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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 289 records · Page 16

Site-Selective Doping and Oxidation State Control of Copper in Gold Nanorods

We report the synthesis of plasmonic gold–copper nanostructures with tunable copper spatial distribution and oxidation state. Au–Cu alloy shells were deposited in aqueous solution onto colloidal gold nanorods that functioned as seeds, and the resulting shell morphology was found to depend strongly on the nanorod aspect ratio. For relatively fat gold nanorods (16 x 31 nm), Au–Cu growth was preferentially localized near the rod midsections, forming belt-like structures, whereas for skinnier nanorods (9 x 32 nm), Au–Cu growth produced patchy surface coverage around the entire rod. The shell thickness was tuned from 1 to 4 nm; upon air exposure, thicker shells exhibited a higher Cu(I) fraction compared to the initial shell. Incorporation of the Au–Cu shell led to pronounced shifts in the plasmonic features of the gold nanorods. These tunable plasmonic Au–Cu nanorods provide a materials basis for Cu-based plasmonic materials in the context of electrochemical CO₂ reduction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Charge Separation at Organic Interfaces with Near-Zero Energy Offset: A Step toward Designing Inorganic-like Organic Semiconductors

For organic semiconductors, it is often presumed that an energy level offset at the donor–acceptor (D-A) interface is required to provide the driving force for charge separation (CS). This energy level offset unavoidably leads to a voltage loss in organic photovoltaics. In this work, by using zinc phthalocyanine (ZnPc) and fluorinated zinc phthalocyanine (F 4 ZnPc) as a model D/A interface, we found that spontaneous CS, with an enthalpy increase of ∼0.3–0.4 eV, can occur even with an interfacial energy offset as small as ∼0.1 eV. This enthalpy-increase CS process is driven by entropy. The entropic driving force can be enhanced by two factors: (1) a point-like spatial contact between the delocalized electron and hole wave function in the charge transfer exciton; (2) a small band bending near the interface originating from long-range electrostatic interaction. Our work demonstrates that effective CS can occur at interfaces with a near-zero energy level offset, which means that the energy loss at the D/A interface can be avoided.

36 MATERIALS SCIENCE↗

Modulation of Electrostatic Potential in 2D Crystal Engineered by an Array of Alternating Polar Molecules

The moiré potential in rotationally misfit two-dimensional (2D) heterostructures has been used to build artificial exciton and electron lattices, which have become platforms for realizing exotic electronic phases. Here, we demonstrate a different approach to create a superlattice potential in 2D crystals by using the near field of an array of polar molecules. Here, a bilayer of titanyl phthalocyanine (TiOPc), consisting of alternating out-of-plane dipoles, is deposited on monolayer MoS 2 . Time-resolved two-photon photoemission spectroscopy reveals a pair of interlayer exciton states with an energy difference of ~0.1 eV, which is consistent with the electrostatic potential modulation induced by the TiOPc bilayer as determined by density functional theory calculations. Because the symmetry and the period of this potential superlattice can be changed readily by using molecules of different shapes and sizes, molecule/2D heterostructures can be promising platforms for designing artificial exciton and electron lattices.

2D heterostructures↗

Long-Term Statistical Process Monitoring of an Ultrafiltration Water Treatment Process

As water treatment technology has improved, the amount of available process data has substantially increased, making real-time, data-driven fault detection a reality. One shortcoming of the fault detection literature is that methods are usually evaluated by comparing their performance on hand-picked, short-term case studies, which yields no insight into long-term performance. In this work, we first evaluate multiple statistical and machine learning approaches for detrending process data. Then, we evaluate the performance of a PCA-based fault detection approach, applied to the detrended data, to monitor influent water quality, filtrate quality, and membrane fouling of an ultrafiltration membrane system for indirect potable reuse. Based on two short case studies, the adaptive lasso detrending method is selected, and the performance of the multivariate approach is evaluated over more than a year. The method is tested for different sets of three critical tuning parameters, and we find that for long-term, autonomous monitoring to be successful, these parameters should be carefully evaluated. However, in comparison with industry standards of simpler, univariate monitoring or daily pressure decay tests, multivariate monitoring produces substantial benefits in long-term testing.

ammonia↗

Nanoscale Periodic Trapping Sites for Interlayer Excitons Built by Deformable Molecular Crystal on 2D Crystal

