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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Performance Improvements for the Griffin Transport Solvers

Griffin is a Multiphysics Object-Oriented Simulation Environment based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. Griffin includes a variety of deterministic radiation transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. A code assessment performed in FY-20 identified two significant issues with the transport solvers in Griffin: first, the primary heterogeneous SN (discrete ordinates) transport solver based on continuous finite element methods required significant mesh refinement and higher memory usage compared to solvers based on the method of characteristic for equivalent accuracy. Second, the homogeneous PN (spherical harmonics expansion) transport solver did not adequately support polynomial refinement, which is a feature usually required for problems with spatial homogenization and pronounced streaming, typical in fast or gas-cooled reactor systems. To address the first issue, the development effort focused on the more promising discontinuous finite element method (DFEM)-based SN transport solver in Griffin. The addition of an asynchronous parallel transport sweeper and coarse mesh finite difference (CMFD) acceleration have rendered a superior heterogeneous SN transport capability for multiphysics problems that requires far less computing resources in terms of both CPU time and memory usage. This is demonstrated with typical thermal- and fast-spectrum reactor benchmark problems, including 2D Transient Reactor Test, 3D Advanced Burner Test Reactor (ABTR), and 2D and 3D Empire microreactor. For the second issue, the development effort focused on a new transport solver based on the hybrid finite element PN method (HFEM-PN), equivalent to the variational nodal method, as well as a new diffusion solver based on HFEM-Diffusion. This solver is intended for homogenized domains with multiphysics coupling (i.e., supports mesh displacement, seamless temperature feedback, etc.). Initial calculations with the HFEM-Diffusion implementation show very good parallel efficiency for the residual evaluations with the 2D ABTR benchmark. A future development effort will be centered on further improvements to the CMFD, HFEM-PN, and DFEM diffusion solvers to ensure Griffin meets performance and software quality assurance requirements for advanced reactor design and analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Dataset for "FLEXPART-WRF simulations to assess dust transport in the convective boundary layer at the Southern Great Plains site"

Soil dusts are an important source of aerosol in agricultural regions and can affect the Earth’s radiation budget through the modification of cloud properties, and in particular, through their ability to act as ice nucleating particles. In order to impact cloud properties, agricultural soil dusts need to be transported from the point of emission to cloud-relevant altitudes. Vertical transport within the planetary boundary layer is strongly controlled by turbulence and is challenging to represent accurately in regional and global models. Large-eddy simulations (LES) are run at resolutions capable of resolving most of the turbulent energy directly and can thus better simulate vertical transport. In this study, we leverage the LES ARM Symbiotic Simulation and Observation (LASSO) large-eddy simulations to simulate vertical transport of agricultural dust within the turbulent boundary layer using a modified version of the stochastic dispersion model FLEXPART-WRF. We find that the modified model is better capable of simulating particle transport due to turbulence, and that particle size was the greatest factor in determining particle lifetime. Individual meteorology and particle density had intermediate effects upon particle transport, while release height had little effect upon simulation results. Finally, we utilize a quasi-single column model (QSCM) approach to determine how our results compare to a parameterized treatment of turbulence. The QSCM simulations led to greater tracer transport out of the boundary layer, with ramifications for any studies utilizing a Lagrangian stochastic model to understand tracer dispersion. These results highlight the importance of accurately simulating turbulence for understanding particle transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

TSDC: Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center is a centralized repository for high-resolution transportation data from hundreds of travel and transit surveys and studies. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. It houses surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Meanwhile, the Livewire Data Platform empowers research, industry, and academic partners to easily and securely preserve, maintain, share, discover, and gain access to transportation and mobility data. Livewire accommodates a range of datasets, including behavioral, experimental, model, analytical, and raw data at the vehicle, traveler, and system levels. Datasets support mobility research and planning spanning urban science, connected and automated vehicles, fueling and charging infrastructure, mobility decision science, multimodal transportation, vehicle efficiency, and more.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Quantifying subsurface parameter and transport uncertainty using surrogate modelling and environmental tracers

