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At least 235 records · Page 13

Compatibility Of Steels At 450°-650°C In Supercritical CO2 With O2 And H2O Additions

Direct-fired supercritical CO2 (sCO2) power cycles are being commercialized to revolutionize fossil energy as a low-emission power source. However, the cycle will increase O2 and H2O in the sCO2 and the implications of these additions have not been fully studied, particularly for lower cost steels that are needed in the lower temperature segments of the plant. Representative 9 and 12%Cr ferritic-martensitic (FM) steels and conventional and advanced austenitic steels were evaluated at 450-650°C to determine the maximum use temperatures in sCO2 with 1%O2 and 0.1%H2O at 300 bar. Compared to research grade (low impurity) sCO2 in indirect-fired cycles, the mass gains and scale thickness were not significantly changed for FM steels: both formed thick duplex Fe-rich scales. For stainless steels, higher mass gains were observed in all cases with increased Fe-rich oxide nodule formation. After 1000h at 650°C, the measured bulk C content was high for all of the steels with the addition of impurities suggesting a lower maximum operating temperature for steels. The post-exposure impact of the environment on room temperature tensile properties also will be discussed.

Pint, Bruce↗

Calibration and Performance of Germanium High Voltage Detectors for SuperCDMS SNOLAB

As SuperCDMS SNOLAB is getting ready to search for low mass dark matter particles, using cryogenic Ge and Si detectors, a set of six of the new SuperCDMS High Voltage (HV) detectors (four Ge and two Si) were tested in the Cryogenic Underground TEst facility (CUTE) at SNOLAB. This provided the first opportunity to gain experience with this new detector type and assess their performance thoroughly under low background conditions. Here we describe the SuperCDMS HV detector concept and discuss some of the newly developed analysis methods and approaches. Focusing on the Ge detectors, we investigate the detector performance under voltage bias (up to 90 V), exercise the low energy (keV to sub-keV range) calibration based on the electron capture peaks generated by the decay of $^{71}$Ge, assess the detector resolution, and demonstrate the unexpected (and encouraging) ability of these detectors to also measure high energy interactions in the hundreds of keV range with good resolution (better than 3% at 356 keV).

Albakry, M. F. [British Columbia U.; TRIUMF]↗

Life cycle assessment of a novel gas switching reforming for sustainable hydrogen production with CO2 capture

Gas switching reforming for hydrogen production (GSR-H2) presents an efficient, low-carbon hydrogen production method that incorporates integrated carbon capture, offering efficiency gains over traditional methods such as proton exchange membrane (PEM) electrolysis, steam methane reforming (SMR) and the newer method of chemical looping reforming (CLR). GSR-H2 has been demonstrated in lab scale which operates as an exothermic process that eliminates the need for additional natural gas combustion, using its own waste heat to generate process steam and partially offset energy usage through electricity production. Beyond its thermal self-sufficiency, GSR-H2 advances upon CLR by integrating all reaction stages within a single reactor cluster, eliminating the complexities of solid circulation, reducing capital costs, and enhancing overall process efficiency. This streamlined design simplifies scale-up and enables inherent CO2 separation with minimal energy penalty, making GSR-H2 a highly competitive pathway for low-carbon hydrogen production. This study presents the first life cycle assessment (LCA) of GSR-H2, offering a novel evaluation of this new process’s environmental impacts across diverse energy scenarios. Key findings reveal that in the renewables-powered scenario, GSR-H2 achieves a GWP of 2.77 kg CO2 eq per kg H2, a substantial improvement over SMR’s 10.4 kg CO2 eq and close to the low emissions of CLR (1.84 kg CO2 eq) and PEM electrolysis (1.85 kg CO2 eq). These results demonstrate GSR-H2’s competitive advantage as a lower-emission alternative, combining design simplicity and efficiency gains, especially in renewable-integrated systems. These results establish GSR-H2 as a competitive, scalable option for hydrogen production, particularly in decarbonization efforts.

