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The ability of some white rot basidiomycetes to remove lignin selectively from wood indicates that low molecular weight oxidants have a role in ligninolysis. These oxidants are likely free radicals generated by fungal peroxidases from compounds in the biodegrading wood. Past work supports a role for manganese peroxidases (MnPs) in the production of ligninolytic oxidants from fungal membrane lipids. However, the fatty acid alkylperoxyl radicals initially formed during this process are not reactive enough to attack the major structures in lignin. Here, we evaluate the hypothesis that the peroxidation of fatty aldehydes might provide a source of more reactive acylperoxyl radicals. We found that Gelatoporia subvermispora produced trans-2-nonenal, trans-2-octenal, and n-hexanal (a likely metabolite of trans-2,4-decadienal) during the incipient decay of aspen wood. Fungal fatty aldehydes supported the in vitro oxidation by MnPs of a nonphenolic lignin model dimer, and also of the monomeric model veratryl alcohol. Experiments with the latter compound showed that the reactions were partially inhibited by oxalate, the chelator that white rot fungi employ to detach Mn3+ from the MnP active site, but nevertheless proceeded at its physiological concentration of 1 mM. The addition of catalase was inhibitory, which suggests that the standard MnP catalytic cycle is involved in the oxidation of aldehydes. MnP oxidized trans-2-nonenal quantitatively to trans-2-nonenoic acid with the consumption of one O2 equivalent. The data suggest that when Mn3+ remains associated with MnP, it can oxidize aldehydes to their acyl radicals, and the latter subsequently add O2 to become ligninolytic acylperoxyl radicals.IMPORTANCEThe biodegradation of lignin by white rot fungi is essential for the natural recycling of plant biomass and has useful applications in lignocellulose bioprocessing. Although fungal peroxidases have a key role in ligninolysis, past work indicates that biodegradation is initiat

We demonstrate that the Berry curvature of an isolated Bloch miniband in two-dimensional superlattices can be probed by the dressed linear optical response when a uniform static field is applied to the system. In particular, when the static field is sufficiently strong such that full Bloch oscillations occur before the crystal momentum relaxes to equilibrium, the optical response of the dressed system becomes resonant at the Bloch frequencies. The latter are in the THz regime when the superlattice periodicity is of the order of 10 nm. Using a band-projected semiclassical theory, we define a dressed optical conductivity and find that the height of the resonances in the dressed Hall conductivity are proportional to the Fourier components of the Berry curvature. We illustrate our results with a low-energy model on an effective honeycomb lattice.

Prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can guarantee to find optimal solutions efficiently. We experimentally explore a novel approach to this problem by using a D-Wave quantum computer, benchmarking its performance for attaining financial equilibrium. To be specific, the equilibrium condition of a nonlinear financial model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then transformed to a spin-1/2 Hamiltonian with at most two-qubit interactions. The problem is thus equivalent to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum annealer. The size of the simulation is mainly constrained by the necessity of a large quantity of physical qubits representing a logical qubit with the correct connectivity. Our experiment paves the way to codify this quantitative macroeconomics problem in quantum computers.

The high luminosity upgrade of the Large Hadron Collider, foreseen for 2029, requires the replacement of the ATLAS Inner Detector with a new all-silicon Inner Tracker (ITk). The expected ultimate total integrated luminosity of 4000 fb−1 means that the strip part of the ITk detector will be exposed to the total particle fluences and ionizing doses reaching the values of 1.6⋅1015MeVneq/cm2 and 0.66MGy, respectively, including a safety factor of 1.5. Radiation hard n+-in-p micro-strip sensors were developed by the ATLAS ITk strip collaboration and are produced by Hamamatsu Photonics K.K. The active area of each ITk strip sensor is delimited by the n-implant bias ring, which is connected to each individual n+ implant strip by a polysilicon bias resistor. The total resistance of the polysilicon bias resistor should be within a specified range to keep all the strips at the same potential, prevent the signal discharge through the grounded bias ring and avoid the readout noise increase. While the polysilicon is a ubiquitous semiconductor material, the fluence and temperature dependence of its resistance is not easily predictable, especially for the tracking detector with the operational temperature significantly below the values typical for commercial microelectronics. Dependence of the resistance of polysilicon bias resistor on the temperature, as well as on the total delivered fluence and ionizing dose, was studied on the specially-designed test structures called ATLAS Testchips, both before and after their irradiation by protons, neutrons, and gammas to the maximal expected fluence and ionizing dose. The resistance has an atypical negative temperature dependence. It is different from silicon, which shows that the grain boundary has a significant contribution to the resistance. We discuss the contributions by parameterizing the activation energy of the polysilicon resistance as a function of the temperature for unirradiated and irradiated ATLAS Testchips.

[EN] This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

[EN] Double electron capture by proton-rich nuclei is a second-order nuclear process analogous to double beta decay. Despite their similarities, the decay signature is quite di erent, potentially providing a new channel to measure the hypothesized neutrinoless mode of these decays. The Standard-Model-allowed two-neutrino double electron capture has been predicted for a number of isotopes, but only observed in 78Kr, 130Ba and, recently, 124Xe. The sensitivity to this decay establishes a benchmark for the ultimate experimental goal, namely the potential to discover also the lepton-number-violating neutrinoless version of this process. Here we report on the current sensitivity of the NEXT-White detector to 124Xe 2 ECEC and on the extrapolation to NEXT-100. Using simulated data for the 2 ECEC signal and real data from NEXT-White operated with 124Xe-depleted gas as background, we de ne an optimal event selection that maximizes the NEXT-White sensitivity. We estimate that, for NEXT-100 operated with xenon gas isotopically enriched with 1 kg of 124Xe and for a 5-year run, a sensitivity to the two-neutroni double electron capture half-life of 6x10exp22 years (at 90% con dence level) or better can be reached.

