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At least 181 records · Page 10

Structural modulation, physical properties, and electronic band structure of the kagome metal UCr 6 ⁢Ge 6

The chemical flexibility of the 𝑅⁢𝑀 6 ⁢𝑋 6 stoichiometry, where an 𝑓-block element is intercalated in the CoSn structure type, allows for the tuning of flatbands associated with kagome lattices to the Fermi level and for emergent phenomena due to interactions between the 𝑓- and 𝑑-electron lattices. Yet, 5⁢𝑓 members of the “166” compounds are underrepresented compared with 4⁢𝑓 members. In this work, we report single-crystal growth of UCr 6 ⁢Ge 6 , which crystallizes in a monoclinically distorted Y 0.5⁢ Co 3 ⁢Ge 3 -type structure. The real-space character of the modulation, which is unique within the 𝑅⁢𝑀 6 ⁢𝑋 6 family, is approximated by a 3×1×2 supercell of the average monoclinic cell. The compound has kagome-lattice flatbands near the Fermi level and a moderately enhanced electronic heat capacity, as evidenced by its low-temperature Sommerfeld coefficient (𝛾=86.5 mJ mol −1 K −2 ) paired with band structure calculations. The small, isotropic magnetization and featureless resistivity of UCr 6 ⁢Ge 6 suggest itinerant uranium 5⁢𝑓 electrons and Pauli paramagnetism. Angle-resolved photoemission spectroscopy results provide evidence for uranium 5⁢𝑓 weight at the Fermi level and for a flatband near the Fermi level associated with the chromium 3⁢𝑑 kagome lattice. The isotropic magnetic behavior of the uranium 5⁢𝑓 electrons starkly contrasts with localized behavior in other uranium 166 compounds, highlighting the high tunability of the magnetic ground state across the material family.

36 MATERIALS SCIENCE↗

Diversification of JAZ‐MYC signaling function in immune metabolism

Summary Jasmonate (JA) re‐programs metabolism to confer resistance to diverse environmental threats. Jasmonate stimulates the degradation of JASMONATE ZIM‐DOMAIN (JAZ) proteins that repress the activity of MYC transcription factors. In Arabidopsis thaliana , MYC and JAZ are encoded by 4 and 13 genes, respectively. The extent to which expansion of the MYC and JAZ families has contributed to functional diversification of JA responses is not well understood. Here, we investigated the role of MYC and JAZ paralogs in controlling the production of defense compounds derived from aromatic amino acids (AAAs). Analysis of loss‐of‐function and dominant myc mutations identified MYC3 and MYC4 as the major regulators of JA‐induced tryptophan metabolism. We developed a JAZ family‐based, forward genetics approach to screen randomized jaz polymutants for allelic combinations that enhance tryptophan biosynthetic capacity. We found that mutants defective in all members ( JAZ1/2/5/6 ) of JAZ group I over‐accumulate AAA‐derived defense compounds, constitutively express marker genes for the JA–ethylene branch of immunity and are more resistant to necrotrophic pathogens but not insect herbivores. In defining JAZ and MYC paralogs that regulate the production of amino‐acid‐derived defense compounds, our results provide insight into the specificity of JA signaling in immunity.

jasmonate↗

Incorporating FLEX Strategies in Multi-Unit Probabilistic Risk Assessment

The catastrophic Fukushima nuclear accident reminded nuclear community about the possibilities of extreme accident scenarios, including those involving multiple reactor units on the same site. As the responses to the Fukushima accident, the nuclear power industry developed and implemented a series of strategies, including the Diverse and Flexible Coping Strategies (FLEX), to enhance the coping capacities of nuclear power plants (NPPs) under extreme accidents. This study intends to examine the impact of FLEX strategies on the risk from all the reactor units on the same NPP site, including risks from accidents involving a single unit and from accidents involving multiple units. The fundamental, methodological element of this study is Multi-Unit Probabilistic Risk Assessment (MUPRA), which requires a shift in Probabilistic Risk Assessment (PRA) from a “one-reactor-at-a-time” mindset to a “considering all reactors sharing a site as a unity” one. An integrated modeling approach for multi-unit event sequence development will be leveraged to develop MUPRA model and address the intra-unit and inter-unit dependencies. Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), a PRA software developed and maintained by Idaho National Laboratory (INL) for the U.S. Nuclear Regulatory Commission (NRC), will serve as the platform for MUPRA modeling. This study selects Loss Of Offsite Power (LOOP) as a representative initiating event, which may occur on a generic two-unit NPP site and impacts both reactor units on the site. First, an MUPRA model, including multi-unit event trees, will be developed to obtain single-unit and multi-unit accident scenarios. Next, different FLEX strategies will be assumed, including FLEX equipment for a unit cannot be used for another unit, FLEX equipment for multiple units can be used in a cross-connected manner, etc. Lastly, the effectiveness of each postulated FLEX strategy will be evaluated by incorporating the corresponding FLEX equipment and deployment logic in the MUPRA model.