03 NATURAL GAS↗

Local spin structure in the layered van der Waals materials MnPS 𝑥 ⁢Se 3−𝑥

Two-dimensional (2D) layered materials, whether in bulk form or reduced to just a single layer, have potential applications in spintronics and capacity for advanced quantum phenomena. A prerequisite for harnessing these opportunities lies in gaining a comprehensive understanding of the spin behavior in 2D materials. The low dimensionality motivates an understanding of the spin correlations over a wide length scale, from local to long-range order. In this context, we focus on the magnetism in bulk MnPSe 3 and MnPS 3 , 2D layered van der Waals antiferromagnetic semiconductors. These materials have similar honeycomb Mn layers and magnetic ordering temperatures, but distinct spin orientations and exchange interactions. Here, we utilize neutron scattering to gain deeper insights into the local magnetic structures and spin correlations in the paramagnetic and ordered phases by systematically investigating a MnPS 𝑥 ⁢Se 3−𝑥 (𝑥 = 0, 1, 1.5, 2, 3) series of powder samples using total neutron scattering measurements. By employing magnetic pair distribution function analysis, we unraveled the short-range magnetic correlations in these materials and explored how the nonmagnetic anion S/Se mixing impacts the magnetic correlations. The results reveal that the magnetism can be gradually tuned through alteration of the nonmagnetic S/Se content, which tunes the atomic structure. The change in magnetic structure is also accompanied by a control of the magnetic correlation length within the 2D honeycomb layers. Complimentary inelastic neutron scattering measurements allowed a quantification of the change in the magnetic exchange interactions for the series and further highlighted the gradual evolution of spin interactions in the series MnPS 𝑥 ⁢Se 3−𝑥 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine learning for postprocessing ensemble streamflow forecasts

Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles, distributed hydrological model, and machine learning to generate ensemble streamflow forecasts at medium-range lead times (1–7 days). We demonstrate the application of machine learning as postprocessor for improving the quality of ensemble streamflow forecasts. Our results show that the machine learning postprocessor can improve streamflow forecasts relative to low-complexity forecasts (e.g., climatological and temporal persistence) as well as standalone hydrometeorological modeling and neural network. The relative gain in forecast skill from postprocessor is generally higher at medium-range timescales compared to shorter lead times; high flows compared to low–moderate flows, and the warm season compared to the cool ones. Overall, our results highlight the benefits of machine learning in many aspects for improving both the skill and reliability of streamflow forecasts.

54 ENVIRONMENTAL SCIENCES↗

Mixed gain detector configurations for time-resolved X-ray solution scattering

X-ray detection at X-ray free-electron lasers is challenging in part due to the XFEL's extremely short and intense X-ray pulses. Experimental measurements are further complicated by the large fluctuations inherent to the self-amplified spontaneous emission process producing the X-rays. At the Linac Coherent Light Source the ePix10ka2M detector offers multiple gain modes, and auto-ranging between these, to increase the dynamic range while retaining low noise. For diffuse scattering techniques, such as time-resolved X-ray solution scattering, where the shape of the scattering pattern largely does not change between exposures, a fixed mix of different gain modes offers many of the same advantages as auto-ranging. We find that configuring individual ASICs in separate gain modes does not impact the intensity linearity of the gain response and has a limited effect on the effective dynamic range in regions with different gain mode settings while avoiding the complexities of auto-ranging. Small (<5%) non-linear gain contributions arise when pixels on the same ASIC are configured in different gain modes. We present a configuration scheme that is designed to select the optimal mixed gain configuration to minimize effects of saturation in the high-/medium-gain region, while maximizing the number of pixels with higher gain to improve the signal-to-noise ratio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Cyanobacterial photosystem II reaction center design in tobacco chloroplasts increases biomass in low light

Abstract The D1 polypeptide of the photosystem II (PSII) reaction center complex contains domains that regulate primary photochemical yield and charge recombination rate. Many prokaryotic oxygenic phototrophs express two or more D1 isoforms differentially in response to environmental light needs, a capability absent in flowering plants and algae. We report that tobacco (Nicotiana tabacum) plants carrying the Synechococcus (Synechococcus elongatus PCC 7942) low-light mutation (LL-E130Q) in the D1 polypeptide (NtLL) acquire the cyanobacterial photochemical phenotype: faster photodamage in high light and significantly more charge separations in productive linear electron flow in low light. This flux increase produces 16.5% more (dry) biomass under continuous low-light illumination (100 μE m−2 s−1, 24 h). This gain is offset by the predicted lower photoprotection at high light. By contrast, the introduction of the Synechococcus high-light mutation (HL-A152S) into tobacco D1 (NtHL) has slightly increased photoprotection, achieved by photochemical quenching, but no apparent impact on biomass yield compared to wild type under the tested conditions. The universal design principle of all PSII reaction centers trades off energy conversion for photoprotection in different proportions across all phototrophs and provides a useful guidance for testing in crop plants. The observed biomass advantage under continuous low light can be transferred between evolutionarily isolated lineages to benefit growth under artificial lighting conditions. However, removal of the selective marker gene was essential to observe the growth phenotype, indicating growth penalty imposed by use of the particular spectinomycin-resistance gene.

