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At least 505 records · Page 28

Inelastic Deformation in Methylammonium Lead Iodide Perovskite and Mitigation by Additives during Thermal Cycling

Metal halide perovskite thin films are promising materials for next-generation photovoltaic applications, but the thermomechanical instabilities of these materials are critical barriers to device longevity. In this study, we measure the evolution of stresses in methylammonium lead iodide (MAPbI3) films thermally cycled from 25 to 105 °C using a multibeam optical stress sensor (MOSS) system. We demonstrate that these films undergo residual stress buildup due to inelastic deformation as well as a simple mitigation strategy by incorporating low concentrations of 5-aminovaleric acid hydrochloride (5-AVACl) as an additive. Adding 5-AVACl increases the tensile stresses measured at room temperature but beneficially decreases the biaxial modulus from 9.60 ± 0.44 GPa to 7.95 ± 0.55 GPa, resulting in greater accommodation of thermal stresses. The hysteresis loop is ~63% smaller with the inclusion of 5-AVACl, and the stress relaxation at 50 °C decreases from 86.46 to 51.49 MPa. The larger stress relaxation in pristine MAPbI 3 is correlated with grain boundary opening after five cycles, while the inclusion of 5-AVACl mitigates this degradation. Furthermore, our findings underscore the importance of studying the dynamic response of perovskite films during thermal cycling and lay the foundation for further exploration into the mechanisms governing the thermomechanical behavior of perovskite thin films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mitigating Hydrogen-Induced Degradation of Iridium Anodes in Proton Exchange Membrane Water Electrolyzers

One promising method for reducing precious metal usage in proton exchange membrane water electrolysis is lowering iridium (Ir) loading at the anode. However, low-loading Ir catalysts often suffer from poor stability under high current densities. In this study, hydrogen (H2) crossover from the cathode to the anode is identified as a key degradation pathway. Temperature-programmed reduction confirms the reduction of IrO2 at 80 °C in a hydrogen environment, highlighting the vulnerability of IrO2-based catalysts to H2 exposure. To mitigate this effect, palladium (Pd) is introduced as an anode additive, acting as an H2 oxidation catalyst and mitigating IrO2 reduction. This protective role is verified by inductively coupled plasma optical emission spectroscopy and in situ X-ray absorption spectroscopy, showing significantly suppressed Ir dissolution at 80 °C under H2 flow when an O-covered Pd surface is present at oxygen evolution reaction potentials. Results from the current study identify a new strategy in improving activity and durability of catalysts in electrolyzers.

58 GEOSCIENCES↗

Spacecraft-charging mitigation of a high-power electron beam emitted by a magnetospheric spacecraft: Simple theoretical model for the transient of the spacecraft potential

A spacecraft-charging mitigation scheme necessary for the operation of a high-power electron beam in the low-density magnetosphere is analyzed. The scheme is based on a plasma contactor, i.e. a high-density charge-neutral plasma emitted prior to and during beam emission, and its ability to emit high ion currents without strong space-charge limitations. A simple theoretical model for the transient of the spacecraft potential and contactor expansion during beam emission is presented. The model focuses on the contactor ion dynamics and is valid in the limit when the ion contactor current is equal to the beam current. The model is found in very good agreement with Particle-In-Cell simulations over a large parametric study that varies the initial expansion time of the contactor, the contactor current and the ion mass. The model highlights the physics of the spacecraft-charging mitigation scheme, indicating that the most important part of the dynamics is the evolution of the outermost ion front which is pushed away by the charge accumulated in the system by the beam. The model can be also used to estimate the long-time evolution of the spacecraft potential. For a short contactor expansion (0.3 or 0.6 ms Helium plasma or 0.8 ms Argon plasma, both with 1 mA current) it yields a peak spacecraft potential of the order of 1-3 kV. This implies that a 1-mA relativistic electron beam would be easily emitted by the spacecraft.

79 ASTRONOMY AND ASTROPHYSICS↗

Different Strategies of Stratospheric Aerosol Injection Would Significantly Affect Climate Extreme Mitigation