[EN] Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses

[EN] Rh2P nanoparticles (NPs) have been identified as suitable mimics of [Rh-I(Ph3P)(3)](+), the benchmark of homogeneous catalysts in liquid-phase hydroformylation. For this reason, a fitted synthetic strategy is required to develop catalysts based exclusively on Rh2P NPs. To attain this, two synthetic pathways have been devised. In the first one, two separate sources of Rh and P were used. In the second one, the Wilkinson complex was employed as a unique source of Rh and P to probe the positive influence of the well-defined molecular organization on the preparation of dispersed and controlled Rh2P nanoparticles, stabilized by carbon patches formed during the pyrolysis treatment from PPh3. In addition, metallic Rh nanoparticles were also synthesized to be used as reference. All catalysts have been compared by means of: transmission electron microscopy, Xray diffraction, and X-ray adsorption spectroscopy. The application of XAS to the study of Rh2P NPs is unusual and has been essential in the discussion of the results. Starting with a well-defined metal precursor leads to the exclusive formation of Rh2P NPs with excellent catalytic activity for the liquid-phase hydroformylation. The role of P is to modulate the particle size and the electronic configuration of Rh species, resulting in the improvement of the catalytic performance and the obtention of turnover frequencies of 5236 h(-1) at 60 degrees C and 17,788 h(-1) at 100 degrees C.

© ACM, 2021. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Mathematical Software, Volume 47, Issue , June 2021, http://doi.acm.org/10.1145/3441850, [EN] The use of mixed precision in numerical algorithms is a promising strategy for accelerating scientific applications. In particular, the adoption of specialized hardware and data formats for low-precision arithmetic in high-end GPUs (graphics processing units) has motivated numerous efforts aiming at carefully reducing the working precision in order to speed up the computations. For algorithms whose performance is bound by the memory bandwidth, the idea of compressing its data before (and after) memory accesses has received considerable attention. One idea is to store an approximate operator-like a preconditioner-in lower than working precision hopefully without impacting the algorithm output. We realize the first high-performance implementation of an adaptive precision block-Jacobi preconditioner which selects the precision format used to store the preconditioner data on-the-fly, taking into account the numerical properties of the individual preconditioner blocks. We implement the adaptive block-Jacobi preconditioner as production-ready functionality in the Ginkgo linear algebra library, considering not only the precision formats that are part of the IEEE standard, but also customized formats which optimize the length of the exponent and significand to the characteristics of the preconditioner blocks. Experiments run on a state-of-the-art GPU accelerator show that our implementation offers attractive runtime savings.

[EN] Experimental results from a study on the evolution of gas jets ejected through the orifices of a pre-chamber in a heavy-duty optical engine are presented. The work examines conditions without fuel inside the main-chamber, which helps to describe the dynamics of the ejected gas jets without the interference of subsequent combustion in the main-chamber. Experimental diagnostics consist of high-speed visible intensified imaging and low-speed infrared imaging. Additionally a one-dimensional gas jet model is used to characterize the spatial distribution of the ejected flow, including parameters such as tip penetration, which are then validated based on experimental results. Different stages in the ejection of pre-chamber jets are identified, with chemical activity restricted to a maximum distance of 5 to 10 orifice diameters downstream of the orifice as indicated by the recorded visible radiation. Sensitivity of cycle-to-cycle variations in pre-chamber jet development to the air-to-fuel ratio in the pre-chamber observed in the experiments is in most part attributed to the variations in the timing of combustion initiation in the pre-chamber. The influence of the ejection flow on the penetration of the gas jet on a cycle-tocycle basis is presented using the one-dimensional model. The one-dimensional model also indicates that the local flow exhibits highest sensitivity to operating conditions during the start of ejection until the timing when maximum flow is attained. Differences that exist during the decreasing mass-flow ejection time-period tend to smear out in part due to the transient slowdown of the ejection process

[EN] Microwave-assisted catalysis is an emerging route for reactor modularization and decarbonization of chemical manufacturing with energy-intensive reactions. While laboratory-scale microwave-assisted heterogeneous catalytic reactors are being developed, hot spots and reactor stability under increased catalyst inventory remain impediments for high throughput processing. Here, we engineer the electromagnetic field-material interactions by introducing a packed monolith configuration, consisting of a microwave absorbing monolith filled with catalytic pellets. Electromagnetic simulations reveal the crucial role of monolith electrical conductivity in diminishing the local power dissipation between the pellets' contact points by absorbing the heat directly. Compared to traditional fixed beds, where hot spots form within minutes of operation, and catalyst-coated monoliths, whose active catalyst loading is limited, the proposed system is stable at all tested temperatures up to 900 C and has a catalyst packing density near that of fixed beds. We demonstrate its versatility first on the ethane dehydrogenation to produce ethylene over a Ga2O3/Al2O3 catalyst. Repeatable performance over multiple cycles of reaction and regeneration highlights long-term operation. Second, the dry reforming of methane (CH4) is carried out over a commercial Rh/Al2O3 catalyst, achieving a high (-86%) CH4 conversion with an order of magnitude higher H2 throughput (-85 m3/kg/hr) than previous laboratory-scale reactors. By enhancing the catalyst inventory, packed monoliths create a potential avenue for broader adoption of microwave-assisted heterogeneous catalytic reactors.