Zhang, Yuan (ORCID:0000000291785207)↗

BeyondPlanck: VII. Bayesian estimation of gain and absolute calibration for cosmic microwave background experiments

We present a Bayesian calibration algorithm for cosmic microwave background (CMB) observations as implemented within the global end-to-end BEYONDPLANCK framework and applied to the Planck Low Frequency Instrument (LFI) data. Following the most recent Planck analysis, we decomposed the full time-dependent gain into a sum of three nearly orthogonal components: one absolute calibration term, common to all detectors, one time-independent term that can vary between detectors, and one time-dependent component that was allowed to vary between one-hour pointing periods. Each term was then sampled conditionally on all other parameters in the global signal model through Gibbs sampling. The absolute calibration is sampled using only the orbital dipole as a reference source, while the two relative gain components were sampled using the full sky signal, including the orbital and Solar CMB dipoles, CMB fluctuations, and foreground contributions. We discuss various aspects of the data that influence gain estimation, including the dipole-polarization quadrupole degeneracy and processing masks. Comparing our solution to previous pipelines, we find good agreement in general, with relative deviations of -0.67% (-0.84%) for 30 GHz, 0.12% (-0.04%) for 44 GHz and -0.03% (-0.64%) for 70 GHz, compared to Planck PR4 and Planck 2018, respectively. We note that the BEYONDPLANCK calibration was performed globally, which results in better inter-frequency consistency than previous estimates. Additionally, WMAP observations were used actively in the BEYONDPLANCK analysis, which both breaks internal degeneracies in the Planck data set and results in an overall better agreement with WMAP. Finally, we used a Wiener filtering approach to smoothing the gain estimates. We show that this method avoids artifacts in the correlated noise maps as a result of oversmoothing the gain solution, which is difficult to avoid with methods like boxcar smoothing, as Wiener filtering by construction maintains a balance between data fidelity and prior knowledge. Although our presentation and algorithm are currently oriented toward LFI processing, the general procedure is fully generalizable to other experiments, as long as the Solar dipole signal is available to be used for calibration.

79 ASTRONOMY AND ASTROPHYSICS↗

Bifacial PV Module Energy Modeling Validation Study

The cost delta between monofacial and bifacial photovoltaic (PV) modules was decreasing in 2018 when this study was initially proposed, making bifacial modules an attractive offering. However, there were limited field studies available that could be considered utility-scale representative, and PV module manufacturers were stating large ranges for the expected energy yield improvements of bifacial technology. This generated uncertainties regarding bifacial performance gains and the actual LCOE (levelized cost of energy). There was also relatively low confidence in the industry’s energy modeling tools’ ability to accurately predict bifacial energy yield, meaning that early adopters of bifacial modules were not able to fully account for the increased energy yield in their energy and financial models. The intent of this project was to provide the solar industry with greater certainty on the energy yield gains of bifacial modules and provide higher confidence in the ability for different energy modeling software to model bifacial PV site performance. Achieving this would allow for bifacial technology to become bankable (i.e. accepted by Independent Engineers, site financiers and other PV site stakeholders), offering a step change in PV site performance that had not been seen since the widespread adoption of the single-axis tracker. Over the course of this study other economic factors including a significant tariff exemption for bifacial modules resulted in accelerated adoption of bifacial technology throughout the US utility scale solar segment. The number of early adopters increased rapidly, and with many investors accepting this module choice the question of bifacial bankability was seemingly answered faster than expected. However, PVEL’s study has still achieved significant accomplishments in demonstrating the accuracy of bifacial modeling across three different software platforms. The results of this study have shown that the mean biased error (MBE) between the field data and the predicted values from all three software platforms were aligned with a maximum MBE of 1.3% and a minimum MBE of -1.8%.