Here, we combine physics-based groundwater reactive transport modelling with machine-learning techniques to quantify hydrogeological model and solute transport predictive uncertainties. We train an artificial neural network (ANN) on a dataset of groundwater hydraulic heads and 3 H concentrations generated using a high-fidelity groundwater reactive transport model. Using the trained ANN as a surrogate model to reproduce the input–output response of the high-fidelity reactive transport model, we quantify the posterior distributions of hydrogeological parameters and hydraulic forcing conditions using Markov chain Monte Carlo calibration against field observations of groundwater hydraulic heads and 3 H concentrations. We demonstrate the methodology with a model application that predicts Chlorofluorocarbon-12 (CFC-12) solute transport at a contaminated field site in Wyoming, United States. Our results show that including 3 H observations in the calibration dataset reduced the uncertainty in the estimated permeability field and infiltration rates, compared to calibration against hydraulic heads alone. However, predictive uncertainty quantification shows that CFC-12 transport predictions conditioned to the parameter posterior distributions cannot reproduce the field measurements. We found that calibrating the model to hydraulic head and 3 H observations results in groundwater mean ages that are too large to explain the observed CFC-12 concentrations. The coupling of the physics-based reactive transport model with the machine-learning surrogate model allows us to efficiently quantify model parameter and predictive uncertainties, which is typically computationally intractable using reactive transport models alone.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling of transport in carrier-selective contacts in silicon heterojunction solar cells

High-performance silicon heterojunction (SHJ) solar cells use carrier-selective contact structures based on hydrogentated amorphous Si (a-Si:H) to maximize collection of photogenerated carriers. The high open circuit voltages observed experimentally in SHJ cells require that the carrier-selective contacts provide selectivity and passivation. However, a microscopic understanding of the dynamics of carrier transport through the a-Si layer is currently lacking. In this paper, we explicitly simulate the transport of holes across the a-Si:H(i) layer using a novel kinetic Monte Carlo approach. The hole-selective contact structure investigated in this paper uses p-type doped a-Si:H(p) and intrinsic a-Si:H(i) on an n-type crystalline silicon wafer, where the selectivity is provided by the a-Si:H(p) and the passivation is provided by the a-Si:H(i). However, in addition to the passivation provided by the a-Si:H(i), this layer also creates a potential barrier to the collection of photogenerated holes. There have been experimental studies in the literature that have suggested that multi-phonon processes are the main transport mechanism that assists in the transport of holes across the intrinsic a-Si:H barrier. Simulations presented here show that multi-phonon injection of holes into the a-Si:H(i) layer is the rate limiting step for transport across the a-Si:H(i) layer. Our results indicate that multi-phonon transport is strongly dependent on the electric field at the a-Si:H(i)/c-Si heterointerface as well. Transport simulations presented in this paper are consistent with experimental findings that multi-phonon processes limit transport across the a-Si:H(i) layer and are responsible for photocurrent suppression at the a-Si:H(i)/c-Si heterointerface when these processes are slower than the associated incident hole flux due to photo-excitation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Explosive Byproduct Gas Transport Through Sorptive Geomedia

Current underground nuclear explosion (UNE) detection strategies rely heavily on atmospheric noble gas sampling of radioxenon. However, discriminating nuclear weapons testing programs from civilian sources is difficult due to highly variable atmospheric radioxenon backgrounds and processes affecting subsurface transport of parent radionuclides. Here, we aim to study the transport of gases produced by subsurface explosions as novel stable signatures for underground nuclear explosion (UNE) monitoring. These gases may be produced in large quantities with distinct molecular ratios, which will be impacted by subsurface transport processes. To demonstrate how ratios of gases produced by explosions can change during transport in geomaterials, we conducted laboratory benchtop experiments on the transport of carbon dioxide (CO 2 ) and hydrogen (H 2 ) gases through variably saturated zeolitic tuff, which is abundant at the historic US testing site. We observed that zeolitic tuff sorbs substantial quantities of CO 2 while allowing H 2 to transport more freely, leading to changes in the molecular ratios of the two gases along the transport pathway. Gas uptake in the dry zeolitic tuff core was 72.3% for CO 2 , compared with 53.4% for xenon and 7.6% for H 2 . The presence of 20% water saturation disrupted the CO 2 sorption process, though to a lesser extent than observed for noble gases, with a 36.7% drop in xenon sorption compared with a 21.9% drop for CO 2 . These results represent the first observations of zeolite sorption altering explosive gas ratios during transport through geomedia relevant to nuclear proliferation monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Non-linear Wire Rope Isolator Model to Enhance Transportation Simulation of Fragile Equipment

