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At least 973 records · Page 54

New isotope 286 Mc produced in the 243 Am + 48 Ca reaction

In this paper, we present results of the second experiment on the synthesis of Mc isotopes in the 243 Am + 48 Ca reaction performed at the gas-filled separator DGFRS-2 of the SHE Factory at JINR. Here, the new isotope 286 Mc was synthesized, and its half-life of $20^{+98}_{–9}$ ms and α-particle energy of 10.71 ± 0.02 MeV were determined. A 286 Mc α–decay chain was recorded down to the spontaneous fission of 266 Db. The spontaneous fission of 279 Rg was observed for the first time in one of four new decay chains of 287 Mc. The excitation function of the reaction was measured at three 48 Ca energies of 242, 250, and 259 MeV; the latter resulted in the first observation of the 5$\textit{n}$–evaporation channel with a cross section of $0.5^{+1.3}_{–0.4}$ pb. The decay properties of 21 previously known odd–$\textit{Z}$ isotopes were improved. The potential for an electron-capture decay mode is discussed for 288 Mc and 284 Nh isotopes. The half-lives of spontaneously fissioning nuclei produced in the 48 Ca–induced reactions with actinide targets are compared with several theoretical predictions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nucleation of Dislocations in 3.9 nm Nanocrystals at High Pressure

As circuitry approaches single nanometer length scales, it has become important to predict the stability of single nanometer-sized metals. The behavior of metals at larger scales can be predicted based on the behavior of dislocations, but it is unclear if dislocations can form and be sustained at single nanometer dimensions. Here, we report the formation of dislocations within individual 3.9 nm Au nanocrystals under nonhydrostatic pressure in a diamond anvil cell. We used a combination of x-ray diffraction, optical absorbance spectroscopy, and molecular dynamics simulation to characterize the defects that are formed, which were found to be surface-nucleated partial dislocations. These results indicate that dislocations are still active at single nanometer length scales and can lead to permanent plasticity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Developing Scaling Relationships for Molecular Electrocatalysis through Studies of Fe-Porphyrin-Catalyzed O 2 Reduction

The oxygen reduction reaction (ORR) is a multiproton/multielectron transformation in which dioxygen (O 2 ) is reduced to water or hydrogen peroxide and serves as the cathode reaction in most fuel cells. The ORR (O 2 + 4e – + 4H + → 2H 2 O) involves up to nine substrates and thus requires navigating a complicated reaction landscape, typically with several high-energy intermediates. Many catalysts can perform this reaction, though few operate with fast rates and at low overpotentials (close to the thermodynamic potential). Attempts to optimize these parameters, both in homogeneous and heterogeneous electrocatalytic systems, have focused on modifying catalyst design and understanding kinetic/thermodynamic relationships between catalytic intermediates. One such method for analyzing and predicting catalyst reactivity and efficiency has been the development of “molecular scaling relationships”. In this work, we share our experience deriving and utilizing molecular scaling relationships for soluble, iron-porphyrin-catalyzed O 2 reduction in organic solvents. These relationships correlate turnover frequencies (TOF max ) and effective overpotentials (η eff ), properties uniquely defined for homogeneous catalysts. Following a general introduction of scaling relationships for both homogeneous and heterogeneous electrocatalysis, we describe the components of such scaling relationships: (i) the overall thermochemistry of the reaction and (ii) the rate and rate law of the catalyzed reaction. We then show how connecting these thermodynamic and kinetic parameters reveals multiple molecular scaling relationships for iron-porphyrin-catalyzed O 2 reduction. For example, the log(TOF max ) responds steeply to changes in ηeff that result from different catalyst reduction potentials (18.5 decades in TOF max /V in η eff ) but much less dramatically to changes in η eff that arise from varying the pKa of the acid buffer (5.1 decades in TOF max /V in η eff ). Thus, a single scaling relationship is not always sufficient for describing molecular electrocatalysis. This is particularly evident when the catalyst identity and reaction conditions are coupled. Using these multiple scaling relationships, we demonstrate that the metrics of turnover frequency and effective overpotential can be predictably tuned to achieve faster rates at lowered overpotentials. This Account uses a collection of related stories describing our research on soluble iron-porphyrin-catalyzed ORR to show how molecular scaling relationships can be derived and used for any electrocatalytic reaction. Such scaling relationships are powerful tools that connect the thermochemistry, mechanism, and rate law for a catalytic system. We hope that this collection shows the utility and simplicity of the molecular scaling approach for understanding catalysis, for enabling direct comparisons between catalyst systems, and for optimizing catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Seeing the Disturbed Forest for the Trees: Remote Sensing Is Underutilized to Quantify Critical Zone Response to Unprecedented Disturbance

Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post-disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground-based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.