14 SOLAR ENERGY↗

3D xRAGE simulation of inertial confinement fusion implosion with imposed mode 2 laser drive asymmetry

Low-mode asymmetries represent an important obstacle to achieving high-gain inertial confinement fusion implosions. As a step in learning how to control such effects, an OMEGA experiment with imposed mode 2 laser drive asymmetries was done to study the expected signatures of this type of asymmetry [M. Gatu Johnson et al., PRE 2018]. In the present work, a 3D xRAGE simulation including the stalk mount has been brought to bear on the data from that experiment. Furthermore, comprehensive comparisons between simulated and measured observables are made. Good agreement between simulated and measured x-ray image-inferred shell trajectories, bang times and neutron emission widths are seen, showing that the hydrodynamics are well captured in the simulation. Asymmetries seen in simulated and measured time-resolved and time-integrated x-ray images and areal densities also compare well, showing impact of both stalk and mode 2. On the other hand, important differences in measured and simulated neutron emission histories, yield, and ion temperature (T ion ) asymmetries are seen, suggesting that the simulation is overestimating shock yield. Overall, the results clearly demonstrate the importance of considering all asymmetry sources when interpreting measured signatures of asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of a CFD-improved dimple stepped-lip piston on thermal efficiency and emissions in a medium-duty diesel engine

Diesel piston-bowl shape is a key design parameter that affects spray-wall interactions and turbulent flow development, and in turn affects the engine’s thermal efficiency and emissions. It is hypothesized that thermal efficiency can be improved by enhancing squish-region vortices as they are hypothesized to promote fuel-air mixing, leading to faster heat-release rates. However, the strength and longevity of these vortices decrease with advanced injection timings for typical stepped-lip (SL) piston geometries. Dimple stepped-lip (DSL) pistons enhance vortex formation at early injection timings. Previous engine experiments with such a bowl show 1.4% thermal efficiency gains over an SL piston. However, soot was increased dramatically [SAE 2022-01-0400]. In a previous study, a new DSL bowl was designed using non-combusting computational fluid dynamic simulations. This improved DSL bowl is predicted to promote stronger, more rotationally energetic vortices than the baseline DSL piston: it employs shallower, narrower, and steeper-curved dimples that are placed further out into the squish region. In the current experimental study, this improved bowl is tested in a medium-duty diesel engine and compared against the SL piston over an injection timing sweep at low-load and part-load operating conditions. No substantial thermal efficiency gains are achieved at the early injection timing with the improved DSL design, but soot emissions are lowered by 45% relative to the production SL piston, likely due to improved air utilization and soot oxidation. However, these benefits are lost at late injection timings, where the DSL piston renders a lower thermal efficiency than that of the SL piston. Energy balance analyses show higher wall heat transfer with the DSL piston than with the SL piston despite a 1.3% reduction in the piston surface area. Vortex enhancement may not necessarily lead to improved efficiency as more energetic squish-region vortices can lead to higher convective heat transfer losses.

42 ENGINEERING↗

Quantum Efficiency Gain in 2D Perovskite Photo and X‐Ray Detectors

Abstract The perovskite polycrystalline thin film detector fabricated by solution method is a promising low‐cost, scalable technology for radiation imaging, but its thin volume limits the sensing efficiency for high‐energy X‐ray photons. This work reports 2D perovskite thin film photo‐diodes with a detection gain when sensing visible and X‐ray photons. Detailed power and temperature‐dependent device characterizations reveal a charge multiplication effect to be responsible for the observed high gain. This is caused by a disparity in electron and hole transport, where electron transport is retarded by a trap/de‐trap process via shallow trap states, whereas the hole transport is fast enough to produce a photoconductive gain in satisfying the charge neutrality. The 2D perovskite made with butylamine spacers is also found to exhibit a larger efficiency gain than those made with phenylethylamines because of the higher likelihood of forming shallow traps in the former. The thin film diodes feature a high temporal response over 1 MHz due to the fast charge collection across a thin volume, and the discovery provides device physics mechanisms in connection to material structure‐function relationship for future optoelectronics design that can boost the efficiency of X‐ray sensing and dim light detection.

2D perovskites↗

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗

Combining fast magic angle spinning dynamic nuclear polarization with indirect detection to further enhance the sensitivity of solid-state NMR spectroscopy