[EN] Pre-chamber spark-ignition (PCSI), either fueled or non-fueled, is a leading concept with the potential to enable diesel-like efficiency in medium-duty (MD) and heavy-duty (HD) natural gas (NG) engines. However, the inadequate scientific base and simulation tools to describe/predict the underlying processes governing PCSI systems is one of the key barriers to market penetration of PCSI for MD/HD NG engines. To this end, experiments were performed in a heavy-duty, optical, single-cylinder engine fitted with an active fueled PCSI module. The spatial and temporal progress of ignition and subsequent combustion of lean-burn natural gas using PCSI system were studied using optical diagnostic imaging and heat release analysis based on main-chamber and pre-chamber pressure measurements. Optical diagnostics involving simultaneous infrared (IR) and high-speed (30 kfps) broadband and filtered OH* chemiluminescence imaging are used to probe the combustion process. Following the early pressure rise in the pre-chamber, IR imaging reveals initial ejection of unburnt fuel-air mixture from the pre chamber into the main-chamber. Following this, the pre-chamber gas jets exhibit chemical activity in the vicinity of the pre-chamber region followed by a delayed spread in OH* chemiluminescence, as they continue to penetrate further into the main-chamber. The OH* signal progress radially until the pre-chamber jets merge, which sets up the limit to a first stage, jet-momentum driven, mixing-controlled (temperature field) premixed combustion. This is then followed by the subsequent deceleration of the pre-chamber jets, caused by the decrease in the driving pressure difference (AP) as well as charge entrainment, resulting in a flame front evolution, where mixing is not the only driver. Chemical-kinetic calculations probe the possibility of flame propagation or sequential auto-ignition in the second stage of combustion. Finally, key phenomenological features are then summarized so as to p

[EN] High pressure xenon Time Projection Chambers (TPC) based on secondary scintillation (electroluminescence) signal amplification are being proposed for rare event detection such as directional dark matter, double electron capture and double beta decay detection. The discrimination of the rare event through the topological signature of primary ionisation trails is a major asset for this type of TPC when compared to single liquid or double-phase TPCs, limited mainly by the high electron diffusion in pure xenon. Helium admixtures with xenon can be an attractive solution to reduce the electron diffu- sion significantly, improving the discrimination efficiency of these optical TPCs. We have measured the electroluminescence (EL) yield of Xe-He mixtures, in the range of 0 to 30% He and demonstrated the small impact on the EL yield of the addition of helium to pure xenon. For a typical reduced electric field of 2.5 kV/cm/bar in the EL region, the EL yield is lowered by similar to 2%, 3%, 6% and 10% for 10%, 15%, 20% and 30% of helium concentration, respectively. This decrease is less than what has been obtained from the most recent simulation framework in the literature. The impact of the addition of helium on EL statistical fluctuations is negligible, within the experimental uncertainties. The present results are an important benchmark for the simulation tools to be applied to future optical TPCs based on Xe-He mixtures.

[EN] Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. However, the reflectance of PTFE is a function of its thickness. In this work, we investigate this dependence in air for light of wavelengths 260 nm and 450 nm using two complementary methods. We find that PTFE reflectance for thicknesses from 5 mm to 10 mm ranges from 92.5% to 94.5% at 450 nm, and from 90.0% to 92.0% at 260 nm We also see that the reflectance of PIFE of a given thickness can vary by as much as 2.7% within the same piece of material. Finally, we show that placing a specular reflector behind the PTFE can recover the loss of reflectance in the visible without introducing a specular component in the reflectance.

[EN] Xe-136 is used as the target medium for many experiments searching for 0 nu beta beta. Despite underground operation, cosmic muons that reach the laboratory can produce spallation neutrons causing activation of detector materials. A potential background that is difficult to veto using muon tagging comes in the form of Xe-137 created by the capture of neutrons on Xe-136. This isotope decays via beta decay with a half-life of 3.8 min and a Q(beta) of similar to 4.16 MeV. This work proposes and explores the concept of adding a small percentage of He-3 to xenon as a means to capture thermal neutrons and reduce the number of activations in the detector volume. When using this technique we find the contamination from Xe-137 activation can be reduced to negligible levels in tonne and multi-tonne scale high pressure gas xenon neutrinoless double beta decay experiments running at any depth in an underground laboratory.

[EN] As computational capabilities continue to grow, exploring the limits of computational fluid dynamics to capture complex and elusive phenomena, which are otherwise difficult to study by experimental techniques, is one of the main targets for the research community. This paper presents a detailed analysis of the physical processes that lead to combustion noise emissions in internal combustion engines. In particular, diesel combustion in a compression-ignition (CI) engine is studied in order to understand the singular behavior of the in-cylinder flow field responsible for the acoustic emissions. The main objective is, therefore, to improve the understanding of the phenomena involved in CI engine noise using large eddy simulations. Several visualization methods are employed to investigate the connection between combustion behavior and its effects on the pressure field. In addition, proper orthogonal decomposition is used to analyze the modal energy distribution among all the acoustic modes. The results show that the acoustic signature is fundamentally conditioned by the intensity of the premixed combustion rather than by the pressure oscillations generated by turbulent fluctuations in the flame surface established during the diffusion stage.

[EN] New compact engine architectures such as pressure gain combustion require ad hoc turbomachinery to ensure an adequate range of operation with high performance. A critical factor for supersonic turbines is to ensure the starting of the flow passages, which limits the flow turning and airfoil thickness. Radial outflow turbines inherently increase the cross section along the flow path, which holds great potential for high turning of supersonic flow with a low stage number and guarantees a compact design. First, the preliminary design space is described. Afterward a differential evolution multi-objective optimization with 12 geometrical design parameters is deducted. With the design tool autoblade 10.1, 768 geometries were generated and hub, shroud, and blade camber line were designed by means of Bezier curves. Outlet radius, passage height, and axial location of the outlet were design variables as well. Structured meshes with around 3.7 x 10(6) cells per passage were generated. Steady three-dimensional (3D) Reynolds-averaged Navier-Stokes (RANS) simulations, enclosed by the k-omega shear stress transport turbulence model were solved by the commercial solver CFD++. The geometry was optimized toward low entropy and high-power output. To prove the functionality of the new turbine concept and optimization, a full wheel unsteady RANS simulation of the optimized geometry exposed to a nozzled rotating detonation combustor (RDC) has been performed and the advantageous flow patterns of the optimization were also observed during transient operation.