54 ENVIRONMENTAL SCIENCES↗

Save or spend? Diverging water‐use strategies of grasses and encroaching clonal shrubs

Abstract Shrub encroachment is one of the primary threats to mesic grasslands around the world. This dramatic shift in plant cover has the potential to alter ecosystem‐scale water budgets and responses to novel rainfall regimes. Understanding divergent water‐use strategies among encroaching shrubs and the grasses they replace is critical for predicting shifts in ecosystem‐scale water dynamics as a result of shrub encroachment, particularly if drought events become more frequent and/or severe in the future. In this study, we assessed how water‐use traits of a rapidly encroaching clonal shrub (Cornus drummondii) and a dominant C 4 grass (Andropogon gerardii) impact responses to changes in water availability in tallgrass prairie. We assessed intra‐annual change in depth of water uptake, turgor loss point and stomatal regulation in each species. Sampling took place at Konza Prairie Biological Station (northeastern KS, USA) during the 2021 and 2022 growing seasons. Cornus drummondiishifted from shallow to deep soil water sources across the 2021 and 2022 growing seasons. This plasticity in depth of water uptake facilitated a ‘wasteful’ water‐use strategy inC. drummondii, where stomatal conductance and transpiration rates continued to increase even when no further gain in photosynthetic rate occurred.A. gerardiiphotosynthetic rates and stomatal conductance were more variable through time and were more responsive to changes in leaf water potential thanC. drummondii. However, intra‐annual adjustment of turgor loss point was more pronounced inC. drummondii(Δπ TLP = −0.48 MPa ± 0.15 SD) than inA. gerardii(Δπ TLP = −0.29 MPa ± 0.19 SD). Synthesis. These results suggest thatC. drummondiiis highly resilient to changes in water availability in surface soils and will likely remain unaffected by future droughts unless they are severe enough to reduce the availability of deep soil water. Given that clonal shrubs are key invaders of grasslands world‐wide, increased leaf‐level water loss is expected to accelerate ecosystem‐level drying as clonal shrub encroachment proceeds in mesic grasslands.

Environmental Sciences & Ecology↗

Synthesis and characterization of isotopically barcoded nickel, molybdenum, and tungsten taggants for intentional nuclear forensics

Intentional nuclear forensics is a concept wherein the deliberate addition of benign and persistent material signatures to nuclear material can be used to reduce the time between the discovery of material outside of regulatory control and determination of its original provenance. One concept within intentional nuclear forensics involves the use of perturbed stable isotopes to generate unique isotope ratio “barcodes” to encode information (e.g., production batch, location, etc.) and track material throughout the nuclear fuel cycle. Synthesis of taggant species of nickel (Ni), molybdenum (Mo), and tungsten (W) was undertaken via a double-spike mechanism, wherein two highly enriched isotopes of interest per elemental taggant were mixed to form an enriched “double-spike” which was subsequently isotopically diluted with bulk material having a natural isotopic composition. Two taggant species perturbing isotopic ratios, alpha (α) and beta (β), for each of Ni, Mo, and W were synthesized. Independent measurements of double spikes and alpha and beta taggant species agreed within uncertainty and are clearly resolvable from natural compositions. High-precision analyses were independently performed by MC-ICP-MS at two U.S. National Laboratories, with consensus values and uncertainties calculated for all samples. Observed isotopic perturbations in the final taggant species measured on the order of hundreds to thousands of permille (‰) with respect to natural for isotope ratios of interest (e.g., 60 Ni/ 58 Ni, 100 Mo/ 98 Mo, 186 W/ 183 W). Discrepancies between modeled and measured isotopic compositions were observed and are largely attributed to imprecise vendor assay values for starting materials. Using measured starting material compositions as inputs for the mixing model improved the level of agreement between predicted and measured α and β taggant isotope ratios. Overall, characterization of all taggant species demonstrates that this “barcode” concept could have viability for use in nuclear forensics. Finally, it is expected that for any two-isotope mixing array dozens of isotopic barcodes could be encoded into a material system and subsequently resolved utilizing modern mass spectrometric methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Impact of ion fluxes across thylakoid membranes on photosynthetic electron transport and photoprotection