Abstract Introduction Wire rope isolators are often used as means of vibration isolation for the transportation of fragile machine equipment. When deployed as suspension systems in a transportation scenario, a simple spring–damper model is often used to predict the dynamic loads that act on the structure being transported. However, this simple model has proved to be too simplistic to be used in the development of an accurate numerical model that can predict the vibration levels experienced by the inner components of fragile equipment during its transportation. This paper describes the experimental tests conducted on a wire rope isolator used for the transportation of the prototype SSR1 cryomodule. Materials and methods A hysteretic Bouc–Wen model has been used to analytically describe the force–deformation relationship of the wire rope isolators. The developed model of the isolator has been implemented in a larger model to simulate the actual transportation of the prototype SSR1 cryomodule, a section of the new PIP-II linear accelerator under construction at Fermilab. A series of multibody dynamic simulations with rigid and flexible components was used to numerically determine the acceleration of some critical components. Results and conclusions An actual experimental transportation was simulated using two numerical models: the developed Bouc–Wen model and a conventional spring–damper model. It is shown how the Bouc–Wen formulation of the isolator characteristics drastically improves the correspondence between experimental and simulated results if compared to a spring–damper model, especially in the range of 0–30 Hz which is the most critical for transportation problems.

42 ENGINEERING↗
DOE OSTI2025

Statistical distributions for transient transport

Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.

TAP reactor↗
DOE OSTI2021

Thermal Energy Transport in Oxide Nuclear Fuel

To efficiently capture the energy of the nuclear bond, advanced nuclear reactor concepts seek solid fuels that must withstand unprecedented temperature and radiation extremes. In these advanced fuels, thermal energy transport under irradiation is directly related to reactor performance as well as reactor safety. The science of thermal transport in nuclear fuel is a grand challenge as a result of both computational and experimental complexities. Here we provide a comprehensive review of thermal transport research on two actinide oxides: one currently in use in commercial nuclear reactors, uranium dioxide (UO 2 ), and one advanced fuel candidate material, thorium dioxide (ThO 2 ). In both materials, heat is carried by lattice waves or phonons. Crystalline defects caused by fission events effectively scatter phonons and lead to a degradation in fuel performance over time. Bolstered by new computational and experimental tools, researchers are now developing the foundational work necessary to accurately model and ultimately control thermal transport in advanced nuclear fuels. We begin by reviewing research aimed at understanding thermal transport in perfect single crystals. The absence of defects enables studies that focus on the fundamental aspects of phonon transport. Next, we review research that targets defect generation and evolution. Here the focus is on ion irradiation studies used as surrogates for damage caused by fission products. We end this review with a discussion of modeling and experimental efforts directed at predicting and validating mesoscale thermal transport in the presence of irradiation defects. While efforts in these research areas have been robust, challenging work remains in developing holistic tools to capture and predict thermal energy transport across widely varying environmental conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Lamination of >21% Efficient Perovskite Solar Cells with Independent Process Control of Transport Layers and Interfaces

Transport layer and interface optimization is critical for improving the performance and stability of perovskite solar cells (PSCs) but is restricted by the conventional fabrication approach of sequential layer deposition. While the bottom transport layer is processed with minimum constraints, the narrow thermal and chemical stability window of the halide perovskite (HP) layer severely restricts the choice of top transport layer and its processing conditions. To overcome these limitations, we demonstrate lamination of HPs—where two transport layer-perovskite half-stacks are independently processed and diffusion-bonded at the HP-HP interface—as an alternative fabrication strategy that enables self-encapsulated solar cells. Power conversion efficiencies (PCE) of >21% are realized using cells that incorporate a novel transport layer combination along with dual-interface passivation via self-assembled monolayers, both of which are uniquely enabled by the lamination approach. This is the highest reported PCE for any laminated PSC encapsulated between glass substrates. We further show that this approach expands the processing window beyond traditional fabrication processes and is adaptable for different transport layer compositions. The laminated PSCs retained >75% of their initial PCE after 1000 h of 1-sun illumination at 40 °C in air using an all-inorganic transport layer configuration without additional encapsulation. Furthermore, a laminated 1 cm 2 device maintained a V oc of 1.16 V. Finally, the scalable lamination strategy in this study enables the implementation of new transport layers and interfacial engineering approaches for improving performance and stability.