[EN] Post-injection fuel dribble is known to lead to incomplete atomisation and combustion due to the release of slow-moving, and often surface-bound, liquid fuel after the end of injection. This can have a negative effect on engine emissions, performance and injector durability. To better quantify this phenomenon, we developed an image-processing approach to measure the volume of ligaments produced during the end of injection. We applied our processing approach to an Engine Combustion Network 'Spray B' 3-hole injector, using datasets from 220 injections generated by different research groups, to decouple the effect of gas temperature and pressure on the fuel dribble process. High-speed X-ray phase-contrast images obtained at room temperature conditions (297 K) at the Advanced Photon Source at Argonne National Laboratory, together with diffused back-illumination images captured at a wide range of temperature conditions (293-900 K) by CMT Motores Termicos were analysed and compared quantitatively. We found a good agreement between image sets obtained by Argonne National Laboratory and CMT Motores Termicos using different imaging techniques. The maximum dribble volume within the field of view of the imaging system and the mean rate of fuel dribble were considered as characteristic parameters of the fuel dribble process. Analysis showed that the absolute mean dribble rate increases with temperature when injection pressure is higher than 1000 bar and slightly decreases at high injection pressures (>500 bar) when temperature is close to 293 K. Larger maximum volumes of the fuel dribble were observed at lower gas temperatures (similar to 473 K) and low gas pressures (<30 bar), with a slight dependence on injection pressure.

[EN] Titanosilicate zeolites are catalysts of interest in the field of fine chemicals. However, the generation and accessibility of active sites in titanosilicate materials for catalyzing reactions with large molecules is still a challenge. Herein, we prepared titanosilicate zeolite precursors with open zeolitic structures, tunable pore sizes, and controllable Si/Ti ratios through a hydrothermal crystallization strategy by using quaternary ammonium templates. A series of quaternary ammonium ions are discovered as effective organic templates. The prepared amorphous titanosilicate zeolites with some zeolite framework structural order have extra-large micropores and abundant octahedrally coordinated isolated Ti species, which lead to a superior catalytic performance in the oxidative desulfurization of dibenzothiophene (DBT) and epoxidation of cyclohexene. It is anticipated that the amorphous prezeolitic titanosilicates will benefit the catalytic conversion of bulky molecules in a wide range of reaction processes.

This is the peer reviewed version of the following article: L. Liu, M. Lopez-Haro, D. M. Meira, P. Concepcion, J. J. Calvino, A. Corma, Angew. Chem. Int. Ed. 2020, 59, 15695, which has been published in final form at https://doi.org/10.1002/anie.202005621. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving., [EN] Preparation of supported metal catalysts with uniform particle size and coordination environment is a challenging and important topic in materials chemistry and catalysis. In this work, we report the regioselective generation of single-site Ir atoms and their evolution into stabilized subnanometric Ir clusters in MWW zeolite, which are located at the 10MR window connecting the two neighboring 12MR supercages. The size of the subnanometric Ir clusters can be controlled by the post-synthesis treatments and maintain below 1 nm even after being reduced at 650 degrees C, which cannot be readily achieved with samples prepared by conventional impregnation methods. The high structure sensitivity, size-dependence, of catalytic performance in the alkane hydrogenolysis reaction of Ir clusters in the subnanometric regime is evidenced.

[EN] The selective incorporation of isolated framework Lewis acid sites at specific crystallographic positions in high-silica zeolites was achieved by applying a rationalized post-synthetic grafting methodology. The removal of framework Ge atoms from a Ge-BEC zeolite with low concentrations of Ge in the framework (Si/Ge similar to 150) followed by grafting allows the synthesis of Sn-BEC zeolites with Sn atoms positionally biased into the double-4-ring (D4R) crystallographic positions of the BEC framework. Spectroscopic characterization using solid-state nuclear magnetic resonance (NMR) coupled with theoretical calculations revealed that Sn atoms preferentially form open Sn sites in the D4R of Sn-BEC. This observation was supported by IR spectra of adsorbed deuterated acetonitrile (CD3CN), a known titrant of Sn sites in zeolites. The catalytic implications of selective incorporation of open Sn sites in Sn-BEC were probed using the Meerwein-Ponndorf-Verley-Oppenauer (MPVO) reaction. Although the MPVO turnover rates normalized by the total number of open Sn sites were comparable on Sn-BEC and a conventional Sn-Beta catalyst synthesized in fluoride media (Sn-Beta(F)), Sn-BEC demonstrated higher per gram reaction rates because of its larger fraction of open sites compared to Sn-Beta(F). These results highlight the advantage of placing active sites in targeted locations within a zeolite structure. The methodology presented here to selectively place catalytic active sitesviasacrificial heteroatoms, such as Ge, can be generalized for the design of many other tetrahedrally-coordinated metal-containing zeolites.

© 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] With the appearance of multi-/many core machines, applications and runtime systems have evolved in order to exploit the new on-node concurrency brought by new software paradigms. POSIX threads (Pthreads) was widely-adopted for that purpose and it remains as the most used threading solution in current hardware. Lightweight thread (LWT) libraries emerged as an alternative offering lighter mechanisms to tackle the massive concurrency of current hardware. In this article, we analyze in detail the most representative threading libraries including Pthread- and LWT-based solutions. In addition, to examine the suitability of LWTs for different use cases, we develop a set of microbenchmarks consisting of OpenMP patterns commonly found in current parallel codes, and we compare the results using threading libraries and OpenMP implementations. Moreover, we study the semantics offered by threading libraries in order to expose the similarities among different LWT application programming interfaces and their advantages over Pthreads. This article exposes that LWT libraries outperform solutions based on operating system threads when tasks and nested parallelism are required.