In photosynthetic thylakoid membranes the proton motive force (pmf) not only drives ATP synthesis, in addition it is central to controlling and regulating energy conversion. As a consequence, dynamic fine-tuning of the two pmf components, electrical (Δψ) and chemical (ΔpH), is an essential element for adjusting photosynthetic light reactions to changing environmental conditions. Good evidence exists that the Δψ/ΔpH partitioning is controlled by thylakoid potassium and chloride ion transporters and channels. However, a detailed mechanistic understanding of how these thylakoid ion transporter/channels control pmf partitioning is lacking. In this work, we combined functional measurements on potassium and chloride ion transporter and channel loss-of-function mutants with extended mathematical simulations of photosynthetic light reactions in thylakoid membranes to obtain detailed kinetic insights into the complex interrelationship between membrane energization and ion fluxes across thylakoid membranes. The data reveal that potassium and chloride fluxes in the thylakoid lumen determined by the K + /H + antiporter KEA3 and the voltage-gated Cl – channel VCCN1/Best1 have distinct kinetic responses that lead to characteristic and light-intensity-dependent Δψ/ΔpH oscillations. These oscillations fine-tune photoprotective mechanisms and electron transport which are particularly important during the first minutes of illumination and under fluctuating light conditions. By employing the predictive power of the model, we unravelled the functional consequences of changes in KEA3 and VCCN1 abundance and regulatory/enzymatic parameters on membrane energization and photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗

Direct cross-section measurement of the weak r -process Sr 88 ( α , n ) Zr 91 reaction in ν -driven winds of core-collapse supernovae

About half of the heavy elements beyond iron are known to be produced by the rapid neutron capture process, known as the r process. However, the astrophysical site producing the r process is still uncertain. Chemical abundances observed in several cosmic sites indicate that different mechanisms should be at play. For instance, the abundances around silver measured in a subset of metal-poor stars indicate the presence of a weak r process. This process may be active in neutrino-driven winds of core collapse supernovae where (α,n) reactions dominate the synthesis of Ζ ≈ 40 elements in the expelled materials. Scarcely measured, the rates of (α,n) reactions are determined from statistical Hauser-Feshbach calculations with α-optical-model potentials, which are still poorly constrained. Further, the uncertainties of the (α,n) reaction rates therefore make a significant contribution to the uncertainties of the abundances determined from stellar modeling. In this work, the 88 Sr (α,n)⁢ 91 Zr reaction which impacts the weak r-process abundances has been probed at astrophysics energy for the first time; directly measuring the total cross sections at astrophysical energies of 8.37–13.09 MeV in the center of mass (3.8–7.5 GK). Two measurements were performed at ATLAS with the electrically segmented ionization chamber MUSIC, in inverse kinematics, while following the active target technique. The cross sections of this α-induced reaction on 88 Sr, located at the shell closure N = 50, have been found to be lower than expected, by a factor of 3, despite recent statistical calculations validated by measurements on neighboring nuclei. This result encourages more experimental investigations of (α,n) reactions, at Ν = 50 and towards the neutron-rich side, to further test the predictive power and reliability of such calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys (HEAs), especially when integrating computational predictions with sparse experimental observations. This study systematically evaluates the training and testing performance of four prominent surrogate models—conventional Gaussian processes (cGP), Deep Gaussian processes (DGP), encoder-decoder neural networks for multi-output regression and eXtreme Gradient Boosting (XGBoost)—applied to a hybrid dataset of experimental and computational properties of the 8-component HEA system Al-Co-Cr-Cu-Fe-Mn-Ni-V. We specifically assess their capabilities in predicting correlated material properties, including yield strength, hardness, modulus, ultimate tensile strength, elongation, and average hardness under dynamic/quasi-static conditions, alongside auxiliary computational properties. The comparison highlights the strengths of hierarchical deep modeling approaches in handling heteroscedastic, heterotopic, and incomplete data commonly encountered in materials science. Our findings illustrate that combined surrogate models such as DGPs infused with machine-learned priors outperform other surrogates by effectively capturing inter-property correlations and by assimilating prior knowledge. This enhanced predictive accuracy positions the combined surrogate models as powerful tools for robust and data-efficient materials design.

