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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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At least 577 records · Page 32

A laser-assisted chlorination process for reversible writing of doping patterns in graphene

Chemical doping can be used to control the charge-carrier polarity and concentration in two-dimensional van der Waals materials. However, conventional methods based on substitutional doping or surface functionalization result in the degradation of electrical mobility due to structural disorder, and the maximum doping density is set by the solubility limit of dopants. Here we show that a reversible laser-assisted chlorination process can be used to create high doping concentrations (above 3 × 10 13 cm -2 ) in graphene monolayers with minimal drops in mobility. The approach uses two lasers—with distinct photon energies and geometric configurations—that are designed for chlorination and subsequent chlorine removal, allowing highly doped patterns to be written and erased without damaging the graphene. To illustrate the capabilities of our approach, we use it to create rewritable photoactive junctions for graphene-based photodetectors.

42 ENGINEERING↗

Silver salt enabled H/D exchange at the β-position of thiophene rings: synthesis of fully deuterated thiophene derivatives

Here, we disclose a silver catalyzed H/D exchange reaction, which can introduce the deuterium atom at the β position of thiophene rings without the assistance of any coordinating groups. The advantages of this reaction include operation in open air, usage of D 2 O as the deuterium source, good tolerance to a range of functional groups and obtaining high atom% deuterium incorporation. In addition, this H/D exchange reaction is employed for direct deuteration of a thiophene based monomer, which is usually prepared by multistep synthesis from expensive deuterated starting materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Boundary conditions manipulation of polar vortex domains in BiFeO 3 membranes via phase-field simulations

Polar vortex domains have recently become an emergent research field due to the abundant physical phenomena and potential applications in high-density memories. Here, we explore the mechanisms of creating polar vortex domains in the BiFeO3 (BFO) membranes subjected to different boundary conditions using phase-field simulations. A major difference is that the vortex in membrane can be stabilized even under short-circuit electrical boundary conditions compared to vortex in other systems, such as thin film or superlattice. We found that (a) the formation of polar vortex domains at the membrane interior under bending is mainly driven by the reduction of elastic energy under short-circuit boundary condition, and the vortex chirality (namely, clockwise and counterclockwise) could be identified by n-shape and u-shape bending; (b) in the unbent open-circuit BFO membrane case, exotic trapezoid-shaped vortex nanodomains form at the terminations of 109 degrees domain walls (DWs) and partially charged 71 degrees DWs, which is driven by the local depolarization field and the interplay among electrostatic, elastic, and gradient and Landau energies. We also examine Kittel's law by establishing the dependence of vortex periods on the membrane thickness. Furthermore, these results give further understanding of the effect of boundary conditions on the formation of polar vortex domains, guiding experimental designs of vortex-based high-density memories.

36 MATERIALS SCIENCE↗

Simulation of DIII-D disruption with argon pellet injection and runaway electron beam

Abstract The next generation of large tokamaks, including ITER, will be equipped with a disruption mitigation system (DMS) that can be activated if a disruption is deemed to be imminent. Introducing impurities by pellet (large or shattered) or massive gas injection has been shown to be an effective mitigation mechanism on many tokamaks. The goal of the mitigation is to lessen the thermal and electromagnetic loads from the disruption without generating enough high-energy (runaway) electrons to damage the device. Variations of this mitigation process with impurity injection are presently being tested on many experiments. We have modeled one such impurity injection experiment on DIII-D using the M3D-C1 nonlinear 3D extended MHD code (Jardin et al 2012 Comput. Sci. Discovery 6 014002), The model includes an argon large pellet injection and ablation model, impurity ionization, recombination, and radiation, and runaway electron formation and subsequent evolution, including both Dreicer and avalanche sources. We obtain reasonable agreement with the experimental results for the timescale of the thermal and current quench and for the magnitude of the runaway electron plateau formed during the mitigation. This is the first 3D full MHD simulation with pellets and REs to simulate the disruption process and it also provides a partial validation of the M3D-C1 DMS model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tonoplast Sucrose Trafficking Modulates Starch Utilization and Water Deficit Behavior in Poplar Leaves

Leaf osmotic adjustment by the active accrual of compatible organic solutes (e.g. sucrose) contributes to drought tolerance throughout the plant kingdom. In Populus tremula x alba, PtaSUT4 encodes a tonoplast sucrose–proton symporter, whose downregulation by chronic mild drought or transgenic manipulation is known to increase leaf sucrose and turgor. While this may constitute a single drought tolerance mechanism, we now report that other adjustments which can occur during a worsening water deficit are damped when PtaSUT4 is constitutively downregulated. Specifically, we report that starch use and leaf relative water content (RWC) dynamics were compromised when plants with constitutively downregulated PtaSUT4 were subjected to a water deficit. Leaf RWC decreased more in wild-type and vector control lines than in transgenic PtaSUT4-RNAi (RNA-interference) or CRISPR (clustered regularly interspersed short palindromic repeats) knockout (KO) lines. The control line RWC decrease was accompanied by increased PtaSUT4 transcript levels and a mobilization of sucrose from the mesophyll-enriched leaf lamina into the midvein. The findings suggest that changes in SUT4 expression can increase turgor or decrease RWC as different tolerance mechanisms to reduced water availability. Evidence is presented that PtaSUT4-mediated sucrose partitioning between the vacuole and the cytosol is important not only for overall sucrose abundance and turgor, but also for reactive oxygen species (ROS) and antioxidant dynamics. Interestingly, the reduced capacity for accelerated starch breakdown under worsening water-deficit conditions was correlated with reduced ROS in the RNAi and KO lines. A role for PtaSUT4 in the orchestration of ROS, antioxidant, starch utilization and RWC dynamics during water stress and its importance in trees especially, with their high hydraulic resistances, is considered.