Abstract Stratospheric aerosol injection (SAI) has been proposed as a potential supplement to mitigate some climate impacts of anthropogenic warming. Using Community Earth System Model ensemble simulation results, we analyze the response of temperature and precipitation extremes to two different SAI strategies: one injects SO 2 at the equator to stabilize global mean temperature and the other injects SO 2 at multiple locations to stabilize global mean temperature as well as the interhemispheric and equator‐to‐pole temperature gradients. Our analysis shows that in the late 21st century, compared with the present‐day climate, both equatorial and multi‐location injection lead to reduced hot extremes in the tropics, corresponding to overcooling of the mean climate state. In mid‐to‐high latitude regions, in comparison to the present‐day climate, substantial decreases in cold extremes are observed under both equatorial and multi‐location injection, corresponding to residual winter warming of the mean climate state. Both equatorial and multi‐location injection reduce precipitation extremes in the tropics below the present‐day level, associated with the decrease in mean precipitation. Overall, for most regions, temperature and precipitation extremes show reduced change in response to multi‐location injection than to equatorial injection, corresponding to reduced mean climate change for multi‐location injection. In comparison with equatorial injection, in response to multi‐location injection, most land regions experience fewer years with significant change in cold extremes from the present‐day level, and most tropical regions experience fewer years with significant change in hot extremes. The design of SAI strategies to mitigate anthropogenic climate extremes merits further study.

54 ENVIRONMENTAL SCIENCES↗

Earlier emergence of a temperature response to mitigation by filtering annual variability

The rate of global surface warming is crucial for tracking progress towards global climate targets, but is strongly influenced by interannual-to-decadal variability, which precludes rapid detection of the temperature response to emission mitigation. Here we use a physics based Green’s function approach to filter out modulations to global mean surface temperature from sea-surface temperature (SST) patterns, and show that it results in an earlier emergence of a response to strong emissions mitigation. For observed temperatures, we find a filtered 2011–2020 surface warming rate of 0.24 °C per decade, consistent with long-term trends. Unfiltered observations show 0.35 °C per decade, partly due to the El Nino of 2015–2016. Pattern filtered warming rates can become a strong tool for the climate community to inform policy makers and stakeholder communities about the ongoing and expected climate responses to emission reductions, provided an effort is made to improve and validate standardized Green’s functions.

58 GEOSCIENCES↗

Environmental trade-offs of direct air capture technologies in climate change mitigation toward 2100

Abstract Direct air capture (DAC) is critical for achieving stringent climate targets, yet the environmental implications of its large-scale deployment have not been evaluated in this context. Performing a prospective life cycle assessment for two promising technologies in a series of climate change mitigation scenarios, we find that electricity sector decarbonization and DAC technology improvements are both indispensable to avoid environmental problem-shifting. Decarbonizing the electricity sector improves the sequestration efficiency, but also increases the terrestrial ecotoxicity and metal depletion levels per tonne of CO 2 sequestered via DAC. These increases can be reduced by improvements in DAC material and energy use efficiencies. DAC exhibits regional environmental impact variations, highlighting the importance of smart siting related to energy system planning and integration. DAC deployment aids the achievement of long-term climate targets, its environmental and climate performance however depend on sectoral mitigation actions, and thus should not suggest a relaxation of sectoral decarbonization targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multicationic interactions mitigating lattice strain in sodium layered cathodes

Transition-metal (TM) layered oxides have emerged as the primary cathode choice for sodium-ion batteries (SIBs) due to their high energy density and sustainable chemistry using non-critical elements. However, their anisotropic lattice strain and stress accumulation during (de)sodiation lead to severe structural degradation, yet an intrinsic strain-depressant approach remains elusive. Herein, we propose entropy regulation with zero Li/Co usage to mitigate harmful lattice displacements and enhance the electrochemical performance of sodium layered cathodes. Our findings demonstrate that high entropy design effectively inhibits TMO 6 octahedra distortions upon cycling, as evidenced by hard X-ray absorption spectroscopy, greatly reducing near-surface structural deconstruction and interface side reactions. Furthermore, multicationic interactions driven by configurational entropy thermodynamically mitigate the formation of oxygen defects and strengthen ligand-to-metal coordination. The complementarity inherent in charge compensation within complex systems is unveiled and the restrained lattice parameters deviations without interior volume residuals are successfully achieved. As a result, the multicationic cathode exhibits improved cycling stability and Na + diffusion kinetics in both half and full cells. The cathode chemistries outlined here broaden the prospects for lattice engineering to alleviate bulk fatigue and open up the possibility to develop an economically viable layered oxides with long durability.