The nanoscale moiré pattern formed at 2D transition-metal dichalcogenide crystal (TMDC) heterostructures provides periodic trapping sites for excitons, which is essential for realizing various exotic phases such as artificial exciton lattices, Bose–Einstein condensates, and exciton insulators. At organic molecule/TMDC heterostructures, similar periodic potentials can be formed via other degrees of freedom. Here, we utilize the structure deformability of a 2D molecular crystal as a degree of freedom to create a periodic nanoscale potential that can trap interlayer excitons (IXs). Specifically, two semiconducting molecules, PTCDI and PTCDA, which possess similar band gaps and ionization potentials but form different lattice structures on MoS 2 , are investigated. The PTCDI lattice on MoS 2 is distorted geometrically, which lifts the degeneracy of the two molecules within the crystal’s unit cell. The degeneracy lifting results in a spatial variation of the molecular orbital energy, with an amplitude and periodicity of ~0.2 eV and ~2 nm, respectively. On the other hand, no such energy variation is observed in PTCDA/MoS 2 , where the PTCDA lattice is much less distorted. Furthermore, the periodic variation in molecular orbital energies provides effective trapping sites for IXs. For IXs formed at PTCDI/MoS 2 , rapid spatial localization of the electron in the organic layer toward the interface is observed, which demonstrates the effectiveness of these interfacial IX traps.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Magnetic Response of Excitons and Excitonic Complexes in Defective Hexyl Ammonium Lead Iodide Self-Assembled Quantum Wells

Correlating the magnetic behavior of low-dimensional semiconductors with the chemistry used to form these excitonic materials remains crucial to the development of devices applied to quantum technologies. In this study, we apply large magnetic fields during the collection of low-temperature photoluminescence (PL) to assess the magnetic properties of excitons in hexyl ammonium lead iodide (HA 2 PbI 4 ) self-assembled quantum wells (SAQWs) formed at liquid−liquid interfaces. The effect of incident laser power and temperature was used to assign lower energy features in these samples’ PL spectra to both excitons trapped at defect sites and trions. Measured peaks shifts allow us to estimate coupling between the applied magnetic fields and the charged defect excitons. Our conclusions are supported by density functional theory calculations on supercells of the proposed defective HA 2 PbI 4 SAQW structure. Additionally, we find an anomalous magnetic response from trion states that resembles the behavior of interacting excitonic complexes in similar, quantum-confined materials at low temperatures. These results highlight the crucial role that chemical conditions can play in the magnetic response of 2D semiconductors applied in quantum technologies.

defect chemistry↗

CMIP5 Climate Models Overestimate Cooling by Volcanic Aerosols

We compare projections of the observed hemispherical mean surface temperature (HadCRUT4.6.0.0) and the ensemble mean of CMIP5 climate models' simulations on a set of standard regression model forcing variables. We find that the volcanic aerosol regression coefficients of the CMIP5 simulations are consistently significantly larger (by 40–49%) than the volcanic aerosol coefficients of the observed temperature. The probability that the observed differences are caused just by chance is much less than 0.01. The overestimate is due to the climate models' response to volcanic aerosol radiative forcing. The largest overestimate occurs in the winter season of each hemisphere. We hypothesize that the models' parameterization of aerosol-cloud interactions within ice and mixed phase clouds is a likely source of this discrepancy. Furthermore, the models significantly underestimate the effect of solar variability on temperature for both hemispheres.

54 ENVIRONMENTAL SCIENCES↗

Cryo-EM structures of HIV-1 trimer bound to CD4-mimetics BNM-III-170 and M48U1 adopt a CD4-bound open conformation

Human immunodeficiency virus-1 (HIV-1), the causative agent of AIDS, impacts millions of people. Entry into target cells is mediated by the HIV-1 envelope (Env) glycoprotein interacting with host receptor CD4, which triggers conformational changes allowing binding to a coreceptor and subsequent membrane fusion. Small molecule or peptide CD4-mimetic drugs mimic CD4’s Phe43 interaction with Env by inserting into the conserved Phe43 pocket on Env subunit gp120. Here, we present single-particle cryo-EM structures of CD4-mimetics BNM-III-170 and M48U1 bound to a BG505 native-like Env trimer plus the CD4-induced antibody 17b at 3.7 Å and 3.9 Å resolution, respectively. CD4-mimetic-bound BG505 exhibits canonical CD4-induced conformational changes including trimer opening, formation of the 4-stranded gp120 bridging sheet, displacement of the V1V2 loop, and formation of a compact and elongated gp41 HR1C helical bundle. We conclude that CD4-induced structural changes on both gp120 and gp41 Env subunits are induced by binding to the gp120 Phe43 pocket.