59 BASIC BIOLOGICAL SCIENCES↗

Band Engineering of Large-Twist-Angle Graphene/h-BN Moiré Superlattices with Pressure

Graphene interfacing hexagonal boron nitride (h-BN) forms lateral moiré superlattices that host a wide range of new physical effects such as the creation of secondary Dirac points and band gap opening. A delicate control of the twist angle between the two layers is required as the effects weaken or disappear at large twist angles. In this Letter, we show that these effects can be reinstated in large-angle (~1.8°) graphene/h-BN moiré superlattices under high pressures. Additionally, a graphene/h-BN moiré superlattice microdevice is fabricated directly on the diamond culet of a diamond anvil cell, where pressure up to 8.3 GPa is applied. The band gap at the primary Dirac point is opened by 40-60 meV, and fingerprints of the second Dirac band gap are also observed in the valence band. Theoretical calculations confirm the band engineering with pressure in large-angle graphene/h-BN bilayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Giant Isotope Effect of Thermal Conductivity in Silicon Nanowires

Isotopically purified semiconductors potentially dissipate heat better than their natural, isotopically mixed counterparts as they have higher thermal conductivity (κ). But the benefit is low for Si at room temperature, amounting to only ~10% higher κ for bulk 28 Si than for bulk natural Si ( nat Si). Here we show that in stark contrast to this bulk behavior, 28 Si (99.92% enriched) nanowires have up to 150% higher κ than nat Si nanowires with similar diameters and surface morphology. Using a first-principles phonon dispersion model, this giant isotope effect is attributed to a mutual enhancement of isotope scattering and surface scattering of phonons in nat Si nanowires, correlated via transmission of phonons to the native amorphous SiO 2 shell. The Letter discovers the strongest isotope effect of κ at room temperature among all materials reported to date and inspires potential applications of isotopically enriched semiconductors in microelectronics.

36 MATERIALS SCIENCE↗

Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical assumptions at leaf and global scales

Abstract Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation ( A ). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO 2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi‐hypothesis methods (that account for both hypothesis and parameter variability) for process‐level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting‐rate selection. Each of the four processes comprises 1–3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high‐resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting‐rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting‐rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A . Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%–10%, equivalent to 50%–160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi‐hypothesis methods.

54 ENVIRONMENTAL SCIENCES↗

Phase transition enhanced superior elasticity in freestanding single-crystalline multiferroic BiFeO 3 membranes

The integration of ferroic oxide thin films into advanced flexible electronics will bring multifunctionality beyond organic and metallic materials. However, it is challenging to achieve high flexibility in single-crystalline ferroic oxides that is considerable to organic or metallic materials. Here, we demonstrate the superior flexibility of freestanding single-crystalline BiFeO 3 membranes, which are typical multiferroic materials with multifunctionality. They can endure cyclic 180° folding and have good recoverability, with the maximum bending strain up to 5.42% during in situ bending under scanning electron microscopy, far beyond their bulk counterparts. Such superior elasticity mainly originates from reversible rhombohedral-tetragonal phase transition, as revealed by phase-field simulations. This study suggests a general fundamental mechanism for a variety of ferroic oxides to achieve high flexibility and to work as smart materials in flexible electronics.

36 MATERIALS SCIENCE↗

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗

Ontology-Enriched Specifications Enabling Findable, Accessible, Interoperable, and Reusable Marine Metagenomic Datasets in Cyberinfrastructure Systems

Marine microbial ecology requires the systematic comparison of biogeochemical and sequence data to analyze environmental influences on the distribution and variability of microbial communities. With ever-increasing quantities of metagenomic data, there is a growing need to make datasets Findable, Accessible, Interoperable, and Reusable (FAIR) across diverse ecosystems. FAIR data is essential to developing analytical frameworks that integrate microbiological, genomic, ecological, oceanographic, and computational methods. Although community standards defining the minimal metadata required to accompany sequence data exist, they haven’t been consistently used across projects, precluding interoperability. Moreover, these data are not machine-actionable or discoverable by cyberinfrastructure systems. By making ‘omic and physicochemical datasets FAIR to machine systems, we can enable sequence data discovery and reuse based on machine-readable descriptions of environments or physicochemical gradients. In this work, we developed a novel technical specification for dataset encapsulation for the FAIR reuse of marine metagenomic and physicochemical datasets within cyberinfrastructure systems. This includes using Frictionless Data Packages enriched with terminology from environmental and life-science ontologies to annotate measured variables, their units, and the measurement devices used. This approach was implemented in Planet Microbe, a cyberinfrastructure platform and marine metagenomic web-portal. Here, we discuss the data properties built into the specification to make global ocean datasets FAIR within the Planet Microbe portal. We additionally discuss the selection of, and contributions to marine-science ontologies used within the specification. Finally, we use the system to discover data by which to answer various biological questions about environments, physicochemical gradients, and microbial communities in meta-analyses. This work represents a future direction in marine metagenomic research by proposing a specification for FAIR dataset encapsulation that, if adopted within cyberinfrastructure systems, would automate the discovery, exchange, and re-use of data needed to answer broader reaching questions than originally intended.