[EN] We describe the application of a communication-reduction technique for the PageRank algorithm that dynamically adapts the precision of the data access to the numerical requirements of the algorithm as the iteration converges. Our variable-precision strategy, using a customized precision format based on mantissa segmentation (CPMS), abandons the IEEE 754 single- and double-precision number representation formats employed in the standard implementation of PageRank, and instead handles the data in memory using a customized floating-point format. The customized format enables fast data access in different accuracy, prevents overflow/underflow by preserving the IEEE 754 double-precision exponent, and efficiently avoids data duplication, since all bits of the original IEEE 754 double-precision mantissa are preserved in memory, but re-organized for efficient reduced precision access. With this approach, the truncated values (omitting significand bits), as well as the original IEEE double-precision values, can be retrieved without duplicating the data in different formats. Our numerical experiments on an NVIDIA V100 GPU (Volta architecture) and a server equipped with two Intel Xeon Platinum 8168 CPUs (48 cores in total) expose that, compared with a standard ieee double-precision implementation, the CPMS-based PageRank completes about 10% faster if high-accuracy output is needed, and about 30% faster if reduced output accuracy is acceptable.

[EN] Metal-organic framework (MOF)-driven synthesis is considered as a promising alternative for the development of new catalytic materials with well-designed active sites. This synthetic approach is used here to gradually transform a new bimetallic MOF, with Pd and Fe as the metal components, by the in situ generation of aniline under mild conditions. This methodology results in a compositionally homogeneous nanocomposite formed by Fe-doped Pd nanoparticles that, in turn, are supported on iron oxide-doped carbon. The nanocomposite has been fully characterized by several techniques such as IR and Raman spectroscopy, TEM, XPS, and XAS. The performance of this nanocomposite as an heterogeneous catalyst for hydrogenation of nitroarenes and nitrobenzene coupling with benzaldehyde has been evaluated, proving it to be an efficient and reusable catalyst.

[EN] Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity- induced backgrounds are measured with the NEXT-White detector. Data from 37.9 days of low-background operations at the Laboratorio Subterraneo de Canfranc with xenon depleted in Xe-136 are analyzed to derive a total background rate of (0.84 +/- 0.02) mHz above 1000 keV. The comparison of data samples with and without the use of the radon abatement system demonstrates that the contribution of airborne-Rn is negligible. A radiogenic background model is built upon the extensive radiopurity screening campaign conducted by the NEXT collaboration. A spectral fit to this model yields the specific contributions of Co-60, K-40, Bi-214 and Tl-208 to the total background rate, as well as their location in the detector volumes. The results are used to evaluate the impact of the radiogenic backgrounds in the double beta decay analyses, after the application of topological cuts that reduce the total rate to (0.25 +/- 0.01) mHz. Based on the best-fit background model, the NEXT-White median sensitivity to the two-neutrino double beta decay is found to be 3.5 sigma after 1 year of data taking. The background measurement in a Q(beta beta)+/- 100 keV energy window validates the best-fit background model also for the neutrinoless double beta decay search with NEXT-100. Only one event is found, while the model expectation is (0.75 +/- 0.12) events.

[EN] Resilience is considered a challenging under-addressed issue that the high performance computing community (HPC) will have to face in order to produce reliable Exascale systems by the beginning of the next decade. As part of a push toward a resilient HPC ecosystem, in this paper we propose an error-resilient iterative solver for sparse linear systems based on stationary component-wise relaxation methods. Starting from a plain implementation of the Jacobi iteration, our approach introduces a low-cost component-wise technique that detects bit-flips, rejecting some component updates, and turning the initial synchronized solver into an asynchronous iteration. Our experimental study with sparse incomplete factorizations from a collection of real-world applications, and a practical GPU implementation, exposes the convergence delay incurred by the fault-tolerant implementation and its practical performance.

[EN] The primary advantage of moderately superheated bubble chamber detectors is their simultaneous sensitivity to nuclear recoils from weakly interacting massive particle (WIMP) dark matter and insensitivity to electron recoil backgrounds. A comprehensive analysis of PICO gamma calibration data demonstrates for the first time that electron recoils in C3F8 scale in accordance with a new nucleation mechanism, rather than one driven by a hot spike as previously supposed. Using this semiempirical model, bubble chamber nucleation thresholds may be tuned to be sensitive to lower energy nuclear recoils while maintaining excellent electron recoil rejection. The PICO-40L detector will exploit this model to achieve thermodynamic thresholds as low as 2.8 keV while being dominated by single-scatter events from coherent elastic neutrino-nucleus scattering of solar neutrinos. In one year of operation, PICO-401, can improve existing leading limits from PICO on spin-dependent WIMP-proton coupling by nearly an order of magnitude for WIMP masses greater than 3 GeV c(-2) and will have the ability to surpass all existing non-xenon bounds on spin-independent WIMP-nucleon coupling for WIMP masses from 3 to 40 GeV c(-2).

[EN] Final results are reported from operation of the PICO-60 C3F8 dark matter detector, a bubble chamber filled with 52 kg of C3F8 located in the SNOLAB underground laboratory. The chamber was operated at thermodynamic thresholds as low as 1.2 keV without loss of stability. A new blind 1404-kg-day exposure at 2.45 keV threshold was acquired with approximately the same expected total background rate as the previous 1167-kg-day exposure at 3.3 keV. This increased exposure is enabled in part by a new optical tracking analysis to better identify events near detector walls, permitting a larger fiducial volume. These results set the most stringent direct-detection constraint to date on the weakly interacting massive particle (WIMP)-proton spin-dependent cross section at 3.2 x 10(-41) cm(2) for a 25 GeV WIMP, improving on previous PICO results for 3-5 GeV WIMPs by an order of magnitude.

