Flux Distribution Research Articles

Numerical analysis of full-scale multi-path shell-and-tube heat exchangers with corrugated tubes

Shell-and-tube heat exchangers (STHx) are extensively implemented in modern energy sectors due to their robustness and cost-effectiveness. Advancements in compact, high-performance STHx designs are critical for optimizing energy transfer and reducing overall energy consumption. The main drawback of STHx is their low compactness. This paper presents a detailed numerical study of retrofitted STHx with enhanced features aimed at improving the compactness and thermal efficiency. This study employs a high-resolution finite element method to model a series of multi-path STHx with plain and corrugated tube bundles. The study shows that even small-sized STHx models require a large number of grid points—10 million for plain tubes and 50 million for corrugated tubes. Retrofitting with PIC tubes increased heat transfer by 12 % to 28 %, albeit with higher pressure drops. Significant pressure losses were observed at the header and distributor, accounting for 35.8 % of total pressure loss in PIC configurations and 69.2 % in plain-tube cases. PIC tubes also promoted more uniform mass flux distribution and enhanced heat transfer via in-tube secondary flows, particularly at lower Reynolds numbers. These findings highlight the merit of high-resolution modeling in heat exchanger analysis and demonstrate the effectiveness of corrugated tubes in enhancing STHx performance.

Slow molecular beams from a cryogenic buffer gas source

We study the properties of a cryogenic buffer gas source that uses a low-temperature two-stage buffer gas cell to produce very slow beams of ytterbium monofluoride molecules. The molecules are produced by laser ablation inside the cell and extracted into a beam by a flow of cold helium. We measure the flux and velocity distribution of the beam as a function of ablation energy, helium flow rate, cell temperature, and the size of the gap between the first and second stages of the cell. We also compare the velocity distributions from one-stage and two-stage cells. The one-stage cell emits a beam with a speed of about 82ms−1 and a translational temperature of 0.63 K. The slowest beams are obtained using the two-stage cell at the lowest achievable cell temperature of 1.8 K. This beam has a peak velocity of 56ms−1 and a flux of 9×109 ground-state molecules per steradian per pulse, with a substantial fraction at speeds below 40ms−1. These slow molecules can be decelerated further by radiation pressure slowing and then captured in a magneto-optical trap. Published by the American Physical Society 2024

Discrete variance decay analysis of spurious mixing

This work examines the use of discrete variance decay of tracers to estimate locally in space and time the numerical mixing caused by different processes during a tracer transport step. Expressions for local discrete variance decay (DVD) rates are directly derived from discrete tracer equations without any assumptions on discrete fluxes of the second moment. They relate the DVD rates to the fluxes of the first moment through the faces of scalar control cell. Mixing associated with advective and diffusive fluxes is thus estimated. The new framework avoids the need for second-moment flux definition when solved directly on finite-volume cell faces but still invokes certain second-moment fluxes when the face DVD rates are partitioned to cells sharing the face. These implied discrete fluxes depend on the partitioning and are non-unique. For third- or higher-order advection schemes, the DVD rates are contaminated by dispersive errors intrinsic to the approach, introducing uncertainty to the locality of any estimates produced by it. Additional temporal averaging or coarse-graining is thus necessary. Through the application of this technique, Numerical mixing is found to be correlated with the distribution of eddy kinetic energy. Numerical mixing induced by vertical advection is found to be relatively small and correlated with the distribution of buoyancy fluxes. The explored high-order schemes are found to demonstrate levels of spurious mixing which may locally exceed physical mixing.