99 GENERAL AND MISCELLANEOUS↗

Hazard Detection Detector Cards

This report presents a comprehensive summary of five advanced anomaly detection tools developed and deployed by Oak Ridge National Laboratory in support of the VA’s Health Information Technology modernization. These detectors—Order Path Tracker, Trend Watcher, Pain Pointer, Performance Monitor, and Patient Record Flag Detector—leverage statistical and machine learning methods to monitor workflow disruptions, detect anomalies in care sequences and volumes, identify bottlenecks, and track system-level performance metrics across VistA and Millennium systems. All detectors have been integrated into the Health Data Analytics Platform (HDAP), with most having completed deployment and testing using live data from targeted stations in cardiology and oncology domains. This work enhances VA’s capacity for proactive system surveillance, promotes patient safety, and informs data-driven operational improvements across the EHR ecosystem.

97 MATHEMATICS AND COMPUTING↗

Cinnamon essential oil vapor alleviates the reduction of aroma-related volatiles in cold-stored “Feicheng” peach using HS-GC-IMS

“Feicheng” peach is popular for its unique aroma, but its defect of being highly sensitive to chilling injury (CI) often leads to aroma loss and internal browning. Essential oils (EOs) are often used to enhance the antioxidant capacity of plants and fruits, as well as to trigger their defense against biotic/abiotic stresses. This study aimed to examine the effect of cinnamon essential oil (CEO) vapor treatment on the aroma quality of peach fruit during cold storage using HS-GC-IMS. The results showed that 50 μL/L CEO vapor reduced the severity of internal browning (IB) in peaches at the stage of 7 ~ 21 d during refrigeration (Significantly, the L * value was higher and the IB index was lower than that of control, p < 0.05). Meanwhile, the evident reduction or loss of aroma content caused by CI was restored to a higher level than the control ( p < 0.05). Furthermore, CEO treatment promoted the release of aroma-related volatiles as evidenced by more propyl acetate, and the dimer of amyl acetate, isoamyl acetate, butyl acetate detected than that on harvest day and no-treated group after 21 d of cold storage plus 2 d of shelf life. Genes of PpLOX1 , PpLOX2 , PpHPL1 and PpADH1 associated with aroma-related volatile biosynthesis revealed higher transcript abundance in peach fruits treated with CEO than the control ( p < 0.05). Overall, our study demonstrated that CEO in vapor phase may be beneficial to alleviate the quality deterioration in aroma and flesh color of “Feicheng” peaches caused by CI, which lays a theoretical reference for maintaining postharvest quality of peach fruits.

Wang, Dan↗

Piezoelectric Energy Harvesting Gyroscopes: Comparative Modeling and Effectiveness

Given its versatility in drawing power from many sources in the natural world, piezoelectric energy harvesting (PEH) has become increasingly popular. However, its energy harvesting capacities could be enhanced further. Here, a mathematical model that accurately simulates the dynamic behavior and energy harvested can facilitate further improvements in the performance of piezoelectric devices. One of the goals of this study is to create a dependable reduced-order model of a multi-purpose gyroscope. This model will make it possible to compute the harvested voltage and electrical power in a semi-analytical manner. The harvested voltage is often modeled as an average value across the whole electrode surface in piezoelectric devices. We propose a model which provides practical insights toward optimizing the performance of the system by considering a spatially varying electric field across the electrode surface length. Our framework allows investigation of the limits of applicability of the modeling assumptions across a range of load resistances. The differential quadrature method (DQM) provides the basis for the suggested numerical solution. The model is also employed to examine energy harvesting under various resistance loads. The newly developed spatially varying model is evaluated for open- and closed-circuit conditions and is proved to be accurate for various values of load resistance that have not previously been considered. The results show that using a spatially varying model is more versatile when modeling the performance of the piezoelectric multifunctional energy harvester. The performance may be accurately captured by the model for load resistances ranging between 103 Ω and 108 Ω. At optimum load resistance and near 65 KHz, the maximum power output predicted by the spatially varying (SV) model is 1.3 mV, 1.5 mV for the open-circuit (OC) model, and 2.1 mV for the closed circuit (CE) model. At a high-load resistance, the SV and OC models all predict the maximum power output to be 1.9 mV while the CE model predicted the maximum voltage to be 3 mV.