[EN] Astrophysical sources of gravitational waves, such as binary neutron star and black hole mergers or core-collapse supernovae, can drive relativistic outflows, giving rise to non-thermal high-energy emission. High-energy neutrinos are signatures of such outflows. The detection of gravitational waves and high-energy neutrinos from common sources could help establish the connection between the dynamics of the progenitor and the properties of the out¿ow. We searched for associated emission of gravitational waves and high-energy neutrinos from astrophysical transients with minimal assumptions using data from Advanced LIGO from its first observing run O1, and data from the ANTARES and IceCube neutrino observatories from the same time period. We focused on candidate events whose astrophysical origins could not be determined from a single messenger. We found no significant coincident candidate, which we used to constrain the rate density of astrophysical sources dependent on their gravitational-wave and neutrino emission processes.

[EN] The NEXT experiment aims at searching for the hypothetical neutrinoless double-beta decay from the 136Xe isotope using a high-purity xenon TPC. Efficient discrimination of the events through pattern recognition of the topology of primary ionisation tracks is a major requirement for the experiment. However, it is limited by the diffusion of electrons. It is known that the addition of a small fraction of a molecular gas to xenon reduces electron diffusion. On the other hand, the electroluminescence (EL) yield drops and the achievable energy resolution may be compromised. We have studied the effect of adding several molecular gases to xenon (CO2, CH4 and CF4) on the EL yield and energy resolution obtained in a small prototype of driftless gas proportional scintillation counter. We have compared our results on the scintillation characteristics (EL yield and energy resolution) with a microscopic simulation, obtaining the diffusion coefficients in those conditions as well. Accordingly, electron diffusion may be reduced from about 10 mm/ sqrt(¿) for pure xenon down to 2.5 mm/sqrt(m) using additive concentrations of about 0.05%, 0.2% and 0.02% for CO2, CH4 and CF4, respectively. Our results show that CF4 admixtures present the highest EL yield in those conditions, but very poor energy resolution as a result of huge fluctuations observed in the EL formation. CH4 presents the best energy resolution despite the EL yield being the lowest. The results obtained with xenon admixtures are extrapolated to the operational conditions of the NEXT-100 TPC. CO2 and CH4 show potential as molecular additives in a large xenon TPC. While CO2 has some operational constraints, making it difficult to be used in a large TPC, CH4 shows the best performance and stability as molecular additive to be used in the NEXT-100 TPC, with an extrapolated energy resolution of 0.4% at 2.45 MeV for concentrations below 0.4%, which is only slightly worse than the one obtained for pure xenon. We demonstrate

[EN] In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In this paper we present the first measurement of the efficiency of a cut based on the different event signatures of double and single electron tracks, using the data of the NEXT-White detector, the first detector of the NEXT experiment operating underground. Using a 228Th calibration source to produce signal-like and background-like events with energies near 1.6 MeV, a signal efficiency of 71.6 ± 1.5 stat ± 0.3 sys% for a background acceptance of 20.6 ± 0.4 stat ± 0.3 sys% is found, in good agreement with Monte Carlo simulations. An extrapolation to the energy region of the neutrinoless double beta decay by means of Monte Carlo simulations is also carried out, and the results obtained show an improvement in background rejection over those obtained at lower energies.

[EN] In this work, we address the efficient realization of block-Jacobi preconditioning on graphics processing units (GPUs). This task requires the solution of a collection of small and independent linear systems. To fully realize this implementation, we develop a variablesize batched matrix inversion kernel that uses Gauss-Jordan elimination (GJE) along with a variable-size batched matrix-vector multiplication kernel that transforms the linear systems' right-hand sides into the solution vectors. Our kernels make heavy use of the increased register count and the warp-local communication associated with newer GPU architectures. Moreover, in the matrix inversion, we employ an implicit pivoting strategy that migrates the workload (i.e., operations) to the place where the data resides instead of moving the data to the executing cores. We complement the matrix inversion with extraction and insertion strategies that allow the block-Jacobi preconditioner to be set up rapidly. The experiments on NVlDlA's K40 and P100 architectures reveal that our variable-size batched matrix inversion routine outperforms the CUDA basic linear algebra subroutine (cuBLAS) library functions that provide the same (or even less) functionality. We also show that the preconditioner setup and preconditioner application cost can be somewhat offset by the faster convergence of the iterative solver. (C) 2018 Elsevier B.V. All rights reserved.

This is the peer reviewed version of the following article: Anzt, H, Dongarra, J, Flegar, G, Higham, NJ, Quintana-Ortí, ES. Adaptive precision in block-Jacobi preconditioning for iterative sparse linear system solvers. Concurrency Computat Pract Exper. 2019; 31:e4460, which has been published in final form at https://doi.org/10.1002/cpe.4460. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving., [EN] We propose an adaptive scheme to reduce communication overhead caused by data movement by selectively storing the diagonal blocks of a block-Jacobi preconditioner in different precision formats (half, single, or double). This specialized preconditioner can then be combined with any Krylov subspace method for the solution of sparse linear systems to perform all arithmetic in double precision. We assess the effects of the adaptive precision preconditioner on the iteration count and data transfer cost of a preconditioned conjugate gradient solver. A preconditioned conjugate gradient method is, in general, a memory bandwidth-bound algorithm, and therefore its execution time and energy consumption are largely dominated by the costs of accessing the problem's data in memory. Given this observation, we propose a model that quantifies the time and energy savings of our approach based on the assumption that these two costs depend linearly on the bit length of a floating point number. Furthermore, we use a number of test problems from the SuiteSparse matrix collection to estimate the potential benefits of the adaptive block-Jacobi preconditioning scheme.

[EN] We present a collection of well-conditioned integral equation methods for the solution of electrostatic, acoustic, or electromagnetic scattering problems involving anisotropic, inhomogeneous media. In the electromagnetic case, our approach involves a minor modification of a classical formulation. In the electrostatic or acoustic setting, we introduce a new vector partial differential equation, from which the desired solution is easily obtained. It is the vector equation for which we derive a well-conditioned integral equation. In addition to providing a unified framework for these solvers, we illustrate their performance using iterative solution methods coupled with the FFT-based technique of [F. Vico, L. Greengard, M. Ferrando, J. Comput. Phys., 323 (2016), pp. 191-203] to discretize and apply the relevant integral operators.