Functions of aldolase in lipid synthesis of Schizochytrium sp. by gene disruption to switch carbon metabolism

BackgroundAs a key rate-limiting enzyme in the glycolytic pathway of cells, aldolase affects the distribution of intracellular carbon flux and determines the overall ability of subsequent cell metabolism, which are mainly reported in the medical related researches, but rarely involved microorganisms. In this study, the aldolase gene of Schizochytrium limacinum SR21 (ALDOA) was knocked out to explore the effect of regulating carbon flux on cell growth and lipid synthesis.ResultsThe knockout of ALDOA showed an adverse effect on cell growth and total lipids production, which was decreased by 9.6% and 23.2%, respectively, but helped to improve the synthetic ability of polyunsaturated fatty acids (PUFAs), in which the proportion of docosahexaenoic acid (DHA) increased by 22.9%. Analysis of phospholipomics, real-time quantitative PCR and metabolomics revealed that the knockout of ALDOA weakened the glycolysis pathway and tricarboxylic acid cycle to inhibit cell growth, and lowered the Kennedy pathway to reduce the production of total lipids and the synthesis of phospholipids to affect cell metabolism. Correspondingly, the knockout of ALDOA enhanced the metabolic flux of the pentose phosphate pathway to provide more reducing power for PUFAs accumulation and improved the glycerophosphorylcholine acylation pathway to promote the accumulation of DHA.ConclusionsALDOA knockout redistributes the carbon metabolic flux in cells, by weakening the glycolysis, tricarboxylic acid cycle and glyceride synthesis pathway to inhibit cell growth and total lipid production, and strengthening the pentose phosphate pathway and glycerophosphorylcholine acylation pathway to increase the synthesis of PUFAs and DHA accumulation. This study provides a new idea for identifying the aldolase function in microorganisms and a metabolic strategy to improve DHA accumulation in Schizochytrium.

Influence of liquid–vapor phase change on the self-propelled motion of droplets on wettability gradient surfaces

Self-propelled motion of sessile droplets on gradient surfaces is key to the advancement of microfluidic, nanofluidic, and surface fluidic technologies. Precise control over droplet dynamics, which often involves liquid–vapor phase transitions, is crucial for a variety of applications, including thermal management, self-cleaning surfaces, biochemical assays, and microreactors. Understanding how specific phase changes like condensation and evaporation affect droplet motion is essential for enhancing droplet manipulation and improving transport efficiency. We use the thermal Navier–Stokes–Korteweg equations to investigate the effects of condensation and evaporation on the motion and internal dynamics of droplets migrating across a surface with a linear surface energy profile. The study focuses on the early dynamics of self-propelled motion of a phase changing droplet at sub-micron scale before viscous forces are comparable with the gradient forces. Our results demonstrate that phase change significantly affects the self-propelled motion of droplets by reshaping interfacial mass flux distributions and internal flow dynamics. Condensation increases droplet volume and promotes extensive spreading toward regions of higher wettability, while evaporation reduces both volume and spreading. These changes in droplet shape and size directly affect the driving forces of motion, augmenting self-propulsion through condensation and suppressing it during evaporation. Additionally, each phase change type generates distinct internal flow patterns within the droplet, with condensation and evaporation exhibiting unique circulatory movements driven by localized phase changes near the contact lines.

A numerical study of the effect of interfacial thermal resistance on thermal conductivity of Cu-B/diamond composites

Cu/diamond composite is a promising thermal management material for heat dissipation of high-power electronic devices. Heat transfer models for a Cu-B/diamond composite with varying boron contents added in the Cu matrix were constructed using the finite element (FE) method, based on the results from transmission electron microscopy (TEM) characterization. The heat transfer behavior of the Cu/diamond composites was then investigated. The predicted effective thermal conductivities were compared to experimental values, using both analytical model calculation and FE simulation. The FE simulation effectively illustrates the dependence of thermal conductivity on interface structure evolution of the composite. The heat transfer behavior of the Cu-B/diamond composites varies as the boron content increases. In the Cu-0.3wt%B/diamond composite, most of the heat flow is concentrated and transferred along the diamond particles. In the Cu-1.0wt%B/diamond composite, the heat flux distribution and flow direction are similar to those in the Cu-0.3wt%B/diamond composite, but the heat flux is substantially lower. The heat transfer behavior is closely related to the interactions between the two phases in the composite and is intensively influenced by the evolution of interfacial carbide morphology. The FE simulation provides a more accurate prediction of effective thermal conductivity compared to the analytical model calculation, as it considers the reasonable interactions between the two phases relating to the actual interfacial structure. The findings provide a fundamental basis for optimizing the interfacial structure of Cu/diamond composites and further improving their thermal conductivity.

