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At least 19 records

Precision measurements of EFT parameters and BAO peak shifts for the Lyman- α forest

We present precision measurements of the bias parameters of the one-loop power spectrum model of the Lyman- α (Ly- α ) forest, derived within the effective field theory (EFT) of large-scale structure. We fit our model to the three-dimensional flux power spectrum measured from the ACCEL 2 hydrodynamic simulations. The EFT model fits the data with an accuracy of below 2% up to k = 2 h Mpc − 1 . Further, we analytically derive how nonlinearities in the three-dimensional clustering of the Ly- α forest introduce biases in measurements of the baryon acoustic oscillations (BAOs) scaling parameters in radial and transverse directions. From our EFT parameter measurements, we obtain a theoretical error budget of Δ α ∥ = − 0.2 % ( Δ α ⊥ = − 0.3 % ) for the radial (transverse) parameters at redshift z = 2.0 . This corresponds to a shift of − 0.3 % (0.1%) for the isotropic (anisotropic) distance measurements. We provide an estimate for the shift of the BAO peak for Ly- α -quasar cross-correlation measurements assuming analytical and simulation-based scaling relations for the nonlinear quasar bias parameters resulting in a shift of − 0.2 % ( − 0.1 % ) for the radial (transverse) dilation parameters, respectively. This analysis emphasizes the robustness of Ly- α forest BAO measurements to the theory modeling. We provide informative priors and an error budget for measuring the BAO feature—a key science driver of the currently observing Dark Energy Spectroscopic Instrument (DESI). Our work paves the way for full-shape cosmological analyses of Ly- α forest data from DESI and upcoming surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST. Published by the American Physical Society 2025

de Belsunce, Roger (ORCID:0000000336604028)↗

The presence of Ru metal modifies the behavior of deuterium bound to pyridinic nitrogen in doped graphene-like materials

We used a combination of x-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) to investigate how the presence of a ruthenium (Ru) metal substrate modifies the N-D bond strength of the pyridinic nitrogen species in nitrogen (N)-doped graphene (Gr) on Ru(0001) compared to metal-free highly-oriented pyrolytic graphite (HOPG) substrate. The N-dopants were introduced through low-energy N+/N2+ irradiation. N is embedded in the carbon materials in two predominant configurations: as graphitic N (GN: N substituted in the hexagonal C lattice) and pyridinic N (PN: substitutional N adjacent to a C vacancy). XPS data showed that upon atomic deuterium (D) exposure at 220 K, the PN peak shifted to a higher binding energy by +1.2 eV for HOPG and +1.0 eV for N-doped graphene on Ru(0001), while the GN peak remained unchanged, indicating that the D atoms bound solely to pyridinic N. 85% of PN sites on HOPG can be saturated with D atoms, whereas only ~30% of pyridinic N sites are able to bind D atoms in N-doped Gr/Ru(0001). Our DFT analysis shows that this difference is due to the coordination of PN to Ru atoms, which necessitates bond cleavage of the N-Ru interaction prior to D atom adsorption. D begins desorbing from N-HOPG at ~573 K and is fully desorbed by ~973 K, whereas desorption from N-doped graphene on Ru(0001) begins at ~290 K, with complete desorption observed at ~700 K, indicating that the Ru metal weakens the N-D bond strength. We also studied a high-surface-area, layered, and porous N-doped carbon material, internally labeled NC900, which was synthesized by pyrolysis of glucose and graphitic carbon nitride (g-C3N4) at 1173 K. D exposure caused a +1.1 eV PN peak shift in NC900, with no change in the GN peak. Moreover, the NC900 exhibited the same desorption behavior as HOPG, demonstrating that well-defined model systems can effectively capture the behavior of more complex N-doped carbon materials.