42 ENGINEERING↗

Extending a land-surface model with <i>Sphagnum</i> moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO<sub>2</sub>

Abstract. Mosses need to be incorporated into Earth system models to better simulate peatland functional dynamics under the changing environment. Sphagnum mosses are strong determinants of nutrient, carbon, and water cycling in peatland ecosystems. However, most land-surface models do not include Sphagnum or other mosses as represented plant functional types (PFTs), thereby limiting predictive assessment of peatland responses to environmental change. In this study, we introduce a moss PFT into the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. The model was parameterized and independently evaluated against observations from an ombrotrophic forested bog as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) project. The inclusion of a Sphagnum PFT with some Sphagnum-specific processes in ELM allows it to capture the observed seasonal dynamics of Sphagnum gross primary production (GPP) albeit with an underestimate of peak GPP. The model simulated a reasonable annual net primary production (NPP) for moss but with less interannual variation than observed, and it reproduced aboveground biomass for tree PFTs and stem biomass for shrubs. Different species showed highly variable warming responses under both ambient and elevated atmospheric CO2 concentrations, and elevated CO2 altered the warming response direction for the peatland ecosystem. Microtopography is critical: Sphagnum mosses on hummocks and hollows were simulated to show opposite warming responses (NPP decreasing with warming on hummocks but increasing in hollows), and hummock Sphagnum was modeled to have a strong dependence on water table height. The inclusion of this new moss PFT in global ELM simulations may provide a useful foundation for the investigation of northern peatland carbon exchange, enhancing the predictive capacity of carbon dynamics across the regional and global scales.

54 ENVIRONMENTAL SCIENCES↗

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

Numerical Investigation of Two-Stage Vapor Compression System with Simultaneous Vapor and Liquid Injection

Two-stage vapor compression systems can be advantageous over single-stage systems by providing improved system performance, lower discharge temperature and reduced throttling losses. These systems employ various intermediate configurations, such as liquid injection and vapor injection. This paper presents a configuration for a R1234ze(E) two-stage air-conditioning system using a turbo compressor with two injection ports, one for vapor injection and the second for liquid injection. The liquid injection is used to cool the motor and electronics. A component-based representation and solution approach was used to simulate the two-stage compression system with simultaneous vapor and liquid injection at steady state. The turbo compressor was represented using a customized performance map. The condenser and the evaporator were modeled using finite-volume approach. A parametric study was conducted to assess the impact of the following three variables on the system performance: vapor injection ratio, condenser air flow rate, and discharge pipe pressure drop. The simulation results show that as the vapor injection ratio increased, the system performance undergoes a tradeoff between an enhanced subcooling effect (and thus enhanced unit refrigeration capacity) and a decreased suction mass flow rate. Maximum COP occurs when the vapor injection ratio was 0.1. The results also show that as the condenser air flow rate increased, both the capacity and power consumption (including fan power) increased monotonically, and COP increased first and then decreased. At 75% load, the COP improvement at the optimum flow rate was marginally less than 0.5%. Lastly, higher discharge pipe pressure drop increased the discharge pressure. It showed very small effect on the overall system performance at the condition selected for the current study.

component-based steady-state simulation↗

Enhanced magnetocaloric performance in manganite bilayers

Bilayer films of La 0.8 Sr 0.2 MnO 3 and La 0.7 Ca 0.3 MnO 3 with different layer thicknesses and stacking sequences were synthesized via pulsed laser deposition. The magnetic properties and magnetocaloric effects were systematically investigated. We found that the phase transition associated with the layers tends to merge together at an optimal thickness and a stacking sequence. The operating temperature span of the entropy change broadens at the expense of its magnitude, leading to an enhancement of the refrigerant capacity by over 40%. The optimized bilayer film possesses a refrigerant capacity of ~6.0J/kg, compared to a value of ~4.2J/kg for the single-phase films. The phase transition broadening induced by epitaxial strain is responsible for the enhanced window of operating temperature as well as refrigerant capacity. Finally, the design principle developed here may be applied to ferroelastic and ferroelectric materials to enhance elastocaloric and electrocaloric effects.