Paradigm of engineering recalcitrant non-model microorganism with dominant metabolic pathway as a biorefinery chassis

The development and implementation of microbial chassis cells have profound impacts on circular economy. Non-model bacterium Zymomonas mobilis is an excellent chassis owing to its extraordinary industrial characteristics. Here, the genome-scale metabolic model iZM516 is improved and updated by integrating enzyme constraints to simulate the dynamics of flux distribution and guide pathway design. We show that the innate dominant ethanol pathway of Z. mobilis restricts the titer and rate of these biochemicals. A dominant-metabolism compromised intermediate-chassis (DMCI) strategy is then developed through introducing low toxicity but cofactor imbalanced 2,3-butanediol pathway, and a recombinant D-lactate producer is constructed to produce more than 140.92 g/L and 104.6 g/L D-lactate (yield > 0.97 g/g) from glucose and corncob residue hydrolysate, respectively. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) demonstrate the commercialization feasibility and greenhouse gas reduction capability of lignocellulosic D-lactate. This work thus establishes a paradigm for engineering recalcitrant microorganisms as biorefinery chassis.

Thermal challenges in heterogeneous packaging: Experimental and machine learning approaches to liquid cooling

In recent years, electronic packaging has evolved significantly to meet demands for higher performance, lower costs, and smaller designs. This shift has led to heterogeneous packaging, which integrates chips of varying stack heights and results in non-uniform heat flux and temperature distributions. These conditions pose substantial thermal management challenges, as they can create large temperature gradients, which increase thermal stress and potentially compromise chip reliability. This study explores single-phase liquid cooling for multi-chip modules (MCMs) through a comprehensive experimental and machine learning approach. It investigates the impact of chip spacing, height, fluid flow rate, fluid inlet location, and heat flux uniformity on chip temperature and the thermohydraulic performance of a commercial cold plate. Results show that increasing coolant flow from 1 LPM to 2 LPM decreased thermal resistance by 26 %, with heat losses remaining below 5 %. The left inlet configuration improved temperature uniformity compared to the right, though both yielded comparable thermal performance. Adjusting heater spacing impacted temperature distribution based on inlet position, and lowering one heater by 1 mm raised its temperatures by 15 °C due to increased thermal resistance from thermal interface material. A transient test demonstrated the cold plate’s quick response to power surges, in which there is only a 1 °C spike above steady state. Complementing these findings, an Artificial Neural Network (ANN) model was developed with optimized architecture specifically for the unique challenges of this study. The ANN model was rigorously validated using an independent dataset, achieving highly accurate temperature predictions (R2 = 0.99) within 2.5 % of experimental values, which demonstrates this framework’s potential for optimizing MCM thermal performance.

Highly crystalline nanorods pyrene-based covalent organic framework artificial solid electrolyte interface accelerated interface Li+ regulation on lithium anode

The detrimental effects of heterogeneous Li deposition and aeolotropic Li dendrite propagation critically hamper its serviceability of Li metal batteries. The exploitation of neutral multifunctional porous polymer artificial SEI is imperative to modulate interfacial ionic transfer behavior. Herein, we propose a strategy based on dual-functional nanorod-shaped covalent organic frameworks (COF) to accelerate Li+ diffusion and mitigate lithium dendrite growth by creating an artificial solid electrolyte interface (SEI) layer. As anticipated, the immobilized high-polarity –OH and −CN- groups, along with the porous channel facilitates, facilitate uniform Li+ flux distribution and rapid Li+ migration. Additionally, the highly conjugated nature of the pyrene moiety not only enhances the plane π-π stacking crystallinity of TFDH-COF, but contributes positively to Li+ and repelling TFSI−. The combination of comprehensive ex-situ/in-situ characterizations and DFT calculations have unraveled the underlying mechanisms on the reductive Li mitigation energy barrier and enhancive Li+ transfer ability. In contrast with bare Li, the resultant TFDH-COF@Li electrode demonstrates the elevated reversibility of Li+ utilization, slight polarization, dendrite-free interface and prolonged cyclic performance in Li|Cu, Li|Li, and Li-based full cells operated at rigorous current densities. Those unswerving evidences enlighten the feasibility of engineering the neutrality COF layer to get rid of adverse disordered Li proliferation.