Alupothe Gedara, Buddhika S.↗

Raman spectroscopy of neutron irradiated silicon carbide

The effects of neutron irradiation on microstructural evolution and the resultant changes in physical and mechanical properties are of critical importance for the development of silicon carbide (SiC) materials for nuclear applications. This study neutron-irradiated βSiC under a wide range of conditions at temperatures between 235 and 750°C and neutron doses of 0.01–11.8 displacements per atom, and then evaluated the effects on the SiC structure using Raman spectroscopy. The SiC optical phonon lines were shifted to lower wavenumbers by irradiation. Correlations were found among the wavenumber of the longitudinal optical phonon line, irradiation-induced swelling, and irradiation temperature. The peak shift also correlated indirectly with decreasing thermal conductivity of irradiated SiC. The irradiation-induced peak shift is explained by combinations of lattice strain, reduction of the elastic modulus, and other factors including decreasing coherent domain size. These findings bridge irradiation-induced microstructural changes and property changes and illustrate how Raman spectroscopy is a useful tool for nondestructively assessing irradiated SiC materials for nuclear applications.

Koyanagi, T.↗

Solid solutions limited by grain-boundary solute clustering in ultrafine-grained alloys

Immiscible Ag-Cu alloys exhibit complex behavior due to varying Cu solid solubilities reported under equilibrium and metastable conditions. In ultrafine-grained alloys, these limits are further complicated by a high fraction of grain boundaries, where solute atoms tend to segregate and, in some cases, form clusters. Here, this study investigates the influence of Cu solute segregation and clustering on solid-solution limits in ultrafine-grained Ag-Cu alloys synthesized by magnetron sputtering with varying Cu content. X-ray diffraction peak shifts reveal a solid-solution concentration plateau for Cu contents from 4.9 to 11.7 at %, in contrast to the peak shifts predicted by density-functional theory for Ag-Cu alloys. Scanning transmission electron microscopy further reveals limited solid solubility and the formation of numerous Cu-rich clusters at grain boundaries. Atomistic simulations demonstrate that such limited solubility does not arise from grain boundary segregation alone, but only when strong solute-solute interactions promote the formation of grain-boundary Cu solute clusters.

Density-functional theory↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

Design and performance assessment of a dual-mode latent thermal storage integrated heat pump across multiple climate zones

The electrification of space cooling and heating systems risks overloading the existing electrical grid during peak hours. Heat pumps integrated with thermal energy storage (HP-TES) offer a promising solution by shifting peak loads to off-peak hours, reducing grid strains. This work presents the design and assessment of a dual-mode HP-TES that uses a single 22°C phase-change material (PCM) as a heat source or sink in heating and cooling modes, respectively. Performance assessment was conducted using Modelica-based transient models, and full-year simulations were conducted across eight US climate zones using typical weather data. Two HP-TES performance metrics: peak energy reduction and recharge energy increases, were defined by comparing HP-TES energy consumption with base HP peak consumptions. Annual heating demand reductions (40–65%) exceeded cooling demand reductions (15–20%) due to the elimination of peak-hour backup heating. Cooling mode recharge energy requirements (0–10%) were reduced in locations with lower summer nighttime temperatures, while heating recharge requirements were lower than the high base-peak energy demand from backup heating. Simplified rapid methods that were 10 7 times faster than annual simulations were developed to predict seasonal cooling and heating energy reductions, and recharge energy requirements, with maximum deviations of ±2.5% and ±3.5% points. These methods enabled rapid parametric studies that identified optimal location-specific PCM temperatures between 22°C and 27°C, highlighting the need to consider both discharge and recharge energy requirements to achieve sustainable, energy-efficient peak load shifting across various climate zones.

25 ENERGY STORAGE↗

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗

Impact of in situ nuclear networks and atomic opacities on neutron star merger ejecta dynamics, nucleosynthesis, and kilonovae