14 SOLAR ENERGY↗
DOE OSTI2024

Curious cross-field transport effects in multi-ion, magnetized plasma

In contrast to single-ion plasma, multiple-ion-species plasma exhibits new, curious, and large transport effects. On short timescales, where ions exchange momentum, magnetized multi-ion plasma behaves as a most unusual substance, compressible across field lines in number density but incompressible in charge density. It takes 40 times longer for electrons to participate. In this ion–ion cross-field transport regime, we identified the charge-incompressibility heat pump effect, transferring heat both spatially and between species. Curiously, the direction of impurity transport strongly depends on plasma magnetization, characterized by the ratio of light ion gyrofrequency to the collision frequency between light and heavy ion species. The expulsion of heavy ion impurities from a hotspot occurs sufficiently quickly to be observable on MagLIF, so long as plasma becomes sufficiently collisionally magnetized under implosion. Even more curious, multi-ion transport changes its nature in partially ionized plasma, where ions occupy different charge states. In this regime, we identify a partial-ionization deconfinement effect. The combination of cross-field transport, ionization, and recombination leads to a net ion charge moving across magnetic field lines on the ion–ion transport timescale as opposed to the electron–ion transport timescale. Cross-field transport effects in multi-ion plasma are important in a number of applications, including nuclear fusion and plasma mass filters.

Mlodik, M. E. (ORCID:0000000343003941)↗
DOE OSTI2022

Simulation of plasma transport in MPS-LD linear plasma device by using BOUT++

Here a linear plasma device (LPD) module based on the 2D transport module under the BOUT++ framework is developed in this paper to simulate plasma transport in the LPD. The LPD module includes three parts, i.e. magnetic field calculation, simulation mesh generation and plasma transport setup. The magnetic field is calculated with the circular current loop using the location and current information of each coil. The mesh generation code can produce a simulation mesh for LPD by employing the magnetic field. The plasma transport model is based on the reduced Braginskii equations, which consist of the continuity equation, momentum equation, and energy equation. The fluid neutral model is applied for neutral particle simulation. Deuterium (D) and helium (He) ions and atoms can be simulated by the model. The first attempt to simulate plasma transport in the new LPD, called multiple plasma simulation linear plasma device (MPS-LD), is presented using the developed model. The D plasma transport in the MPS-LD is simulated and benchmarked against the two-point model, showing the validation of the BOUT++ simulation. The effects of radial transport on the heat load to the target are studied, which illustrates the significant impact of the radial diffusivities $D_⟂$ and $\mathcal{X}_{⟂i,e}$ on the plasma. Moreover, the He impurity injection process during the discharge is studied with emphasis on plasma–impurity interactions. The simulation results show that He injection can reduce the plasma energy load to the target significantly, and the efficiency depends on the He source density and injection velocity. The present work provides an alternative and flexible simulation tool for plasma transport in LPDs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Testing predictions of electron scale turbulent pedestal transport in two DIII-D ELMy H-modes