Prediction and Optimization of Water Flux Distribution for Flat Nozzles in Slab Continuous Casting

Flat nozzles are widely used in the continuous casting process due to their stable spraying effect, wide spraying area, and strong applicability. The type and arrangement of nozzles have a direct effect on cooling efficiency and blank quality. Herein, the spray characteristics of flat nozzles in slab continuous casting are investigated with a detecting apparatus developed by University of Science and Technology Beijing and Jiangsu Boji Company (named USTB‐BOJI DA), and a prediction model for water flux distribution under different flat nozzle arrangements is established. The results show that the nozzles in a foot roller zone have good spray performance and water flow distribution, while the nozzles in bending zones are poor. Comparing the predicted and measured results of water flux distributions, the average error is less than 0.24%, indicating that the predictive model is reliable. In addition, the evaluation index is defined for water flux distribution under multinozzle arrangement, and the solution equations are given by applying the predictive model. Combining the above research, a new design and optimization strategy/method for flat nozzle arrangements is proposed, which can significantly improve the uniformity of the water flux distribution of the spray in the secondary cooling zones during continuous casting.

Efficient Production of 3'-Sialyllactose Using Escherichia coli.

3'-Sialyllactose (3'-SL), a key component of human milk oligosaccharides, provides significant health benefits and immune modulation, and is increasingly used in infant formula and dietary supplements. This study presents a novel approach for the efficient biosynthesis of 3'-SL using Escherichia coli BL21star(DE3)ΔlacZ through genomic integration. We first addressed the issue of metabolic competition by deleting crucial genes, nanA, nanK, nanE, and nanT, that are involved in the degradation of N-acetylneuraminic acid. This strategic gene knockout minimized the flux through competing pathways. The engineered Escherichia coli strain was subsequently transformed with the exogenous genes neuBCA and nST, enabling the de novo synthesis of 3'-SL. A modular metabolic engineering strategy was utilized to optimize the expression of key enzymes within the MSU module, enhancing and balancing the carbon flux distribution. Additionally, a cofactor regeneration strategy was implemented to increase CTP availability, which improved cofactor recycling and fine-tuned the metabolic pathway for maximal 3'-SL production. Transport protein screening was incorporated to further increase the extracellular concentration of 3'-SL, resulting in an unprecedented yield of 56.8 g/L in a 5L bioreactor fermentation, setting a new benchmark in the field.

Oxygen Vacancy Engineering of TiNb2O7 Modified PE Separator Toward Dendrite-Free Lithium Metal Battery.

Lithium metal battery with high specific energy and high safety is crucial for the next-generation energy storage technologies. However, the poor thermal stability, lower mechanical performance, and poor electrochemical performance of the commercially available polyethylene (PE) separator hinders the development of high-specific lithium metal batteries. Herein, a functional PE separator is prepared by innovative coating the TiNb2O7 microspheres with oxygen vacancies on the surface of PE (denoted as TNO-x-PE). The porosity, contact angle, electrolyte uptake rate, thermal shrinkage rate, mechanical properties, conductivity as well as lithium ions transference number of the TNO-x modified PE separator are all improved. The favorable TNO-x is beneficial for facilitating fast Li+ migration and impeding anions transfer, guiding the uniform distribution of lithium-ion flux. Consequently, the lithium symmetric cells with TNO-x-PE separator can be stably cycled more than 1600 h at 1 mA cm-2, and the initial capacity of the LFP/Li cells with TNO-x-PE separator is as high as 139.8 mAh g-1, and after 500 cycles, the capacity retention rate is still 99.5%. This work may provide a new idea to construct a multi-functional separator with high safety and superior electrochemical performance and promote the development of LMBs.