Context. Binary neutron star merger (BNSM) ejecta are key sites of rapid neutron capture (r-process) nucleosynthesis and they produce kilonovae powered by the radioactive decay of freshly synthesized nuclei. Modeling their evolution requires multi-physics simulations involving hydrodynamics, nuclear reactions, and radiative processes. The impact of nuclear burning and atomic opacity is poorly understood and often treated with simplified prescriptions. Aims. We systematically investigate different treatments of nuclear heating, particle thermalization, and atomic opacities in radiation-hydrodynamics simulations of BNSM ejecta and kilonova light curves. Methods. Ejecta profiles from long-term numerical-relativity simulations of asymmetric neutron star binaries with a massive neutron star remnant were evolved to ∼30 days using a 2D ray-by-ray approach. We compared simplified heating-rate and thermalization prescriptions with in situ Nuclear reaction Network (NN) calculations that track nuclear energy deposition and include a composition-dependent thermalization scheme. We also contrasted various gray opacity models with a frequency-dependent treatment based on atomic calculations. Results. Coupling NN and hydrodynamics significantly affects nucleosynthesis and kilonova emission. Assuming homologous expansion alters abundance evolution and produces a narrower, less populated second r-process peak and a third peak shifted to higher mass numbers. The back-reaction of nuclear heating affects the temperature evolution enough to delay and redden the early (t∼ hours) kilonova peaks. A constant thermalization efficiency underestimates and reddens the early emission while overestimating the late-time luminosity compared to the composition-dependent treatment. Analytical opacity prescriptions yield a more extended, colder photosphere, resulting in dimmer, redder kilonovae at early times (t≲ hour), while the delayed recession of the photosphere prolongs the red emission at t ≳ 5 days. Conclusions. Coupling hydrodynamics to an in situ NN is crucial for reliable nucleosynthesis and kilonova predictions. Resolving the first several hundred milliseconds of the hydrodynamics is essential for robust nucleosynthesis calculations. Composition-dependent thermalization and frequency-dependent, atomic-physics-based opacities are needed to accurately capture the temperature evolution of the ejecta and the brightness and color evolution of the kilonova. Calibrated analytic nuclear-power fits with simplified thermalization and opacity prescriptions can still reproduce the density and temperature evolution of the ejecta.

74 ATOMIC AND MOLECULAR PHYSICS↗

Latent heat thermal energy storage performance maps enabling fast & accurate building energy simulations

Thermal energy storage (TES) using phase change materials (PCMs) has gained attention as an effective approach to manage energy demand fluctuations and shift peak building loads. PCM embedded heat exchangers (PCM-HXs) offer high energy storage density and low temperature variation during phase change, being suitable for load-shifting applications. However, this component is typically evaluated using computationally expensive methods, which present significant challenges when the ultimate goal is to assess the performance of PCM-HX integrated thermal energy storage systems in the full building context. In this paper, we present a methodology to generate highly accurate and computationally efficient PCM-HX performance maps which can be easily integrated into building energy simulation tools to analyze the feasibility of space conditioning systems with latent heat PCM-based TES. The performance maps are generated using a computationally efficient PCM-HX simulation tool based on a Generalized Resistance-Capacitance Model (GRCM) which can simulate arbitrary PCM-HXs with high accuracy and significantly less computational effort compared to full CFD simulations. The methodology was verified for a case study considering a 5-ton (~17.5 kW) air-to-water heat pump-thermal energy storage system (HP-TES), which was co-simulated in Modelica for a DOE prototype small-office building in Vienna, Austria, using Spawn of EnergyPlus™. The TES performance maps provided accurate predictions of PCM-HX behavior when used as Modelica component, with deviations within 2-4% while also achieving at least 103 computational time reduction. Leveraging this faster prediction capability, four PCMs with different melting temperatures for cooling (12°C, 16°C) and heating (31°C, 36°C) were assessed to investigate their impact on system performance. This work highlights the importance of robust PCM-HX models for efficient and high-fidelity building-level simulations, presenting new opportunities for advanced control strategy development and parametric analysis of TES configurations in a computationally efficient manner

Modelica Building Simulations↗

Reviews and syntheses: Opportunities for robust use of peak intensities from high-resolution mass spectrometry in organic matter studies

Abstract. Earth's biogeochemical cycles are intimately tied to the biotic and abiotic processing of organic matter (OM). Spatial and temporal variations in OM chemistry are often studied using direct infusion, high-resolution Fourier transform mass spectrometry (FTMS). An increasingly common approach is to use ecological metrics (e.g., within-sample diversity) to summarize high-dimensional FTMS data, notably Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). However, problems can arise when FTMS peak-intensity data are used in a way that is analogous to abundances in ecological analyses (e.g., species abundance distributions). Using peak-intensity data in this way requires the assumption that intensities act as direct proxies for concentrations. Here, we show that comparisons of the same peak across samples (within-peak) may carry information regarding variations in relative concentration, but comparing different peaks (between-peak) within or between samples does not. We further developed a simulation model to study the quantitative implications of using peak intensities to compute ecological metrics (e.g., intensity-weighted mean properties and diversity) that rely on information about both within-peak and between-peak shifts in relative abundance. We found that, despite analytical limitations in linking concentration to intensity, ecological metrics often perform well in terms of providing robust qualitative inferences and sometimes quantitatively accurate estimates of diversity and mean molecular characteristics. We conclude with recommendations for the robust use of peak intensities for natural organic matter studies. A primary recommendation is the use and extension of the simulation model to provide objective guidance on the degree to which conceptual and quantitative inferences can be made for a given analysis of a given dataset. Broad use of this approach can help ensure rigorous scientific outcomes from the use of FTMS peak intensities in environmental applications.