In this study, we present linear and nonlinear gyrokinetic analyses in the pedestal region of two DIII-D ELMy H-mode discharges using the CGYRO code. The otherwise matched discharges employ different divertor configurations to investigate the impact of varying recycling and particle source on pedestal profiles. Linear gyrokinetic simulations find electrostatic ion-scale instabilities (ion temperature gradient and trapped electron modes, ITG-TEM) are present just inside the top of the pedestal with growth rates that are enhanced significantly by parallel velocity shear. In the sharp gradient region, E x B shearing rates are comparable or larger than ion scale growth rates, suggesting the suppression of ITG-TEM modes in this region. Instead, the electron temperature profiles are found to be correlated with and just above the electron temperature gradient (ETG) instability thresholds. Using gradients varied within experimental uncertainties, nonlinear electron-scale gyrokinetic simulations predict electron heat fluxes from ETG turbulence, that when added to neoclassical ion thermal transport simulated by NEO, account for 30-60% of the total experimental heat flux. In addition, the neoclassical electron particle flux is found to contribute significantly to the experimental fluxes inferred from SOLPS-ITER analysis. Additional nonlinear gyrokinetic simulations are run varying input gradients to develop a threshold-based reduced model for ETG transport, finding a relatively simple dependence on η e = L ne /L Te . Predictive transport simulations are used to validate this pedestal-specific ETG model, in conjunction with a model for neoclassical particle transport. In both discharges, the predicted electron temperatures are always overpredicted, indicative of the insufficient stiffness in the ETG pedestal model to account for all of the experimental electron thermal transport. In the case of the closed divertor discharge with lower particle source, the predicted electron density is close to the experiment, consistent with the magnitude of neoclassical particle transport in that discharge. However, the density profiles are overpredicted in the open divertor discharge (larger particle source), due to insufficient model transport. In conclusion, the implications for other mechanisms accounting for the remainder of transport in the sharp gradient region in the two discharges are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Challenges and approaches to interpretive modeling of boundary plasma and neutral transport in a closed, pumped divertor

An experimental discharge from the DIII-D tokamak is modeled using the SOLPS-ITER code suite and compared against measurements in the pumped and relatively closed upper divertor. Uncertainties of boundary plasma simulations are identified by attempting to match code inputs to experimental conditions, including iteratively solving transport coefficients to match upstream experimental profiles using varying quantities of core particle flux, different pumping models, and various assumptions of ion thermal transport. Simulated boundary conditions for particle injection at the core interface are shown to be relevant to the plasma solution at the divertor targets, even if upstream transport is modified so that plasma profiles are comparatively similar, although seperatrix density is not held constant. When upstream plasma profiles are matched to experimental measurements by varying diffusive transport coefficients, using either poloidally symmetric or ballooning structure, the model finds a majority of injected energy being transported radially off the computational domain, in conflict with experimental radiated power measurements and heat flux measurements at the divertor target. Imposing a maximum thermal diffusivity or radially shifting the experimental separatrix location of the fitted profiles to increase power conducted to the targets by increasing the upstream electron temperature does not significantly modify this result. Including a thermalizing plenum volume in the simulation domain is shown to maintain the experimental volumetric pumping rate without knowing the neutral energy distribution incident on the pump duct a priori. By modifying transport parameters to match different assumptions for ion temperature, downstream neutral pressure changes by more than a factor of two, suggesting that attention to ion thermal transport may be a critical parameter for simulations to accurately resolve recycling and neutral transport, particularly in a closed divertor geometry. In addition to quantifying various modeling uncertainties, this work motivates both further experimental study and modeling improvements to improve predictive capabilities.

divertor↗
DOE OSTI2023

Chloroplast phosphate transporter CrPHT4-7 regulates phosphate homeostasis and photosynthesis in Chlamydomonas

Abstract In eukaryotic cells, phosphorus is assimilated and utilized primarily as phosphate (Pi). Pi homeostasis is mediated by transporters that have not yet been adequately characterized in green algae. This study reports on PHOSPHATE TRANSPORTER 4-7 (CrPHT4-7) from Chlamydomonas reinhardtii, a member of the PHT4 transporter family, which exhibits remarkable similarity to AtPHT4;4 from Arabidopsis (Arabidopsis thaliana), a chloroplastic ascorbate transporter. Using fluorescent protein tagging, we show that CrPHT4-7 resides in the chloroplast envelope membrane. Crpht4-7 mutants, generated by the CRISPR/Cas12a-mediated single-strand templated repair, show retarded growth, especially in high light, reduced ATP level, strong ascorbate accumulation, and diminished non-photochemical quenching in high light. On the other hand, total cellular phosphorous content was unaffected, and the phenotype of the Crpht4-7 mutants could not be alleviated by ample Pi supply. CrPHT4-7-overexpressing lines exhibit enhanced biomass accumulation under high light conditions in comparison with the wild-type strain. Expressing CrPHT4-7 in a yeast (Saccharomyces cerevisiae) strain lacking Pi transporters substantially recovered its slow growth phenotype, demonstrating that CrPHT4-7 transports Pi. Even though CrPHT4-7 shows a high degree of similarity to AtPHT4;4, it does not display any substantial ascorbate transport activity in yeast or intact algal cells. Thus, the results demonstrate that CrPHT4-7 functions as a chloroplastic Pi transporter essential for maintaining Pi homeostasis and photosynthesis in C. reinhardtii.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Anisotropic Thermal Transport in Quasi-2D Ruddlesden-Popper Hybrid Perovskite Superlattices