36 MATERIALS SCIENCE↗

Solid State Reduction Driven Synthesis of Mn Containing Multi-principal Component Alloys

In recent years, high entropy alloys (HEAs), also known as multi-principal component alloys (MPCAs) have emerged as a new and exciting class of materials. This paper reports on the solid state reduction synthesis of a series of CoFeNiMn-based MPCA compositions, starting from a mixture of the corresponding oxides. One of the aims of the study was to test whether the degree of reduction of MnO, a highly stable oxide, could be enhanced by tailoring the alloy composition. Specifically, the influence of Ni content was studied because Ni exhibits a significant negative enthalpy of mixing with Mn. High purity precursor powders of Co(OH) 2 , Fe 2 O 3 , MnO 2 , and NiO were milled and mixed using standard ceramic processing methods. Here, the nominal sample compositions (assuming complete oxide reduction) were (CoFeMn) x Ni (1-x) , for x = 0, 0.083, 0.166, and 0.25. The oxide samples were subjected to a series of isothermal reduction anneals in flowing 3 pct H 2 –Ar at 1100 °C. The resulting microstructures were characterized using scanning electron microscopy (SEM), X-ray energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD). The composition of the resulting MPCAs was determined quantitatively using wavelength dispersive spectroscopy (WDS) in the electron microprobe. The study revealed that for each of the initial oxide compositions studied, it was possible to achieve an MPCA with ~ 25 at. pct Mn. These results were found to be consistent with the predictions of a thermodynamic model whereby a negative enthalpy of mixing (ΔH mix ), combined with a contribution from configurational entropy, can offset a positive free energy of reduction (ΔG red ). The incorporation of vibrational entropy into first principles calculations was found to have a significant effect on the predicted crystal structure of the MPCAs.

36 MATERIALS SCIENCE↗

Dynamics of poly[n]catenane melts

Inspired by advances in the chemical synthesis of interlocking polymer architectures, extensive molecular dynamics simulations have been conducted to study the dynamical properties of poly[n]catenanes-polymers composed entirely of interlocking rings-in the melt state. Both the degree of polymerization (number of links) and the number of beads per ring are systematically varied, and the results are compared to linear and ring polymers. Herein, a simple Rouse-like model is presented, and its analytical solution suggests a decomposition of the dynamics into "ring-like" and "linear-like" regimes at short and long times, respectively. In agreement with this picture, multiple sub-diffusive regimes are observed in the monomer mean-squared-displacements even though interchain entanglement is not prevalent in the system. However, the Rouse-type model does not account for the topological effects of the mechanical bonds, which significantly alter the dynamics at intermediate length scales both within the rings and at the chain segment scales. The stress relaxation in the system is extremely rapid and may be conveniently separated into ring-like and linear-like contributions, again in agreement with the Rouse picture. However, the viscosity has a non-monotonic dependence on the ring size for long chains, which disagrees strongly with theoretical predictions. This unexpected observation cannot be explained in terms of chain disentanglement and is inconsistent with other measures of polymer relaxation. Possible mechanisms for this behavior are proposed and implications for materials design are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental measurement of the rapid mixing of fuel and air in a multi-element diffusion (Hencken) burner

Flat flame burners are valuable tools for studying complex combustion phenomena like particle synthesis due to the well-controlled and well-behaved initial and boundary conditions. In this study, the methane/air flame temperature and tracer density profiles of a multi-element diffusion burner equipped with a central tube were characterized using krypton (Kr) x-ray fluorescence at the Advanced Photon Source at Argonne National Laboratory. The experiments were performed using a fuel-to-oxygen equivalence ratio of 0.8 and 3.3% Kr by volume was added to the reactant gases. One- and two-dimensional scans of non-combusting (i.e., cold flow) and combusting conditions, both with and without flow through the central tube were performed. Spatially-resolved Kr number density profiles were obtained at different planar locations and heights above the surface of the burner. The results show rapid mixing occurred near the exit-plane of the burner and increased spatial uniformity was achieved from 0.1 mm to 0.5 mm above the surface of the burner. Further, the data also showed the impact of the central tube flow on the main methane/air flame, including evidence of the central tube flow mixing with the main flow. Flame temperatures were calculated from the fluorescence measurements at various heights above the burner surface and were in good agreement with model predictions for a burner stabilized flame. These high-fidelity measurements provide accurate baseline data that are particularly valuable for understanding the effects of fuel and air mixing on downstream phenomena, such as the formation of condensed-phase products.