Wang, Haoji [Central South University, Changsha (C↗

Group-theoretic error mitigation enabled by classical shadows and symmetries

Abstract Estimating expectation values is a key subroutine in quantum algorithms. Near-term implementations face two major challenges: a limited number of samples required to learn a large collection of observables, and the accumulation of errors in devices without quantum error correction. To address these challenges simultaneously, we develop a quantum error-mitigation strategy called symmetry-adjusted classical shadows , by adjusting classical-shadow tomography according to how symmetries are corrupted by device errors. As a concrete example, we highlight global U(1) symmetry, which manifests in fermions as particle number and in spins as total magnetization, and illustrate their group-theoretic unification with respective classical-shadow protocols. We establish rigorous sampling bounds under readout errors obeying minimal assumptions, and perform numerical experiments with a more comprehensive model of gate-level errors derived from existing quantum processors. Our results reveal symmetry-adjusted classical shadows as a low-cost strategy to mitigate errors from noisy quantum experiments in the ubiquitous presence of symmetry.

Zhao, Andrew (ORCID:0000000202990277)↗

Mitigation of hydrogen crossover in liquid alkaline water electrolysers using gas recombination catalysts

The rising demand for hydrogen calls for improvements in the efficiency of liquid alkaline water electrolysers (LAWEs), which can be fulfilled by advanced electrodes or separators. Nevertheless, they also intensify hydrogen crossover and safety concerns, thus mandating efficient mitigation strategies. Here we studied the correlation between cathodes and hydrogen crossover behaviours and mitigated safety risks by designing a gas recombination catalyst (GRC). We attribute the elevated hydrogen crossover associated with platinum-based cathodes to their preferential utilization for the hydrogen evolution reaction that creates elevated hydrogen supersaturation, as evidenced by direct measurements of dissolved hydrogen concentration. Varying the placement of platinum layers relative to the cathode–separator interface also supports this conclusion. The implementation of a GRC reduces hydrogen crossover by 95% without affecting LAWE performance and functions for over 1,000 h at 1 A cm−2. This study provides insights into hydrogen supersaturation and the crossover mechanism, as well as offering a promising pathway to enhance the efficiency and reliability of alkaline water electrolysis.

Liu, Haotian↗

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗

Pathways for mitigating thermal losses in solar photovoltaics

Abstract To improve the performance of solar photovoltaic devices one should mitigate three types of losses: optical, electrical and thermal. However, further reducing the optical and electrical losses in modern photovoltaic devices is becoming increasingly costly. Therefore, there is a rising interest in minimizing the thermal losses. These correspond to the reduction in electrical power output resultant of working at temperatures above 25 °C and the associated accelerated aging. Here, we quantify the impact of all possible strategies to mitigate thermal losses in the case of the mainstream crystalline silicon technology. Results indicate that ensuring a minimum level of conductive/convective cooling capabilities is essential. We show that sub-bandgap reflection and radiative cooling are strategies worth pursuing and recommend further field testing in real-time operating conditions. The general method we propose is suitable for every photovoltaic technology to guide the research focused on reducing thermal losses.

14 SOLAR ENERGY↗

Quantum error mitigation by Pauli check sandwiching

Abstract We describe and analyze an error mitigation technique that uses multiple pairs of parity checks to detect the presence of errors. Each pair of checks uses one ancilla qubit to detect a component of the error operator and represents one layer of the technique. We build on the results on extended flag gadgets and put it on a firm theoretical foundation. We prove that this technique can recover the noiseless state under the assumption of noise not affecting the checks. The method does not incur any encoding overhead and instead chooses the checks based on the input circuit. We provide an algorithm for obtaining such checks for an arbitrary target circuit. Since the method applies to any circuit and input state, it can be easily combined with other error mitigation techniques. We evaluate the performance of the proposed methods using extensive numerical simulations on 1850 random input circuits composed of Clifford gates and non-Clifford single-qubit rotations, a class of circuits encompassing most commonly considered variational algorithm circuits. We observe average improvements in fidelity of 34 percentage points with six layers of checks.

97 MATHEMATICS AND COMPUTING↗

A hidden demethylation pathway removes mercury from rice plants and mitigates mercury flux to food chains

Dietary exposure to methylmercury (MeHg) causes irreversible damage to human cognition and is mitigated by photolysis and microbial demethylation of MeHg. Rice (Oryza sativa L.) has been identified as a major dietary source of MeHg. However, it remains unknown what drives the process within plants for MeHg to make its way from soils to rice and the subsequent human dietary exposure to Hg. Here we report a hidden pathway of MeHg demethylation independent of light and microorganisms in rice plants. This natural pathway is driven by reactive oxygen species generated in vivo, rapidly transforming MeHg to inorganic Hg and then eliminating Hg from plants as gaseous Hg°. MeHg concentrations in rice grains would increase by 2.4- to 4.7-fold without this pathway, which equates to intelligence quotient losses of 0.01–0.51 points per newborn in major rice-consuming countries, corresponding to annual economic losses of US$30.7–84.2 billion globally. Importantly, this discovered pathway effectively removes Hg from human food webs, playing an important role in exposure mitigation and global Hg cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation

Widespread expansion of agriculture and forestry has altered the surface of the Earth, the composition of the atmosphere, and as a result, the climate. Here we quantify the radiative forcing caused by the historical deforestation of an ecoregion in the U.S. Upper Midwest and the adoption of eight nature-based climate solutions. We combined regional forest inventory data with over three decades of remote sensing and in situ data from a replicated land use change experiment. Deforestation of the region caused net global warming (1626 ± 44 µW m -2 ), mainly from the 76 % reduction of ecosystem carbon stocks, but also from the 84 % reduction of the soil methane sink and the 115 % increase in soil nitrous oxide emissions. The associated albedo increase offset 24 % of this greenhouse gas induced warming. For the adoption of nature-based climate solutions, we found that conservation agriculture can provide -39 to -76 ± 31 µW m -2 of climate mitigation over a 100-year time period while short/medium length forestry rotations can provide more at -296 to -881 ± 44 µW m -2 and natural forest regeneration can provide the most at -1555 ± 44 µW m -2 . As the impacts of climate change on nature and society intensify, consideration should be given to the climate mitigation, habitat, and ecosystem services that nature-based climate solutions can provide.

54 ENVIRONMENTAL SCIENCES↗

Mitigating mechanical failure of crystalline silicon electrodes for lithium batteries by morphological design [Morphological design of silicon electrode with anisotropic interface reaction rate for lithium ion batteries]

Although crystalline silicon (c-Si) anodes promise very high energy densities in Li-ion batteries, their practical use is complicated by amorphization, large volume expansion and severe plastic deformation upon lithium insertion. Recent experiments have revealed the existence of a sharp interface between crystalline Si (c-Si) and the amorphous Li x Si alloy during lithiation, which propagates with a velocity that is orientation dependent; the resulting anisotropic swelling generates substantial strain concentrations that initiate cracks even in nanostructured Si. Here we describe a novel strategy to mitigate lithiation-induced fracture by using pristine c-Si structures with engineered anisometric morphologies that are deliberately designed to counteract the anisotropy in the crystalline/amorphous interface velocity. This produces a much more uniform volume expansion, significantly reducing strain concentration. Based on a new, validated methodology that improves previous models of anisotropic swelling of c-Si, we propose optimal morphological designs for c-Si pillars and particles. The advantages of the new morphologies are clearly demonstrated by mesoscale simulations and verified by experiments on engineered c-Si micropillars. The results of this study illustrate that morphological design is effective in improving the fracture resistance of micron-sized Si electrodes, which will facilitate their practical application in next-generation Li-ion batteries. In conclusion, the model and design approach present in this paper also have general implications for the study and mitigation of mechanical failure of electrode materials that undergo large anisotropic volume change upon ion insertion and extraction.

25 ENERGY STORAGE↗

Dispersive shell pellet injection modeling and validation for DIII-D disruption mitigation

Dispersive shell pellet injection for disruption mitigation on the DIII-D tokamak is modeled with the 3D MHD code NIMROD. The simulations attempt to reproduce as closely as possible a pellet velocity scan that was performed on the DIII-D tokamak [Hollmann, et al., Phys. Rev. Lett. 122, 65001 (2019)]. This scan involved injecting a hollow diamond shell filled with boron dust that is released in the core of the plasma. Trends that are reproduced in the simulation include improved mitigation, reduced plasma current spike amplitude, and increased likelihood of hot-tail runaway electron production with increased pellet speed. The simulations provide additional physics insight into these findings. Limitations of the present model and requirements for a predictive model are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An investigation of shock formation vs shock mitigation of colliding plasma jets

Here, this work studies the interaction between colliding plasma jets to understand regimes in which jet merging results in shock formation vs regimes in which the shock formation is mitigated due to the collisionless interpenetration of the jets. A kinetic model is required for this study because fluid models will always produce a shock upon the collision of plasma jets. The continuum-kinetic, Vlasov–Maxwell–Dougherty model with one velocity dimension is used to accurately capture shock heating, along with a novel coupling with a moment equation to evolve perpendicular temperature for computational efficiency. As a result, this relatively inexpensive simulation can be used for detailed scans of the parameter space toward predictions of shocked vs shock-mitigated regimes, which is of interest for several fusion concepts such as plasma-jet-driven magneto-inertial fusion, high-energy-density plasmas, astrophysical phenomena, and other laboratory plasmas. The initial results obtained using this approach are in agreement with the preliminary outcomes of the plasma liner experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