Robust Sodium Storage Enabled by Heterogeneous Engineering and Electrolyte Modification

AbstractThe modulation of heterointerfaces in 2D materials is critically important for improving the electrochemical performance of sodium‐ion batteries (SIBs). In this context, the MoS2/Ti3C2Tx MXene heterostructure is taken as a typical example to reveal the fundamental principle of high sodium storage performance by regulating the terminal groups of Ti3C2Tx. It is demonstrated that MoS2/Ti3C2(OH)x (M/‐(OH)x) heterostructure with a high work function difference generates an enhanced built‐in electric field, which facilitates charge transfer. Moreover, ether‐based electrolytes, when compared to ester‐based electrolytes, provide lower solvation‐free energies and exhibit high compatibility with M/‐(OH)x, resulting in superior rate capability. Notably, COMSOL simulations of sodium ion (Na+) concentration and Na+ flux distributions reveal that the M/‐(OH)x electrode has low concentration polarization and rapid diffusion kinetics in ether‐based electrolytes. Consequently, the combination of M/‐(OH)x heterostructure with the ether‐based electrolyte provides 224.06 mAh g−1 after 1000 cycles at 5.0 A g−1. Furthermore, the Na3V2(PO4)3/C//M/‐(OH)x full cell demonstrates robust electrochemical performance, delivering 116.49 mAh g−1 after 140 cycles at 1.0 A g−1. These findings emphasize the impact of modulating terminal functional groups to optimize the electrochemical functionality of heterostructures and highlight the crucial role of electrode/electrolyte synergistic coupling in advancing the practical applications of SIBs.

NSTTF Heliocon Wireless Closed-Loop Controls Test Bed Development

A closed loop controls test bed is in development at the Sandia National Laboratories (SNL), National Solar Thermal Test Facility (NSTTF) as part of the U.S. DOE SETO sponsored Heliostat Consortium (HelioCON) program. This work pertains to preliminary development of advanced feedback controls for a concentrating solar power (CSP) field of 218 heliostats, and the development of a baseline closed-loop controls extremum seeking control (ESC) algorithm. This algorithm utilizes a batch least squares (BLS) technique to facilitate feedback control automation for heliostat pointing. This allows the determination of the optimal highest flux within a Gaussian profile, for both a four-point (QuadCell) aim point strategy, and a concentric aim point strategy. The results of this work determined that both approaches using the ESC BLS were able to reduce pointing errors to zero for both azimuth and elevation heliostat position movements. This work also reviews progress of the test bed which will allow flexible employment of controls and sensors which will be communicating with both wired and wireless protocols. The solar field distributed control system (DCS) will manage the flux distribution of energy across test articles and solar receivers using real-time programmable logic controllers (PLC) at each heliostat, for aiming and closed-loop feedback. Feedback control will be facilitated with a variety of sensors, located: 1. On the heliostat, 2. On the tower or 3. At an ancillary field tower station. The system is also developed to incorporate environmental information to provide real-time feedback into advanced algorithms for solar field management.

Dependence of divertor turbulence on plasma density and current in TCV

Abstract To reliably predict the distribution of heat and particle fluxes at the target plates of tokamaks, a comprehensive understanding of turbulence throughout the entire Scrape-Off-Layer (SOL) is imperative. This study examines divertor turbulence systematically across a broad parameter range on the TCV tokamak, including variations in magnetic field direction, plasma current I p ∈ [ 140 , 320 ] kA, edge safety factor q 95 ∈ [ 2.6 , 4.7 ] and Greenwald fraction f G ∈ [ 0.18 , 0.6 ] . The TCV X-point Gas Puff Imaging (GPI) system is used to measure 2D filament properties in the inner and outer divertor region. The fluctuation levels in the divertor are found to strongly increase with density (to 80% over most of the SOL) while remaining insensitive to I p . The previously identified divertor-localized filaments (DLF), located on the bad curvature side of the outer divertor leg, are found to be a common feature on TCV, while no filaments are observed in the PFR. DLFs are present over most of the parameter space and in both field directions. However, they are absent, or appear only closer to the target, for sufficiently large Λ div ≳ 10 or q 95 ≳ 3.7 . Across both I p and f G scans, some clear trends with Λ div are found for divertor filament sizes and velocities, and with target fall-off lengths of density and heat flux profiles at the outer target. This study provides important experimental insights to turbulent transport in the divertor also for comparison with self-consistent, turbulence simulations and extrapolation to future reactor conditions.