Two-dimensional hybrid metal-halide perovskites (2D-MHPs) have emerged as important solution-processed semiconductors with favorable optical and electronic properties for diverse applications in photovoltaics, optoelectronics, and spintronics. The quasi-2D layered structures, featuring large acoustic impedance mismatches between the organic and inorganic sublattices, are expected to result in distinct and anisotropic thermal transport properties along the cross-plane and in-plane directions. Here, we introduce transducer-free vibrational-pump-visible-probe (VPVP) approaches that enable accurate quantification of anisotropic thermal transport properties in various archetypical single-crystalline 2D-MHPs. Specifically, using VPVP spectroscopy and VPVP microscopy, we measure the anisotropic thermal diffusivities of 2D-MHPs with systematically varied Pb-I octahedral layer thicknesses, as well as organic spacer types and lengths, revealing how these structural parameters alter the cross-plane and in-plane thermal transport properties in distinct ways. While diffuse interface scattering plays an important role in dictating cross-plane thermal transport, in-plane thermal transport is primarily determined by phonon transport within interconnected inorganic layers. Density functional theory incorporating four-phonon scatterings provides further insight into the low thermal conductivity and modest thermal conduction anisotropy in 2D-MHPs. Our work demonstrates a new all-optical and noncontact method, which requires minimal sample preparation and allows direct visualization of cross-plane and in-plane thermal transport, potentially compatible with sample environments. The demonstrated VPVP approaches can advance understanding of thermal transport in 2D-MHPs as well as wide-ranging hybrid and polymeric semiconductors beyond 2D-MHPs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Inside out: Measuring the effect of wood anatomy on the efflux and assimilation of xylem–transported CO 2

Carbon dioxide concentrations (including aqueous CO 2 , carbonic acid, bicarbonate, and carbonate) in woody tissues can be up to 750 times higher than atmospheric CO 2 concentrations, ranging from <1% to >26% vs atmospheric ~0.04% (Fig. 1) (Teskey et al. 2008). CO 2 formed through respiration is generally assumed to diffuse to the atmosphere from tissues adjacent to where it is produced. Here, this CO 2 buildups in the stem due to the diffusional barriers in woody and bark tissues. CO 2 in the stem has three fates: 1) it can be refixed for photosynthesis, 2) it can be used for anaplerotic reactions, or 3) it can exit the plant either adjacent to where it was produced (radial diffusion) or in an area remote from its point of origin (xylem-transported CO 2 ). Not accounting for assimilation of xylem-transported CO 2 may result in underestimating total plant photosynthesis. Alternatively, overlooking the transport of CO 2 away from its point of origin complicates the estimation of respiration in stems, branches, or even leaves. For example, CO 2 efflux from the stem may not solely represent stem respiration, but it may represent CO 2 generated through respiration in areas remote from the point of efflux (Stutz et al., 2017). Additionally, wood anatomy and branching architecture likely influence how much and how far xylem-transported CO 2 travels (Fig. 2). Few studies have combined measurements of both the efflux of xylem-transported CO 2 from trees together and the assimilation of xylem-transported CO 2 . Excitingly in this issue of Plant, Cell & Environment, Salomón et al. (pp. ) demonstrate the importance of xylem-transported CO 2 in plants with different wood anatomies by comparing the amount of xylem-transported CO 2 used for photosynthesis to the amount effluxed.

54 ENVIRONMENTAL SCIENCES↗