54 ENVIRONMENTAL SCIENCES↗

Controlled Reaction Dynamics of Binary Hexafluorides to Explore New Chemical Signatures

Conclusions • Successfully halted the UF6 hydrolysis reaction and trapped intermediate complexes • Simple alcohol instead of water leads to shifting of bands in UF6 likely from change in matrix effects • MoF6 reaction shows some potential for methyl group being present in structure of intermediates • Future work with bulkier R-groups will hopefully reveal further information as to the reaction pathway and intermediate structure via kinetics and peak shifting

Dorris, Austin L. [Savannah River National Laborat↗

Multifunctional Heat Pump with Energy Storage Capability

Replacing gas furnaces with heat pumps on a large scale can pose challenges to the electrical grid. It will significantly increase the demand, strain the electrical grid, especially during peak usage times. To ensure that heat pumps contribute to reducing emissions, it's essential to increase the share of renewable energy in the grid. However, the supply of renewable energy is unstable. Large scale of electrification must address the concern of grid resilience to meet necessary heating/cooling demands and shift peak electric load. All these require future heat pumps having energy storage capability. These systems can store excess energy during low-demand periods and release it during high-demand periods, reducing stress on the grid. This paper will introduce an innovative configuration, control, and laboratory investigations of a multifunctional packaged heat pump. In addition to the original indoor and outdoor air coils, the heat pump has a parallel hydronic loop with a brazed plate heat exchanger (BHP). The hydronic loop circulates hot/chilled water to store heating/cooling energy in phase change material (PCM). It is capable of space cooling, space heating, cooling energy storage/defrosting, water heating/heating energy storage with outdoor air source or indoor air source, and cooling/heating energy free discharge. The laboratory studies and breadboard unit are presented. Additionally, building energy simulation demonstrates utility cost reduction potential via charging PCM panels/ceilings during off-peak hours and releasing the energy during peak hours to mitigate the peak power consumption.

Shen, Bo↗

Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control

The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.

catalysts↗

Nanoscale Compositional and Strain Gradients Enable High‐Speed and Amplitude‐Resolved Pyroelectric Sensing

The frequency response of pyroelectric sensors is fundamentally governed by thermal time constant (τth, determined by thermal mass and thermal conductance) and electrical impedance arising from film capacitance and readout circuit. Conventional bulk LiTaO3 detectors are optimized for high responsivity at low modulation frequencies (0.1-10 Hz), possessing a large τth that thermally averages rapid temperature oscillations at elevated modulation frequencies, limiting fidelity in resolving dynamic varying thermal signals. Here, compositional and strain gradients are introduced into 100-nm-thick relaxor-ferroelectric films reducing τth to ≈2 µs and producing built-in potentials (≈1.45 V or 145 kV cm-1) that enhance the pyroelectric coefficient and suppress the dielectric constant. This enables complementary dual-mode operation by enhancing current-mode electrical responsivity and improving the voltage-mode figure of merit - advantageous for superior temperature resolution (ΔTmin ≈ 30 µK). The responsivity peak shifts to near 1 kHz (>2500-times higher than conventional bulk sensors), with measurable responsivity extending to a carrier frequency of 100 kHz and amplitude-resolved detection at modulation frequencies up to 15 kHz. These results establish nanoscale internal-field engineering can reshape electro-thermal trade-off in pyroelectric thin films toward zero-bias, high-thermal-sensitivity, and amplitude-resolved thermal sensing across a wide frequency bandwidth.

