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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 217 records · Page 12

Stochastically Realized Observables for Excitonic Molecular Aggregates

In this work, we show that a stochastic approach enables calculations of the optical properties of large 2-dimensional and nanotubular excitonic molecular aggregates. Previous studies of such systems relied on numerically diagonalizing the dense and disordered Frenkel Hamiltonian, which scales approximately as $\mathcal{O}$($N$ 3 ) for $N$ dye molecules. Our approach scales much more efficiently as $\mathcal{O}$($N$ log($N$)), enabling quick study of systems with a million of coupled molecules on the micrometer size scale. We calculate several important experimental observables, including the optical absorption spectrum and density of states, and develop a stochastic formalism for the participation ratio. Quantitative agreement with traditional matrix diagonalization methods is demonstrated for both small- and intermediate-size systems. The stochastic methodology enables the study of the effects of spatial-correlation in site energies on the optical signatures of large 2D aggregates. Our results demonstrate that stochastic methods present a path forward for screening structural parameters and validating experiments and theoretical predictions in large excitonic aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Theoretical Pathway toward Improved Reverse Osmosis Membrane Selectivity for Neutral Solutes: Inspiration from Gas Separations

We report highly rigid membrane materials with tailored structures have exhibited permeabilities and selectivities that exceed the polymer upper bound in gaseous and organic solvent separations for challenging mixtures containing species that are similar in size and shape. One potential question is whether such membrane materials can maintain meaningful guest diffusivities in situations where the microporous spaces are essentially full of guest molecules. Here, we use a simplified transition state theory approach to estimate the diffusivity of water and small organics within a microporous membrane. The transition state theory model is parameterized using experimental values from zeolites and carbon molecular sieve materials found in the literature. We demonstrate the differences in transport and Maxwell–Stefan diffusivities based on guest species loading with different isotherm behaviors. These calculations theorize a path forward for highly selective reverse osmosis membranes for aqueous phase separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser Direct Write Synthesis of Lead Halide Perovskites

Lead halide perovskites are increasingly considered for applications beyond photovoltaics, for example, light emission and detection, where an ability to pattern and prototype microscale geometries can facilitate the incorporation of this class of materials into devices. In this study, we demonstrate laser direct write of lead halide perovskites, a remarkably simple procedure that takes advantage of the inverse dependence between perovskite solubility and temperature by using a laser to induce localized heating of an absorbing substrate. We also demonstrate arbitrary pattern formation of crystalline CH 3 NH 3 PbBr 3 on a range of substrates and fabricate and characterize a microscale photodetector using this approach. This direct write methodology provides a path forward for the prototyping and production of perovskite-based devices.

36 MATERIALS SCIENCE↗

High-Temperature Refractory Metasurfaces for Solar Thermophotovoltaic Energy Harvesting

Solar energy promises a viable solution to meet the ever-increasing power demand by providing a clean, renewable energy alternative to fossil fuels. For solar thermophotovoltaics (STPV), high-temperature absorbers and emitters with strong spectral selectivity are imperative to efficiently couple solar radiation into photovoltaic cells. We demonstrate refractory metasurfaces for STPV with tailored absorptance and emittance characterized by in situ high-temperature measurements, featuring thermal stability up to at least 1200 °C. Our tungsten-based metasurface absorbers have close-to-unity absorption from visible to near-infrared and strongly suppressed emission at longer wavelengths, while our metasurface emitters provide wavelength-selective emission spectrally matched to the band-edge of InGaAsSb photovoltaic cells. The projected overall STPV efficiency is as high as 18% when a fully integrated absorber/emitter metasurface structure is employed, which is comparable to the efficiencies of the best currently available commercial single-junction PV cells and can be further improved to potentially exceed those in mainstream photovoltaic technologies. Finally, our work opens a path forward for high-performance STPV systems based on refractory metasurface structures.

14 SOLAR ENERGY↗

Interplay Between Strain and Thickness on the Effective Carrier Lifetime of Buffer-Mediated Epitaxial Germanium Probed by the Photoconductance Decay Technique

We report contactless effective minority carrier lifetime of epitaxially grown unstrained and in-plane <110> biaxially tensile-strained (001) germanium (..epsilon..-Ge) epilayers measured using microwave-reflectance photoconductance decay measurements. Strained Ge epilayers were grown using InxGa1-xAs linearly graded buffers on (001) GaAs substrates. Using homogeneous excitation of unstrained Ge epilayers, thickness-dependent separation of minority carrier lifetime components under low injection conditions yielded a bulk lifetime of 114 +/- 2 ns and low surface recombination velocity of 21.3 +/- 0.04 cm/s. More notably, an effective minority carrier lifetime of >100 ns obtained from sub-50 nm 1.6% tensile-strained Ge epilayers showed no degradation relative to the unstrained counterpart. Detailed material characterization using X-ray diffractometry revealed successful strain transfer of 0.61 and 0.89% to the Ge epilayers via InxGa1-xAs metamorphic buffers and confirms pseudomorphic growth. Lattice coherence observed at the e-Ge epilayer and InxGa1-xAs buffer heterointerfaces via transmission electron microscopy substantiates the prime material quality achieved. The relatively high carrier lifetimes achieved are an indicator of excellent material quality and provide a path forward to realize low-threshold Ge laser sources.