60 APPLIED LIFE SCIENCES↗

Structural and functional characterization of NEMO cleavage by SARS-CoV-2 3CLpro

Abstract In addition to its essential role in viral polyprotein processing, the SARS-CoV-2 3C-like protease (3CLpro) can cleave human immune signaling proteins, like NF-κB Essential Modulator (NEMO) and deregulate the host immune response. Here, in vitro assays show that SARS-CoV-2 3CLpro cleaves NEMO with fine-tuned efficiency. Analysis of the 2.50 Å resolution crystal structure of 3CLpro C145S bound to NEMO 226–234 reveals subsites that tolerate a range of viral and host substrates through main chain hydrogen bonds while also enforcing specificity using side chain hydrogen bonds and hydrophobic contacts. Machine learning- and physics-based computational methods predict that variation in key binding residues of 3CLpro-NEMO helps explain the high fitness of SARS-CoV-2 in humans. We posit that cleavage of NEMO is an important piece of information to be accounted for, in the pathology of COVID-19.

60 APPLIED LIFE SCIENCES↗

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

The neurobench framework for benchmarking neuromorphic computing algorithms and systems

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. This article presents NeuroBench, a benchmark framework for neuromorphic algorithms and systems, which is collaboratively designed from an open community of researchers across industry and academia. NeuroBench introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent and hardware-dependent settings. For latest project updates, visit the project website (neurobench.ai).

Yik, Jason [Harvard Univ., Cambridge, MA (United S↗

Transforming jet flavour tagging at ATLAS

Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data. The measured c-jet (light-jet) rejection in data is improved by a factor of 3.5 (1.8) for a 70% b-jet tagging efficiency, compared to the previous algorithm. GN2 provides substantial benefits for physics analyses involving heavy-flavour jets, such as measurements of Higgs boson pair production and the couplings of bottom and charm quarks to the Higgs boson, and demonstrates the impact of advanced machine learning methods in experimental particle physics.

Characterization and analytical techniques↗

Ozone mitigates extended growing season and enhanced vegetation greenness driven by environmental change

Rising temperature and elevated CO 2 concentrations lead to extended growing seasons and enhanced vegetation greenness in terrestrial ecosystems, especially across the Northern Hemisphere. However, whether and to what extent surface ozone, an anthropogenic environmental factor, affects vegetation phenology and greenness remains unexplored at a large scale. Integrating ground-based ozone observations with multiple satellite observations, we demonstrate that surface ozone significantly shortened the growing season by delaying start of season and advancing end of season. Additionally, ozone reduced growing-season vegetation greenness, as reflected in decreased annual accumulated Enhanced Vegetation Index and maximum Enhanced Vegetation Index. These impacts show pronounced spatial heterogeneity, varying in magnitude across the United States, Europe, and China over the past decade, highlighting ozone’s diverse impact on vegetation across regions. Our study predicts that continuously increasing surface ozone concentration will mitigate warming-driven lengthening the growing season by 2 to 4 days, reduce maximum Enhanced Vegetation Index by 0.4% to 8.3%, and reduce annual accumulated Enhanced Vegetation Index by 1.0% to 5.6% in 2050 under Shared Socioeconomic Pathway 5-8.5 scenario. Our findings highlight the imperative need for strategic surface ozone regulation to optimize vegetation health and maximize the capacity for carbon sequestration.

Yin, Hao [Vanderbilt Univ., Nashville, TN (United ↗

Polymerization of the backbone of the pectic polysaccharide rhamnogalacturonan I

Rhamnogalacturonan I (RG-I) is a major plant cell wall pectic polysaccharide defined by its repeating disaccharide backbone structure of [4)-α-d-GalA- (1,2)-α-l-Rha-(1,]. A family of RG-I:Rhamnosyltransferases (RRT) has previously been identified, but synthesis of the RG-I backbone has not been demonstrated in vitro because the identity of Rhamnogalacturonan I:Galaturonosyltransferase (RG-I:GalAT) was unknown. Here a putative glycosyltransferase, At1g28240/MUCI70, is shown to be an RG-I:GalAT. The name RGGAT1 is proposed to reflect the catalytic activity of this enzyme. When incubated together with the rhamnosyltransferase RRT4, the combined activities of RGGAT1 and RRT4 result in elongation of RG-I acceptors in vitro into a polymeric product. RGGAT1 is a member of a new GT family categorized as GT116, which does not group into existing GT-A clades and is phylogenetically distinct from the GALACTURONOSYLTRANSFERASE (GAUT) family of GalA transferases that synthesize the backbone of the pectin homogalacturonan. RGGAT1 has a predicted GT-A fold structure but employs a metal-independent catalytic mechanism that is rare among glycosyltransferases with this fold type. Furthermore, the identification of RGGAT1 and the 8-member Arabidopsis GT116 family provides a new avenue for studying the mechanism of RG-I synthesis and the function of RG-I in plants.

59 BASIC BIOLOGICAL SCIENCES↗