Lin, Ching‐Che↗

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗

Characterization of SiO 2 Thermally Grown Oxide Stress Evolution of EBCs with Al-Containing Dopants

SiC/SiC ceramic matrix composites (CMCs) are desired for use in combustion environments to achieve higher turbine operating temperatures. However, CMCs require environmental barrier coatings (EBCs) for protection from the gas environment. EBC systems are known to primarily fail through coating delamination via growth of a thermally grown oxide (TGO) at the EBC—silicon bond coating interface when exposed to steam, which accelerates the TGO growth rate. The TGO undergoes a phase transformation during thermal cycling, which results in stresses that may encourage EBC spallation. Yb-silicate EBCs with mullite and yttrium aluminum garnet (YAG) dopant additions were deposited on SiC substrates with a Si intermediate bond coating and exposed to thermal cycling in steam at 1350 °C. The impact of Al dopant additions on the TGO growth rate and the SiO 2 phase transformation was assessed. Photo-stimulated luminescence spectroscopy (PSLS) was used to characterize the Al-containing phases and to measure stress evolution in the EBC following exposure using the stress-induced peak shift of the R-lines of mullite. Raman microscopy was used to map the stresses in the Si bond coating following exposure. It was found that the TGO phase transformation upon cooling increased compressive stress in the Si bond coating within 15 µm of the TGO.

Building Materials↗

Chemical changes from N-doped graphene and Metal-Organic Frameworks to N-G/MOF composites for improved electrocatalytic activity

Integrating N doped graphene (N G) with Metal Organic Frameworks (MOFs) enhances catalytic activity for oxygen reduction reaction (ORR), often exceeding both the performances of their precursors and, in some cases, even PGM based catalysts. However, the factors driving this improved catalytic activity in N G/MOF composites remain unexplored, particularly from the perspective of the chemical changes. To investigate the chemical changes in N G and MOF upon their integration and the implications of these changes on ORR catalytic activity, an N G/MOF was synthesized from N G with a MOF (ZIF 8) following a mechanochemical wet ball milling process. The N G, ZIF 8, and N G/MOF samples were examined for changes in elemental composition, chemical state of carbon, different nitrogen and carbon bonds, and other chemical interactions. In the N G/MOF catalyst, compared to its N G and ZIF 8 precursors, the relative oxygen content increased, indicating the formation of additional oxygen containing groups. The C 1s peak shifted to a lower binding energy in N G/MOF, suggesting changes in the overall chemical or oxidation state of the carbon atoms. Besides, the increase in pyridinic N functional groups in N G/MOF points to the formation of additional active sites. Furthermore, the formation of C Zn bonds in N G/MOF suggests the probable emergence of single atom Zn sites, while the increase in C=O bonds points to the formation of carboxyl or carbonyl groups. These chemical changes could be linked to the enhanced electrocatalytic activity of the N G/MOF composite for ORR. In conclusion, this study may also be beneficial for other research focused on developing composite catalysts involving various N G and MOF materials.

25 ENERGY STORAGE↗

Understanding the deformation behavior of the γ rich transformative Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy using in situ synchrotron diffraction

In situ tensile testing coupled with synchrotron x-ray diffraction was used to study the deformation behavior of metastability-engineered Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy. Monitoring the evolution of phase fraction and strain hardening response allowed the determination of true critical stress for the onset of the transformation-induced plasticity (TRIP) to be ∼375 MPa, preceded by slip starting at ∼255 MPa. In situ EBSD was used to validate the critical stress for transformation at the microstructure level and observe slip traces to confirm prior slip activity before the transformation. Further, a modeling framework based on stacking fault energy (SFE) was developed to predict the critical stress for transformation. Modeling suggested the SFE of the alloy to fall nearly 15 mJ/m 2 , which agrees well with SFE values calculated using synchrotron peak shifting (12 mJ/m 2 ) and thermodynamic calculation (11 mJ/m 2 ). As a result of γ-fcc to ε-hcp phase transformation, new {0002} ε planes emerged parallel to unaligned {111} γ planes with the tensile loading following S-N orientation relationship. Such selective emergence of new diffraction rings corresponding to ε phase is understood based on the reorientation of γ crystals with reference to tensile axis. In conclusion, this approach can be extended to effectively design alloys based on critical stress required for activating different deformation mechanisms to further push the limits of the strength-ductility envelope.

Complex concentrated alloy↗