bulk lifetime↗

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗

Enhanced Anhydrous Proton Conductivity in Azole Phosphonic Acid Mixtures

Azole molecules are investigated as potential candidates for proton conductors under anhydrous conditions. Since 1,2,3-triazole has the lowest melting point (T m = 17 °C), it was blended with three phosphonic acid-containing molecules (small molecules with one and two phosphonic acids per molecule and a phosphonic acid polymer) to provide a source of excess protons to enhance the proton conductivity of the blends. Here we study a wide range of compositions in each system to find that these three mixtures show a maximum proton conductivity at moderate doping compositions, approximately 5–10 azole molecules per phosphonic acid group. Using NMR diffusometry, we show that the protons bonded to nitrogen move faster than the protons bonded to carbons of 1,2,3-triazole, suggesting proton hopping between azole proton carriers. Given the high proton conductivity at 90 °C of the best mixtures, in the range of 20–60 mS/cm, this work provides a path forward for future work in anhydrous proton-conducting polymer membranes. Additionally, Raman spectroscopy was used to accurately determine the molar percentage of protonated 1,2,3-triazole. Combining that with the proton diffusion results, we find that the phosphonic acid polymer shows the most proton hopping at low acid content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure-Dependent Phase Behavior of Chemically Synthesized Ytterbium Hydride Nanoparticles and Confinement in CMK-3

In this work, we developed a chemical synthesis protocol to prepare both spherical and rod shaped YbH x nanoparticles and infiltrate a mesoporous CMK-3 structure with YbH x nanoparticles. The phase evolution of the YbH x nanoparticles was monitored as a function of the pressure in a diamond anvil cell. The cell volume of the Yb atom showed an unexpected positive deviation from the calculated equation of state (EoS) for the α-phase (space group Pnma) of YbH x . Additionally, the β-phase (space group Fm3̅m) YbH x nanoparticles appeared to become amorphous at approximately 27 GPa, although the same behavior was not observed in the Pnma (α-phase). The Pmna phase remained stable (measured up to 59.3 GPa) and showed a significantly higher than expected volume per Yb atom relative to the calculated EoS. This deviation could be attributed to the nanoscale effect on the thermodynamics of ytterbium hydride formation, which could provide a path forward to accessing higher order ytterbium hydrides (YbH x , x > 3) at pressures much lower than in the bulk metal.

diamond anvil cell↗

Using a 3D Porous Flow-Through Electrode Geometry for High-Rate Electrochemical Reduction of CO 2 to CO in Ionic Liquid

Three-dimensional porous flow-through electrodes promise the realization of higher current densities in the electrochemical carbon dioxide reduction reaction (CO 2 RR) by overcoming mass-transport limitations associated with the diffusion of dissolved CO 2 in the bulk electrolyte. Using an ionic-liquid-based electrolyte, [EMIM]BF 4 , offers the additional benefit of higher CO 2 solubility compared to water-based electrolytes. Here, we quantitatively evaluated the effects of flow-driven reactant transport on electrode activity and selectivity for the electrochemical CO 2 RR in [EMIM]BF4. High-surface-area porous flow-through electrodes were fabricated by wet-chemical deposition of Ag nanoflowers on commercial macroporous Al foams. At the highest electrolyte flow-through rate of 100 mL min –1 , we observed a 70-fold increase in partial CO current density, and a 7-fold increase in the Faradaic efficiency toward CO, from 10% without flow to 75% with flow. At the same time, the selectivity changed from oxalate as the main product without flow to CO in the electrolyte flow-through configuration. These results demonstrate that the flow-through approach provides a promising path forward to control selectivity and to overcome mass-transport limitations of the electrochemical CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymeric Electron-Selective Contact for Crystalline Silicon Solar Cells with an Efficiency Exceeding 19%

Carrier-selective contacts have become a prominent path forward toward efficient crystalline silicon (c-Si) photovoltaics. Among the proposed contacting materials, organic materials may offer simplified and low-cost processing compared with typical vacuum deposition techniques. In this paper, branched polyethylenimine (b-PEI) is presented as an electron-transport layer (ETL) for c-Si solar cells. The incorporation of a b-PEI interlayer between c-Si(n) and Al leads to a low contact resistivity of 24 mΩ cm 2 . A silicon heterojunction solar cell integrated with b-PEI is demonstrated achieving a power conversion efficiency of 19.4%, which improves the benchmark efficiency of a c-Si solar cell with an organic ETL. This electron selectivity of b-PEI is attributed to its Lewis basicity, i.e., electron-donating ability, promoting favorable band bending at the c-Si surface for electron transport. Moreover, several other Lewis base polymers perform as efficient ETLs in organic/c-Si hybrid devices, indicating Lewis basicity could be a guideline for future organic ETL design.