Local-scale variability in packed beds of polyhedral particles: Structural and thermal distribution

Heat transfer in packed beds largely depends on the bed structure, which is strongly linked to particle shape, yet most prior work focuses on spherical particles. This work contributes towards a better understanding of particle shape effect on the local-scale and its variability. Particle beds are generated numerically and steady-state thermal simulations are conducted for 12 different particle shapes and three particle-to-gas conductivity ratios. Voronoi cells are extracted to obtain local cell porosities; distributions are studied statistically. Another crucial parameter, particle-particle contact areas, are evaluated and compared with shapes. Variability in local structure results in varied temperature profiles. Thermal fluctuations are substantially affected by irregular shapes, an effect that increases for highly conductive particles. Notably, the spatial distribution of phases with different conductance has a strong influence on the distribution of local heat flux. Predominantly, these outcomes also indicate the relevancy of including shape parameters in developing reactors or modeling other granular applications.

A Comprehensive Microstructure-Aware Electromigration Modeling Framework; Investigation of the Impact of Trench Dimensions in Damascene Copper Interconnects.

As electronic devices continue to shrink in size and increase in complexity, the current densities in interconnects drastically increase, intensifying the effects of electromigration (EM). This renders the understanding of EM crucial, due to its significant implications for device reliability and longevity. This paper presents a comprehensive simulation framework for the investigation of EM in nano-interconnects, with a primary focus on unravelling the influential role of microstructure, by considering the impact of diffusion heterogeneity through the metal texture and interfaces. As such, the resulting atomic flux and stress distribution within nano-interconnects could be investigated. To this end, a novel approach to generate microstructures of the conductor metal is presented, whereby a predefined statistical distribution of grain sizes obtained from experimental texture analyses can be incorporated into the presented model, making the model predictive under various scales and working conditions with no need for continuous calibration. Additionally, the study advances beyond the state-of-the-art by comprehensively simulating all stages of electromigration including stress evolution, void nucleation, and void dynamics. The model was employed to study the impact of trench dimensions on the dual damascene copper texture and its impact on electromigration aging, where the model findings were corroborated by comparing them to the available experimental findings. A nearly linear increase in normalized time to nucleation was detected as the interconnect became wider with a fixed height for aspect ratios beyond 1. However, a saturation was detected with a further increase in width for lines of aspect ratios below 1, with no effective enhancement in time to nucleation. An aspect ratio of 1 seems to maximize the EM lifetime for a fixed cross-sectional area by fostering a bamboo-like structure, where about a 2-fold of increase was estimated when going from aspect ratio 2 to 1.

Design of Small Permanent-Magnet Linear Motors and Drivers for Automation Applications with S-Curve Motion Trajectory Control and Solutions for End Effects and Cogging Force

This paper designs and fabricates a small-type permanent-magnet linear motor and driver for automation applications. It covers structural design, magnetic circuit analysis, control strategies, and hardware development. Magnetic circuit analysis software JMAG is used for flux density distribution, back electromotive force (back-EMF), and electromagnetic force analysis. To address the lack of a complete closed magnetic circuit path at the ends of the linear motor, which causes magnetic field asymmetry, a phenomenon known as end effects, auxiliary core structures are proposed to compensate for the magnetic field at the ends. It successfully utilizes auxiliary cores to achieve the phase voltages of each phase, which are balanced at a phase voltage error of 0.02 V. To address the cogging force caused by variations in the magnetic reluctance of the core, this paper analyzes the relationship between electromagnetic force and mover position, conducting harmonic content analysis to obtain parameters. These parameters are applied to the designed cogging force control compensation strategy. It successfully achieves q-axis current compensation of around 1.05 A based on the mover’s position, ensuring that no jerking caused by cogging force occurs during closed-loop electromagnetic force control. The S-curve motion trajectory control is proposed to replace the traditional trapezoidal acceleration and deceleration, resulting in smoother position control of the linear motor. Simulations using JMAG-RT models in MATLAB/Simulink verified these control strategies. After verification, practical test results showed a maximum position error of approximately 5.0 μm. Practical tests show that the designed small-type permanent-magnet linear motor and its driver provide efficient, stable, and high-precision solutions for automation applications.