36 MATERIALS SCIENCE↗

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Distributed PV Hosting Capacity Evaluation Considering Equitable PV Accommodation

Distributed photovoltaic (DPV) hosting capacity is widely used by distribution system operators to evaluate how much DPV the distribution networks can accommodate without violating operational constraints. If the proliferation of DPV deployment is appropriately managed, it offers an excellent opportunity to mitigate the energy inequity issue in electric grids. Hosting capacity improvement plans that neglect energy equity can exacerbate unequal DPV access. To consider energy equity in distribution network planning to enhance DPV accommodation, hosting capacity evaluations should be improved to consider equity constraints endogenously. This paper proposes a DPV hosting capacity evaluation method that considers equitable DPV access among sub-regions of a distribution feeder partitioned by socioeconomic indicators, such as income level. The results demonstrate that considering equity in DPV hosting capacity evaluations can provide a valuable reference in the equitable energy transition. This work provides guidance for future distribution network upgrade planning for equitable DPV deployment.

distributed PV↗

Revolutionizing Lithium Storage Capabilities in TiO 2 by Expanding the Redox Range

TiO 2 is a widely recognized intercalation anode material for lithium-ion batteries (LIBs), yet its practical capacity is kinetically constrained due to sluggish lithium-ion diffusion, leading to a lithiation number of less than 1.0 Li + (336 mAh g -1 ). Here, the growth of TiO 2 crystallites is restrained by integrating Si into the TiO 2 framework, thereby enhancing the charge transfer and creating additional active sites potentially residing at grain boundaries for Li + storage. This strategy is corroborated by the expanded redox range of Ti, as thoroughly demonstrated via synchrotron radiation-based X-ray spectroscopy and Cs-corrected electron microscopy. Consequently, when deployed for lithium storage, the tailored material achieves an extraordinarily high reversible capacity of 559 mAh g -1 , 116% of the theoretical maximum of 483 mAh g -1 calculated based on all active species, while simultaneously retaining superior rate capability and robust cycling stability. Further, this work offers fresh perspectives on the revitalization of traditional electrode materials to achieve enhanced capacities.

25 ENERGY STORAGE↗

In vitro enhancement of Zika virus infection by preexisting West Nile virus antibodies in human plasma-derived immunoglobulins revealed after P2 binding site-specific enrichment

ABSTRACT Human immunoglobulin preparations contain a diverse range of polyclonal antibodies that reflect past immune responses against pathogens encountered by the blood donor population. In this study, we examined a panel of intravenous immunoglobulins (IGIVs) manufactured over the past two decades (1998–2020) for their capacity to neutralize or enhance Zika virus (ZIKV) infectionin vitro. These IGIVs were selected specifically based on their production dates in relation to the occurrences of two flavivirus outbreaks in the U.S.: the West Nile virus (WNV) outbreak in 1999 and the ZIKV outbreak in 2015. As demonstrated by enzyme-linked immunosorbent assay (ELISA) experiments, IGIVs made before the ZIKV outbreak already harbored antibodies that bind to various peptides across the envelope protein of ZIKV because of the WNV outbreak. Using phage display, the most dominant binding site was mapped precisely to the P2 peptide between residues 211 and 230 within domain II, where BF1176-56, an anti-ZIKV monoclonal antibody, also binds. When tested in permissive Vero E6 cells for ZIKV neutralization, the IGIVs, even after undergoing rigorous enrichment for P2 binding specificity, failed, as did BF1176-56. Meanwhile, BF1176-56 enhanced ZIKV infection in both FcγRII-expressing K562 cells and human peripheral blood mononuclear cells. However, for enhancement by the IGIVs to be detected in these cells, a substantial increase in their P2 binding specificity was required, thus linking the P2 site with ZIKV enhancementin vitro. Our findings warrant further study of the significance of elevated levels of anti-WNV antibodies in IGIVs, considering that various mechanisms operatingin vivomay modulate ZIKV infection outcomes. IMPORTANCE We investigated the capacity of intravenous immunoglobulins manufactured previously over two decades (1998–2020) to neutralize or enhance Zika virus infectionin vitro. West Nile virus antibodies in IGIVs could not neutralize Zika virus initially; however, once the IGIVs were concentrated further, they enhanced its infection. These findings lay the groundwork for exploring how preexisting WNV antibodies in IGIVs could impact Zika infection, bothin vitroandin vivo. Our observations are historically significant, since we tested a panel of IGIV lots that were carefully selected based on their production dates which covered two major flavivirus outbreaks in the U.S.: the WNV outbreak in 1999 and the ZIKV outbreak in 2015. These findings will facilitate our understanding of the interplay among closely related viral pathogens, particularly from a historical perspective regarding large blood donor populations. They should remain relevant for future outbreaks of emerging flaviviruses that may potentially affect vulnerable populations.