59 BASIC BIOLOGICAL SCIENCES↗

Signatures of aerosol-cloud interactions in GiOcean: a coupled global reanalysis with two-moment cloud microphysics

Aerosols influence the Earth's radiative balance through direct interactions with radiation and by affecting cloud properties. Anthropogenic aerosols have led to cooling during the industrial era through aerosol–cloud interactions (ACI), including aerosol effects on cloud microphysical properties and the subsequent adjustments. However, large uncertainties remain in Earth system models (ESMs) regarding the magnitude of this cooling. In part, ESMs substantially disagree on cloud properties, thermodynamics, the hydrological cycle, and general circulation. Reanalysis provides a useful avenue for exploring the impact of ACI on clouds and radiation because its atmosphere is forced to match realistic conditions through the assimilation of observations. Here, we explore the impact of ACI on clouds in the GiOcean reanalysis – the first to incorporate aerosol-cloud interactions. We contrast variables important for ACI between GiOcean and satellite observations and develop 2-dimensional lookup tables of ACI for both using a source-sink budget perspective to attribute the changes in cloud droplet number (Nd) and liquid water path (LWP) to aerosol and meteorology. A compositing analysis using lookup tables shows that GiOcean captures key aspects of aerosol–cloud–precipitation interactions, including (1) activation of aerosol into cloud droplets, (2) effective precipitation scavenging of Nd, (3) suppression of precipitation by high Nd in regions with heavy aerosol emissions. In contrast, satellite observations do not exhibit clear patterns for processes (2) and (3). Random Forest analysis shows that interannual variability in Nd and LWP over the Northern Hemisphere ocean in GiOcean is primarily driven by precipitation, consistent with satellite observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number

Aerosol-cloud interactions (ACI) in warm clouds alter reflected shortwave radiation by influencing cloud microphysical and macrophysical properties. The variable of state controlling ACI is the cloud droplet number concentration (N d ). Here, we examine the perturbations in N d due to anthropogenic aerosols (ΔN d, PD-PI ) using a perturbed parameter ensemble (PPE) hosted in the sixth Community Atmosphere Model (CAM6). Surrogate models are created for the CAM6 PPE outputs and are used to generate 1 million model variants of CAM6 by sampling 45 sources of parameter uncertainty. The range of uncertain physical parameters related to ACI are constrained with observations of aerosol and cloud properties from SOCRATES. The likely range of uncertain parameters and the associated range of ΔN d, PD-PI are more strongly constrained with observations of N d relative to observations of cloud condensation nuclei. We conduct sensitivity tests of how constraints on ΔN d, PD-PI are affected by systematic uncertainties in observations and our limitations in our surrogate models created for CAM6 PPE outputs. Based on this, we provide guidance on the impact of reducing systematic uncertainty in airborne microphysical observations and in surrogate models.

Song, Ci [Univ. of Wyoming, Laramie, WY (United St↗

Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble

Abstract. Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, referred to as the radiative forcing due to ACI (RFaci) and aerosol–cloud adjustments. While the magnitude of RFaci is uncertain, its sign is confidently negative and results in a cooling in the historical record. In contrast, the adjustment of cloud liquid water path (LWP) to enhanced Nd and associated radiative forcing is uncertain in sign. Increased LWP in response to increased Nd is consistent with precipitation suppression, while decreased LWP in response to increased Nd is consistent with enhanced evaporation from cloud top. Observational constraints of these processes are poor in part because of causal ambiguity in the relationship between Nd and LWP. To better understand this relationship, precipitation (P), Nd, and LWP surface observations from the Eastern North Atlantic (ENA) atmospheric observatory are combined with the output from a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model version 6 (CAM6). This allows for causal interpretation of observed covariability. Observations of precipitation and cloud from ENA constrain the range of possible LWP aerosol–cloud adjustments relative to the prior from the PPE by 15 %, resulting in a global value that is confidently positive (a historical cooling) ranging from 2.1 to 6.9 g m−2. It is found that observed covariability between Nd and LWP is dominated by coalescence scavenging and that this observed covariability is not strongly related to aerosol–cloud adjustments.

54 ENVIRONMENTAL SCIENCES↗

An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6

This paper documents the methodology and preliminary results from a perturbed parameter ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2–CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks are analyzed. The use of various emulators is explored in the multi-dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties, are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2–CAM6 PPE is publicly available and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g., coupling to the land surface).

54 ENVIRONMENTAL SCIENCES↗