14 SOLAR ENERGY↗

Engineering the Novel Extremophile Alga Chlamydomonas pacifica for High Lipid and High Starch Production as a Path to Developing Commercially Relevant Strains

Microalgae offer a compelling platform for the production of commodity products, due to their superior photosynthetic efficiency, adaptability to nonarable lands and nonpotable water, and their capacity to produce a versatile array of bioproducts, including biofuels and biomaterials. However, the scalability of microalgae as a bioresource has been hindered by challenges such as costly biomass production related to vulnerability to pond crashes during large-scale cultivation. This study presents a pipeline for the genetic engineering and pilot-scale production of biodiesel and thermoplastic polyurethane precursors in the extremophile species Chlamydomonas pacifica. This extremophile microalga exhibits exceptional resilience to high pH (>11.5), high salinity (up to 2% NaCl), and elevated temperatures (up to 42 °C). Initially, we evolved this strain to also have a high tolerance to high light intensity (>2000 μE/m 2 /s) through mutagenesis, breeding, and selection. We subsequently genetically engineered C. pacifica to significantly enhance lipid production by 28% and starch accumulation by 27%, all without affecting its growth rate. We demonstrated the scalability of these engineered strains by cultivating them in pilot-scale raceway ponds and converting the resulting biomass into biodiesel and thermoplastic polyurethanes. This study showcases the complete cycle of transforming a newly discovered species into a commercially relevant commodity production strain. This research underscores the potential of extremophile algae, including C. pacifica, as a key species for the burgeoning sustainable bioeconomy, offering a viable path forward in mitigating environmental challenges and supporting global bioproduct demands.

59 BASIC BIOLOGICAL SCIENCES↗

Toward Continuous, Oriented Covalent Organic Framework Membranes for Precise Molecular Separations

The goal of achieving energy-efficient, precise molecular separations has motivated interest in developing and employing porous crystalline frameworks as membrane materials. Covalent organic frameworks (COFs) are ordered crystalline matrices composed of covalently bonded organic monomers and are synthesized via reversible reticular chemistry. COFs possess high porosity, structural tunability, and chemical and thermal stability, making them ideally suited for emerging, high-value membrane separation processes, such as ion separations, organic solvent nanofiltration, and gas separations. Although a range of COF membranes have been fabricated and tested in the past decade, these membranes are primarily polycrystalline, weakly crystalline, and/or discontinuous, resulting in suboptimal performance. In this review, we identify the properties that make COFs well-suited as membrane materials, while critically outlining the shortcomings of existing disordered COF membranes. We then highlight the recent emergence of highly crystalline, continuous, oriented two-dimensional COF membranes as a promising path forward for highly selective molecular separations. These continuous, oriented COF membranes exhibit tunable one-dimensional nanochannels, allowing for ultrafast molecular transport and precise species selectivity, thereby expanding the set of separations that can be practically achieved with membrane systems. We discuss synthesis and modification techniques that result in continuous, oriented COF membranes and evaluate the performance of such membranes for a variety of molecular separations. We conclude by identifying ongoing challenges in the development of COF membranes and outlining the future of their applications in molecular separations, which will necessarily rely on advancements in the synthesis of continuous, oriented membranes.

COF modification↗

Inverse-Designed Photonics for Semiconductor Foundries

Silicon photonics is becoming a leading technology in photonics, displacing traditional fiber optic transceivers and enabling new applications. Further improving the density and performance of silicon photonics, however, has been challenging due to the large size and limited performance of traditional semianalytically designed components. Automated optimization of photonic devices using inverse design is a promising path forward but has, until now, faced difficulties in producing designs that can be fabricated reliably at scale. In this paper we experimentally demonstrate four inverse-designed devices made successfully in a commercial silicon photonics foundry: a spatial mode multiplexer, wavelength demultiplexer, 50–50 directional coupler, and 3-way power splitter. These devices are efficient, robust to fabrication variability, and compact, with footprints only a few micrometers across. They pave the way forward for the widespread practical use of inverse design.

36 MATERIALS SCIENCE↗

Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

54 ENVIRONMENTAL SCIENCES↗

Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

58 GEOSCIENCES↗

The Terrestrial Biosphere Model Farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

54 ENVIRONMENTAL SCIENCES↗

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