PICZL : Image-based photometric redshifts for AGN

Computing reliable photometric redshifts (photo-z) for active galactic nuclei (AGN) is a challenging task, primarily due to the complex interplay between the unresolved relative emissions associated with the supermassive black hole and its host galaxy. Spectral energy distribution (SED) fitting methods, while effective for galaxies and AGN in pencil-beam surveys, face limitations in wide or all-sky surveys with fewer bands available, lacking the ability to accurately capture the AGN contribution to the SED, hindering reliable redshift estimation. This limitation is affecting the many tens of millions of AGN detected in existing datasets, such as those AGN clearly singled out and identified by SRG/eROSITA. Our goal is to enhance photometric redshift performance for AGN in all-sky surveys while simultaneously simplifying the approach by avoiding the need to merge multiple data sets. Instead, we employ readily available data products from the 10th Data Release of the Imaging Legacy Survey for the Dark Energy Spectroscopic Instrument, which covers > 20,000 deg of extragalactic sky with deep imaging and catalog-based photometry in the grizW1-W4 bands. We fully utilize the spatial flux distribution in the vicinity of each source to produce reliable photo-z. We introduce PICZL a machine-learning algorithm leveraging an ensemble of convolutional neural networks. Utilizing a cross-channel approach, the algorithm integrates distinct SED features from images with those obtained from catalog-level data. Full probability distributions are achieved via the integration of Gaussian mixture models. On a validation sample of 8098 AGN PICZL achieves an accuracy $ NMAD $ of 4.5<!PCT!> with an outlier fraction eta of 5.6<!PCT!>. These results significantly outperform previous attempts to compute accurate photo-z for AGN using machine learning. We highlight that the model's performance depends on many variables, predominantly the depth of the data and associated photometric error. A thorough evaluation of these dependencies is presented in the paper. Our streamlined methodology maintains consistent performance across the entire survey area, when accounting for differing data quality. The same approach can be adopted for future deep photometric surveys such as LSST and Euclid, showcasing its potential for wide-scale realization. With this paper, we release updated photo-z (including errors) for the XMM-SERVS W-CDF-S, ELAIS-S1 and LSS fields.

Application of the Krylov-Schur method in three-dimensional nuclear reactor discrete ordinates criticality calculations

The accurate and efficient solution of the neutron transport equation is essential in nuclear reactor physics for understanding reactor kinetics, stability, and safety. This study investigates the application of the Krylov-Schur method to three-dimensional neutron transport criticality calculations within the Marvin code, comparing its performance to the traditional Power Iteration (PI) method. Using the Takeda benchmark problems, the Krylov-Schur solver demonstrated high accuracy in eigenvalue calculations and neutron flux distributions, closely matching reference Monte Carlo (MC) results. Additionally, the parallel efficiency of the Krylov-Schur method was evaluated, showing significant speed-up and better scalability compared to the PI method, particularly in large-scale computations. However, the method requires a larger memory footprint due to the need to store multiple Krylov subspace vectors and Schur decompositions. Despite this, the findings highlight the Krylov-Schur method's robustness and computational efficiency, making it a promising tool for neutron transport simulations in complex reactor configurations. Future work will focus on investigating the subtraction of high-order eigenvalues and eigenvectors using the Krylov-Schur method to further enhance neutron transport simulations.