Dynamic nuclear polarization (DNP) and indirect detection are two commonly applied approaches for enhancing the sensitivity of solid-state NMR spectroscopy. However, their use in tandem has not yet been investigated. With the advent of low-temperature fast magic angle spinning (MAS) probes with 1.3-mm diameter rotors capable of MAS at 40 kHz it becomes feasible to combine these two techniques. In this study, we performed DNP-enhanced 2D indirectly detected heteronuclear correlation (idHETCOR) experiments on 13 C, 15 N, 113 Cd and 89 Y nuclei in functionalized mesoporous silica, CdS nanoparticles, and Y 2 O 3 nanoparticles. The sensitivity of the 2D idHETCOR experiments was compared with those of DNP-enhanced directly-detected 1D cross polarization (CP) and 2D HETCOR experiments performed with a standard 3.2-mm rotor. Due to low CP polarization transfer efficiencies and large proton linewidth, the sensitivity gains achieved by indirect detection alone were lower than in conventional (non-DNP) experiments. Nevertheless, despite the smaller sample volume the 2D idHETCOR experiments showed better absolute sensitivities than 2D HETCOR experiments for nuclei with the lowest gyromagnetic ratios. Finally, for 89 Y, 2D idHETCOR provided 8.2 times better sensitivity than the 1 D 89 Y-detected CP experiment performed with a 3.2-mm rotor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emerging Electrochemical Techniques for Probing Site Behavior in Single-Atom Electrocatalysts

Single-atom catalysts (SACs) have aroused tremendous interest over the past decade, particularly in the community of energy and environment-related electrocatalysis. A rapidly growing number of recent publications have recognized it as a promising candidate with maximum atomic utilization, distinct activity, and selectivity in comparison to bulk catalysts and nanocatalysts. However, the complexity of localized coordination environments and the dispersion of isolated sites lead to significant difficulties when it comes to gaining insight into the intrinsic behavior of electrocatalytic reactions. Furthermore, the low metal loadings of most SACs make conventional ensemble measurements less likely to be accurate on the subnanoscale. Thus, it remains challenging to probe the activity and properties of individual atomic sites by available commercial instruments and analytical methods. In spite of this, continuing efforts have lately focused on the development of advanced measurement methodologies, which are very useful to the fundamental understanding of SACs. There have recently been a number of in situ/operando techniques applied to SACs, such as electron microscopy, spectroscopy, and other analysis methods, which support relevant functions to identify the active sites and reaction intermediates and to investigate the dynamic behavior of localized structures of the catalytic sites. This Account aims to present recent electrochemical probing techniques which can be used to identify single-atomic catalytic sites within solid supports. First, we describe the basic principles of molecular probe methods for the study and analysis of electrocatalytic site behavior. In particular, the in situ probing technique enabled by surface interrogation scanning electrochemical microscopy (SISECM) can measure the active site density and kinetic rate with high resolution. An alternative electrochemical probing technique is further demonstrated on the basis of single-entity electrochemistry, which allows the unique electrochemical imaging of the size and catalytic rate of single atoms, molecules, and clusters. Next, the merits and limitations of different electrochemical techniques are then discussed, along with perspectives for future prospects. Apart from this, we further showcase the powerful capability of emerging electrochemical probing techniques for determining significant effects and properties of SACs for various electrocatalytic reactions, including oxygen reduction and evolution, hydrogen evolution, and nitrate reduction. Overall, electrochemical techniques with atomic resolution have greatly increased opportunities for observing, measuring, and understanding the surface and interface chemistry during energy conversion. In the future, it is anticipated that the development of electrochemical probing techniques will be advanced with innovative perspectives on the behavior and features of SACs. We hope that this Account can contribute in several ways to promoting the fundamental knowledge and technical progress of emerging electrochemical measurements for studying SACs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Origin of Room-Temperature Amplified Spontaneous Emission in CsPbBr 3 Single Crystals

CsPbBr 3 is an all-inorganic halide perovskite with excellent photoluminescence (PL) properties for laser applications. Amplified spontaneous emission (ASE) is a prerequisite for lasing and typically observed from low-dimensional CsPbBr3 nanostructures, where quantum confinement enhances ASE. However, a gain medium for lasing should be prepared into a robust bulk form that works under intense light illumination. Here, we demonstrate that bulk CsPbBr 3 single crystals exhibit highly efficient ASE with a threshold of 46 MWcm -2 at 520 nm, if PL reabsorption via the indirect Rashba gap is properly suppressed by thickness control. Based on a series of spectroscopic and microscopic measurements, we show that this below-the-gap absorption can significantly alter the PL feature and even the apparent color of the crystal depending on the crystal size. Our results show that a thin CsPbBr 3 single crystal can be utilized for lasing applications when engineered into a submillimeter thickness for effective light–matter interaction.

36 MATERIALS SCIENCE↗

Towards High-Performance AI4NP Applications on Modern GPU Platforms

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.

Mei, Xinxin↗