42 ENGINEERING↗

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization

The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200 000 integrated design evaluations were performed exploring the trade-offs between capital cost minimization and operational reliability (maximizing q 95 ) while satisfying engineering constraints including 250 ± 50 MW net electric power, tritium breeding ratio > 1.1, power exhaust limits and an hour flattop time. Both configurations achieve similar cost-performance Pareto fronts through contrasting design philosophies. PT, while demonstrating resilience to pedestal degradation (compensating for up to 40% reduction), are constrained to larger machines (R 0 > 6.5 m) by the narrow operational window between L–H threshold requirements and the research-established power exhaust limit (P sol /R < 15 MW m –1 ). This forces optimization through comparatively reduced magnetic field (∼8 T). NT configurations exploit their freedom from these constraints to access compact, high-field designs (R 0 ~ 5.5 m, B 0 >12 T), creating natural synergy with advancing HTS technology. Sensitivity analyses reveal that PT’s economic viability depends critically on uncertainties in L–H threshold scaling and power handling limits. Notably, a 50% variation in either could eliminate viable designs or enable access to the compact design space. These results suggest configuration selection should be risk-informed: PT offers the lowest-cost path when operational constraints can be confidently predicted, while NT is robust to large variations in constraints and physics uncertainties.

FUSE framework↗

Synthesis and structural characterization of the new Zintl phases Ba 3 Cd 2 P 4 and Ba 2 Cd 2 P 3 . Rare example of small gap semiconducting behavior with negative thermopower within the range 300 K-700 K

The new Zintl phases Ba 3 Cd 2 P 4 and Ba 2 Cd 2 P 3 have been synthesized using Pb flux, which allowed for the growth of 4-5 mm large crystals. The structures were determined utilizing single-crystal X-ray diffraction methods. Both compounds crystalize in the monoclinic crystal system (space group C2/m (No. 12)) and their structures are closely related. The structure of Ba 3 Cd 2 P 4 can be seen as being comprised of divalent Ba atoms and conjoined CdP 4 tetrahedra in the form of [Cd 2 P 4 ] 6- layers. Within the layers, homoatomic P–P bonds are present, which if cleaved, leave two infinite [CdP 3 ] 7- chains running along the crystallographic b-axis. The other structure, that of Ba 2 Cd 2 P 3 , can be rationalized as also having divalent Ba atoms and conjoined CdP4 tetrahedra in the form of [Cd 2 P 3 ] 6- layers. These layers, again, can be visualized as chains that run down the crystallographic b-axis, which are further connected by P-P dimers. Electronic band structure calculations show that each structure has an optimal number of valence electrons, and therefore conform to the Zintl-Klemm concept. Accordingly, the two compounds can be considered small band gap semiconductors, with band gaps of ca. 0.1 eV and 0.6 eV for Ba3Cd2P4 and Ba 2 Cd 2 P 3 , respectively. Electrical resistivity measurements show that Ba3Cd2P4 displays a large resistivity value at room temperature and an experimental band gap of ca. 0.05 eV, which fits reasonably well with the theoretical predictions. Thermopower measurements show that throughout the temperature range 300 K-700 K, Ba 3 Cd 2 P 4 displays a negative Seebeck coefficient. Here, the extremum value of -84 μV is reached at 630 K, suggestive of an n-type semiconductor, a rarity among Zintl phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controls and relationships of soil organic carbon abundance and persistence vary across pedo–climatic regions

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (n Profile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth–resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo–climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo–climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo–climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process–oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo–climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

54 ENVIRONMENTAL SCIENCES↗

Effective medium approximation for the refractive index of stratified metal oxide composites synthesized by atomic layer deposition

Atomic layer deposition (ALD) is a unique method for synthesizing conformal layers with precise composition. It is especially useful for the synthesis of mixed metal oxides for functional materials. One application of interest is the use of ALD for tailoring the refractive index of coatings. In homogeneously distributed composites of metal oxides, the refractive properties can be approximated as the average of the indices of the components. This is known as an effective medium approximation (EMA) and can be used to design the macroscopic properties of composites. ALD produces layered, anisotropic films, so the validity of an EMA in describing these films is not clear. Here, we use optical simulations and experimental characterization of stratified composites of TiO 2 and Al 2 O 3 to study the application of an EMA to the transmission and reflection behavior of ALD-prepared mixed metal oxide thin films. We found that when the characteristic layer thickness is smaller than roughly 10 nm, the optical spectra of theoretical and experimental ALD films match the equivalent theoretical spectra for a material with a refractive index calculated from a simple, compositionally weighted EMA. Hence, this EMA could describe the transmission and reflectance spectra in ALD-derived TiO2–Al 2 O 3 nanolaminates when the films were sufficiently stratified even without thorough characterization of the real layers in the films. As a result, we demonstrated that ALD can be used to prepare effectively homogenous mixed metal oxide films with a predictable, tailorable refractive index of any value between those of the TiO 2 and Al 2 O 3 component materials.

42 ENGINEERING↗