[EN] Zeolites are porous, aluminosilicate materials with many industrial and "green" applications. Despite their industrial relevance, many aspects of zeolite synthesis remain poorly understood requiring costly trial and error synthesis. In this paper, we create natural language processing techniques and text markup parsing tools to automatically extract synthesis information and trends from zeolite journal articles. We further engineer a data set of germanium-containing zeolites to test the accuracy of the extracted data and to discover potential opportunities for zeolites containing germanium. We also create a regression model for a zeolite's framework density from the synthesis conditions. This model has a cross-validated root mean squared error of 0.98 T/1000 angstrom(3) , and many of the model decision boundaries correspond to known synthesis heuristics in germanium-containing zeolites. We propose that this automatic data extraction can be applied to many different problems in zeolite synthesis and enable novel zeolite morphologies.

[EN] CONSPECTUS: Zeolites are microporous crystalline materials with well-defined cavities and pores, which can be prepared under different pore topologies and chemical compositions. Their preparation is typically defined by multiple interconnected variables (e.g., reagent sources, molar ratios, aging treatments, reaction time and temperature, among others), but unfortunately their distinctive influence, particularly on the nucleation and crystallization processes, is still far from being understood. Thus, the discovery and/or optimization of specific zeolites is closely related to the exploration of the parametric space through trial-and-error methods, generally by studying the influence of each parameter individually. In the past decade, machine learning (ML) methods have rapidly evolved to address complex problems involving highly nonlinear or massively combinatorial processes that conventional approaches cannot solve. Considering the vast and interconnected multiparametric space in zeolite synthesis, coupled with our poor understanding of the mechanisms involved in their nucleation and crystallization, the use of ML is especially timely for improving zeolite synthesis. Indeed, the complex space of zeolite synthesis requires draWing inferences from incomplete and imperfect information, for which ML methods are very well-suited to replace the intuition-based approaches traditionally used to guide experimentation. In this Account, we contend that both existing and new ML approaches can provide the "missing link" needed to complete the traditional zeolite synthesis workflow used in our quest to rationalize zeolite synthesis. Within this context, we have made important efforts on developing ML tools in different critical areas, such as (1) data-mining tools to process the large amount of data generated using high-throughput platforms; (2) novel complex algorithms to predict the formation of energetically stable hypothetical zeolites and guide the synthesis of new zeo

[EN] Identification of active sites in heterogeneous metal catalysts is critical for understanding the reaction mechanism at the molecular level and for designing more efficient catalysts. Because of their structural flexibility, subnanometric metal catalysts, including single atoms and clusters with a few atoms, can exhibit dynamic structural evolution when interacting with substrate molecules, making it difficult to determine the catalytically active sites. In this work, Pt catalysts containing selected types of Pt entities (from single atoms to clusters and nanoparticles) have been prepared, and their evolution has been followed, while they were reacting in a variety of heterogeneous catalytic reactions, including selective hydrogenation reactions, CO oxidation, dehydrogenation of propane, and photocatalytic H-2 evolution reaction. By in situ X-ray absorption spectroscopy, in situ IR spectroscopy, and high-resolution electron microscopy techniques, we will show that some characterization techniques carried out in an inadequate way can introduce confusion on the interpretation of coordination environment of highly dispersed Pt species. Finally, the combination of catalytic reactivity and in situ characterization techniques shows that, depending on the catalyst-reactant interaction and metal-support interaction, singly dispersed metal atoms can rapidly evolve into metal clusters or nanoparticles, being the working active sites for those abovementioned heterogeneous reactions.

[EN] This paper describes the electronics of NEXT-White (NEW) detector PMT plane, a high pressure xenon TPC with electroluminescent amplification (HPXe-EL) currently operating at the Laboratorio Subterraneo de Canfranc (LSC) in Huesca, Spain. In NEXT-White the energy of the event is measured by a plane of photomultipliers (PMTs) located behind a transparent cathode. The PMTs are Hamamatsu R11410-10 chosen due to their low radioactivity. The electronics have been designed and implemented to fulfill strict requirements: an overall energy resolution below 1% and a radiopurity budget of 20 mBq unit(-1) in the chain of Bi-214. All the components and materials have been carefully screened to assure a low radioactivity level and at the same time meet the required front-end electronics specifications. In order to reduce low frequency noise effects and enhance detector safety a grounded cathode connection has been used for the PMTs. This implies an AC-coupled readout and baseline variations in the PMT signals. A detailed description of the electronics and a novel approach based on a digital baseline restoration to obtain a linear response and handle AC coupling effects is presented. The final PMT channel design has been characterized with linearity better than 0.4% and noise below 0.4mV.

[EN] We introduce a simulation framework for the transport of high and low energy electrons in xenon-based optical time projection chambers (OTPCs). The simulation relies on elementary cross sections (electron-atom and electron-molecule) and incorporates, in order to compute the gas scintillation, the reaction/quenching rates (atom-atom and atom-molecule) of the first 41 excited states of xenon and the relevant associated excimers, together with their radiative cascade. The results compare positively with observations made in pure xenon and its mixtures with CO2 and CF4 in a range of pressures from 0.1 to 10 bar. This work sheds some light on the elementary processes responsible for the primary and secondary xenon-scintillation mechanisms in the presence of additives, that are of interest to the OTPC technology.

[EN] Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors' approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.

