals, this does not stem from the chemical randomness. Instead, solute segregation is necessary to pin GBs up to high temperatures

    Advanced Magnetic Nanocomposites

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    This book is a collection of research articles and review articles, which was published in the Special Issue "Advanced Magnetic Nanocomposites: Structural, Physical Properties and Application". This book ‘‘Advanced Magnetic Nanocomposites: Structural, Physical Properties and Application’’ discussed recent development on advanced magnetic nanoparticles and nanocomposites with detailed explanation of structural and physical characteristics, and further possible potential application

    Synthesis, Properties and Applications of Germanium Chalcogenides

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    Germanium (Ge) chalcogenides are characterized by unique properties that make these materials interesting for a very wide range of applications from phase change memories to ovonic threshold switches and from photonics to thermoelectric and photovoltaic devices. In many cases, their physical properties can be finely tuned by doping or by changing the amount of Ge, which may therefore play a key role in determining the applications, performance, and even the reliability of these devices. In this book, we include 11 articles, mainly focusing on applications of Ge chalcogenides for non-volatile memories. Most of the papers have been produced with funding received from the European Union’s Horizon 2020 Research and Innovation program under grant agreement n. 824957. In the Special Issue “BeforeHand: Boosting Performance of Phase Change Devices by Hetero- and Nanostructure Material Design”, two contributions are related to the prototypical Ge2Sb2Te5 compound, which is the most studied composition, already integrated in many devices such as optical and electronic memories. Five articles focus on Ge-rich GeSbTe alloys, exploring the electrical and the structural properties, as well as the decomposition paths. Other contributions are focused on the effect of the interfaces and on nanowires

    Strong absorption and ultrafast localisation in NaBiS2 nanocrystals with slow charge carrier recombination

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    I V VI2 ternary chalcogenides are gaining attention as earth abundant, nontoxic, and air stable absorbers for photovoltaic applications. However, the semiconductors explored thus far have slowly rising absorption onsets, and their charge carrier transport is not well understood yet. Herein, we investigate cation disordered NaBiS2 nanocrystals, which have a steep absorption onset, with absorption coefficients reaching gt;105 cm amp; 8722;1 just above its pseudo direct bandgap of 1.4 eV. Surprisingly, we also observe an ultrafast picosecond time scale photoconductivity decay and long lived charge carrier population persisting for over onemicrosecond in NaBiS2 nanocrystals. These unusual features arise because of the localised, non bonding S p character of the upper valence band, which leads to a high density of electronic states at the band edges, ultrafast localisation of spatially separated electrons and holes, as well as the slow decay of trapped holes. Thiswork reveals the critical role of cation disorder in these systems on both absorption characteristics and charge carrier kinetic

    Sensitivity Analysis

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    Sensitivity analysis (SA), in particular global sensitivity analysis (GSA), is now regarded as a discipline coming of age, primarily for understanding and quantifying how model results and associated inferences depend on its parameters and assumptions. Indeed, GSA is seen as a key part of good modelling practice. However, inappropriate SA, such as insufficient convergence of sensitivity metrics, can lead to untrustworthy results and associated inferences. Good practice SA should also consider the robustness of results and inferences to choices in methods and assumptions relating to the procedure. Moreover, computationally expensive models are common in various fields including environmental domains, where model runtimes are long due to the nature of the model itself, and/or software platform and legacy issues. To extract using GSA the most accurate information from a computationally expensive model, there may be a need for increased computational efficiency. Primary considerations here are sampling methods that provide efficient but adequate coverage of parameter space and estimation algorithms for sensitivity indices that are computationally efficient. An essential aspect in the procedure is adopting methods that monitor and assess the convergence of sensitivity metrics. The thesis reviews the different categories of GSA methods, and then it lays out the various factors and choices therein that can impact the robustness of a GSA exercise. It argues that the overall level of assurance, or practical trustworthiness, of results obtained is engendered from consideration of robustness with respect to the individual choices made for each impact factor. Such consideration would minimally involve transparent justification of individual choices made in the GSA exercise but, wherever feasible, include assessment of the impacts on results of plausible alternative choices. Satisfactory convergence plays a key role in contributing to the level of assurance, and hence the ultimate effectiveness of the GSA can be enhanced if choices are made to achieve that convergence. The thesis examines several of these impact factors, primary ones being the GSA method/estimator, the sampling method, and the convergence monitoring method, the latter being essential for ensuring robustness. The motivation of the thesis is to gain a further understanding and quantitative appreciation of elements that shape and guide the results and computational efficiency of a GSA exercise. This is undertaken through comparative analysis of estimators of GSA sensitivity measures, sampling methods and error estimation of sensitivity metrics in various settings using well-established test functions. Although quasi-Monte Carlo Sobol' sampling can be a good choice computationally, it has error spike issues which are addressed here through a new Column Shift resampling method. We also explore an Active Subspace based GSA method, which is demonstrated to be more informative and computationally efficient than those based on the variance-based Sobol' method. Given that GSA can be computationally demanding, the thesis aims to explore ways that GSA can be more computationally efficient by: addressing how convergence can be monitored and assessed; analysing and improving sampling methods that provide a high convergence rate with low error in sensitivity measures; and analysing and comparing GSA methods, including their algorithm settings
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