Microbiology↗

Sparse chronology strategy for integrating seasonal energy storage in capacity expansion models

Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Composition Dependent Electrochemical Properties of Earth-Abundant Ternary Nitride Anodes

Growing energy storage demands on lithium-ion batteries necessitate exploration of new electrochemical materials as next-generation battery electrode materials. In this work, we investigate the previously unexplored electrochemical properties of earth-abundant and tunable Zn 1-x Sn 1+x N 2 (x = -0.4 to x = 0.4) thin films, which show high electrical conductivity and high gravimetric capacity for Li insertion. Enhanced cycling performance is achieved compared to previously published end-members Zn 3 N 2 and Sn 3 N 4 , showing decreased irreversible loss and increased total capacity and cycle stability. The average reversible capacity observed is >1050 mAh/g for all compositions and 1220 mAh/g for Zn-poor (x = 0.2) films. Extremely Zn-rich films (x = -0.4) show improved adhesion; however, Zn-rich films undergo a phase transformation on the first cycle. Zn-poor and stoichiometric films do not exhibit significant phase transformations which often plague nitride materials and show no required overpotential at the 0.5 V plateau. Cation composition x is explored as a mechanism for tuning relevant mechanical and electrochemical properties, such as capacity, overpotential, phase transformation, electrical conductivity, and adhesion. The lithiation/delithiation experiments confirm the reversible electrochemical reactions. Without any binding additives, the as-deposited electrodes delaminate resulting in fast capacity degradation. We demonstrate the mechanical nature of this degradation through decreased electrode thinning, resulting in cells with improved cycling stability due to increased mechanical stability. Combining composition and electrochemical analysis, this work demonstrates for the first time composition dependent electrochemical properties for the ternary Zn 1-x Sn 1+x N 2 and proposes earth-abundant ternary nitride anodes for increased reversible capacity and cycling stability.

25 ENERGY STORAGE↗

3D printed Mg-NiTi interpenetrating-phase composites with high strength, damping capacity, and energy absorption efficiency

It is of significance, but still remains a key challenge, to simultaneously enhance the strength and damping capacities in metals, as these two properties are often mutually exclusive. Here, we provide a multidesign strategy for defeating such a conflict by developing a Mg-NiTi composite with a bicontinuous interpenetrating-phase architecture through infiltration of magnesium melt into three-dimensionally printed Nitinol scaffold. The composite exhibits a unique combination of mechanical properties with improved strengths at ambient to elevated temperatures, remarkable damage tolerance, good damping capacities at differing amplitudes, and exceptional energy absorption efficiency, which is unprecedented for magnesium materials. The shape and strength after deformation can even be largely recovered by heat treatment. This study offers a new perspective for the structural and biomedical applications of magnesium.

36 MATERIALS SCIENCE↗

Enhancing sorption kinetics by oriented and single crystalline array-structured ZSM-5 film on monoliths

Abstract To enhance the reaction kinetics without sacrificing activity in porous materials, one potential solution is to utilize the anisotropic distribution of pores and channels besides enriching active centers at the reactive surfaces. Herein, by designing a unique distribution of oriented pores and single crystalline array structures in the presence of abundant acid sites as demonstrated in the ZSM-5 nanorod arrays grown on monoliths, both enhanced dynamics and improved capacity are exhibited simultaneously in propene capture at low temperature within a short duration. Meanwhile, the ZSM-5 array also helps mitigate the long-chain HCs and coking formation due to the enhanced diffusion of reactants in and reaction products out of the array structures. Further integrating the ZSM-5 array with Co 3 O 4 nanoarray enables comprehensive propene removal throughout a wider temperature range. The array structured film design could offer energy-efficient solutions to overcome both sorption and reaction kinetic restrictions in various solid porous materials for various energy and chemical transformation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