[EN] Knock is a major bottleneck to achieving higher thermal efficiency in spark-ignited (SI) engines. The overall tendency to knock is highly dependent on fuel anti-knock quality as well as engine operating conditions. It is, therefore, critical to gain a better understanding of fuel-engine interactions in order to develop robust knock mitigation strategies. In the present work, a numerical model based on three-dimensional (3-D) computational fluid dynamics (CFD) was developed to capture knock in a Cooperative Fuel Research (CFR) engine. For combustion modeling, a hybrid approach incorporating the G-equation model to track turbulent flame propagation, and a homogeneous reactor multi-zone model to predict end-gas auto-ignition ahead of the flame front and post-flame oxidation in the burned zone, was employed. In addition, a novel methodology was implemented wherein a laminar flame speed lookup table generated a priori from a chemical kinetic mechanism could be used to provide flame speed as an input to the G-equation model, instead of using conventional empirical correlations. Multi-cycle Reynolds-Averaged Navier Stokes (RANS) simulations were performed for two different spark timings (STs) corresponding to non-knocking and knocking conditions, with other operating conditions kept the same as those of a standard Research Octane Number (RON) test. Iso-octane was considered as the fuel for the numerical study. Two different reduced kinetic mechanisms were employed to describe end-gas auto-ignition chemistry and to generate the flame speed lookup table. Experimental data, including intake/exhaust boundary conditions, was provided by a spark timing sweep study conducted in an in-house CFR engine. Moreover, cylinder wall/valve/port surface temperatures and residual gas fraction (RGF) were estimated using a well-calibrated one-dimensional (1-D) model. On the other hand, a novel methodology was also developed to analyze experimental data for the knocking case and identify

[EN] It is challenging to develop highly efficient and clean engines while meeting user expectations in terms of performance, comfort and drivability. One of the critical aspects in this regard is combustion noise control. Combustion noise accounts for about 40 percent of the overall engine noise in typical turbocharged diesel engines. The experimental investigation of noise generation is difficult due to its inherent complexity and measurement limitations. Therefore, it is important to develop efficient numerical strategies in order to gain a better understanding of the combustion noise mechanisms. In this work, a novel methodology was developed, combining computational fluid dynamics (CFD) modeling and genetic algorithm (GA) technique to optimize the combustion system hardware design of a high-speed direct injection (HSDI) diesel engine, with respect to various emissions and performance targets including combustion noise. The CFD model was specifically set up to reproduce the unsteady pressure field inside the combustion chamber, thereby allowing an accurate prediction of the acoustic response of the combustion phenomena. The model was validated by simulating several steady operating conditions and comparing the numerical results against experimental data, in both temporal and frequency domains. Thereafter, a GA optimization was performed with the goal of minimizing indicated specific fuel consumption (ISFC) and combustion noise, while restricting pollutant (soot and NOx) emissions to their respective baseline values. Eight design variables were selected pertaining to piston bowl geometry, nozzle inclusion angle, number of injector nozzle holes and in-cylinder swirl. An objective merit function based on the emissions, ISFC and combustion noise, was constructed to quantify the strength of the engine designs, and was determined using the CFD model as the function evaluator. The in-cylinder noise level was characterized by the total resonance energy of local pressure

[EN] The remarkable ability of Al-containing CHA zeolite to trap and stabilize noble single-metal atoms and metal clusters has facilitated the design of sinter-resistant materials for catalytic applications that require severe reaction conditions. At high temperatures in O-2, volatile MOx species appear to be fixated by the zeolite Al centers to prevent Ostwald-ripening sintering mechanisms, whereas small metal clusters (<100 atoms) are stabilized in H-2 without further aggregation as coalescence by Brownian motion is inhibited because of an encapsulation effect. Evidences of the possibility to trap the metal released from a second adjacent surface (e.g., SiO2 and Al2O3), upon metal migration over micrometer distances, are provided. These properties have opened the possibility to prepare several noble-metal atoms and clusters inside small-pore zeolites, including bimetallic formulation, by simple wetness impregnations or solid-to-solid transformations followed by standard calcination procedures, resulting in improved catalytic performances compared to other nonreducible supports in reactions that subject the catalysts to severe redox stress, such as the water-gas-shift reaction.

[EN] Directive-based programming models, such as OpenMP, OpenACC, and OmpSs, enable users to accelerate applications by using coprocessors with little effort. These devices offer significant computing power, but their use can introduce two problems: an increase in the total cost of ownership and their underutilization because not all codes match their architecture. Remote accelerator virtualization frameworks address those problems. In particular, rCUDA provides transparent access to any graphic processor unit installed in a cluster, reducing the number of accelerators and increasing their utilization ratio. Joining these two technologies, directive-based programming models and rCUDA, is thus highly appealing. In this work, we study the integration of OmpSs and OpenACC with rCUDA, describing and analyzing several applications over three different hardware configurations that include two InfiniBand interconnections and three NVIDIA accelerators. Our evaluation reveals favorable performance results, showing low overhead and similar scaling factors when using remote accelerators instead of local devices.

[EN] Conceived to host 5 kg of xenón at a pressure of 15 bar in the ¿ducial volume,the NEXTWhite (NEW)apparatus is currently the largest high pressure xenon gas TPC using electroluminescent ampli¿cation in the world. It is also a 1:2 scale model of the NEXT-100 detector scheduled to start searching for ßß0¿ decays in 136Xe in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2017 at the Canfranc Underground Laboratory (LSC), in Spain. This paper describes the detector and associated infrastructures.

[EN] Gaseous time projection chambers (TPC) are a very attractive detector technology for particle tracking. Characterization of both drift velocity and di¿usion is of great importance to correctly assess their tracking capabilities. NEXT-White is a High Pressure Xenon gas TPC with electroluminescent ampli¿cation, a 1:2 scale model of the future NEXT-100detector, which will be dedicated to neutrinoless double beta decay searches. NEXT-White has been operating at Canfranc Underground Laboratory (LSC) since December2016. The drift parameters have been measured using 83mKr for a range of reduced drift ¿elds at two di¿erent pressure regimes, namely 7.2 bar and 9.1 bar. Theresults have been compared with Magboltz simulations. Agreement at the 5% level or better has been found for drift velocity, longitudinal di¿usion and transverse di¿usion.