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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Synergistic Interactions During Co-Hydrothermal Liquefaction of Food Waste and Biomass Model Compounds for Increased Sustainable Aviation Fuel Production

Hydrothermal liquefaction (HTL) of lignocellulosic biomass is plagued with low biocrude yields owing to the tendency of highly reactive oxygenated intermediates to condense to form biochars. By contrast, the high protein content in food waste is comprised of substantial nitrogen species, which are known to interact strongly with oxygenates through Maillard, amide, and peptide bond formation reactions. Co-feeding food waste and lignocellulose opens new reaction pathways for biocrude formation but is currently poorly understood. This work evaluated the molecular level interactions between food waste and lignocellulose model compounds and the corresponding effect on product yields and quality. Food waste–cellulose and food waste–xylan feedstock blends achieved maximum biocrude carbon yield improvements of 12.2% and 10.1%, respectively, relative to a simple linear model that interpolates between the yields of the pure feedstocks. Increases in biocrude yield were balanced by corresponding decreases in char yield, indicating synergistic interactions between the feeds during HTL. Biocrude volatility analysis revealed that increased biocrude yield preferentially benefitted the jet fuel fraction, which comprised up to 22.6% of the total carbon yield for food waste–cellulose blends. Biocrude and char were analyzed using GC–MS and FT-IR spectroscopy to investigate the source of synergistic trends and provide greater mechanistic understanding. Key cofeeding effects included the promotion of retro-aldol condensation reactions and trans-esterification of fatty acids, sequestering carbon in the biocrude phase via the inhibition of char formation while increasing biocrude volatility toward jet fuel-range compounds. These results indicate the potential for judicious selection of HTL cofeeds to increase both biocrude yield and selectivity to desired fuel precursors, including sustainable aviation fuel.

Maillard reaction↗
DOE OSTI2025

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating the Variation in Solvation Interactions of Choline Chloride-Based Deep Eutectic Solvents Formed Using Different Hydrogen Bond Donors

Choline chloride-based deep eutectic solvents (DESs) have gained widespread recognition as green solvents in catalysis and separation science as their designer properties permit solvation properties to be modulated by the choice of the hydrogen bond donor (HBD) as well as its molar ratio. Despite being one of the most popular classes of DESs, very little is currently understood regarding how their solvation characteristics differ among themselves as well as from other classes of DESs. Previous studies have shown that the catalytic activity, extraction efficiency, and solubilities of natural compounds can be influenced by the type of choline salt and HBD, but no study has systematically related these parameters with its solvation properties. In this study, inverse gas chromatography was employed for the first time to study the individual solvation characteristics of a diverse range of choline chloride and acetate-based DESs composed of amides, diols, organic acids, and carbohydrates. Furthermore, hydrogen bond acidity was found to be a dominant interaction for all DESs, especially those composed of organic acid HBDs. DESs composed of isomers of butane diol and hexane diol as HBDs exhibited higher hydrogen bond basicity and dispersive-type interactions compared to those composed of urea, acetamide, and organic acids with the position of the hydroxyl functional group influencing their solvation interactions. Choline acetate-based DESs exhibited lower dipolarity and stronger hydrogen bond basicity and dispersive-type interactions compared to choline chloride DESs. The solvation models developed in this study were used to interpret and explain DES behavior in previously reported studies involving catalysis, organic synthesis, and extractions demonstrating that the measured solute–solvent interactions can serve to predict the performance of choline chloride-based DESs when used in various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Quaternary Charge-Transfer Complex Enables Photoenzymatic Intermolecular Hydroalkylation of Olefins

Intermolecular C–C bond-forming reactions are underdeveloped transformations in the field of biocatalysis. Here we report a photoenzymatic intermolecular hydroalkylation of olefins catalyzed by flavin-dependent ‘ene’-reductases. Radical initiation occurs via photoexcitation of a rare high-order enzyme-templated charge-transfer complex that forms between an alkene, α-chloroamide, and flavin hydroquinone. This unique mechanism ensures that radical formation only occurs when both substrates are present within the protein active site. Here, this active site can control the radical terminating hydrogen atom transfer, enabling the synthesis of enantioenriched γ-stereogenic amides. This work highlights the potential for photoenzymatic catalysis to enable new biocatalytic transformations via previously unknown electron transfer mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enzymatic Nitrogen Insertion into Unactivated C–H Bonds

Selective functionalization of aliphatic C–H bonds, ubiquitous in molecular structures, could allow ready access to diverse chemical products. While enzymatic oxygenation of C–H bonds is well established, the analogous enzymatic nitrogen functionalization is still unknown; nature is reliant on pre-oxidized compounds for nitrogen incorporation. Likewise, synthetic methods for selective nitrogen derivatization of unbiased C–H bonds remain elusive. In this work, new-to-nature heme-containing nitrene transferases were used as starting points for the directed evolution of enzymes to selectively aminate and amidate unactivated C(sp3)–H sites. The desymmetrization of methyl- and ethylcyclohexane with divergent site selectivity is offered as demonstration. The evolved enzymes in these lineages are highly promiscuous and show activity towards a wide array of substrates, providing a foundation for further evolution of nitrene transferase function. Computational studies and kinetic isotope effects (KIEs) are consistent with a stepwise radical pathway involving an irreversible, enantiodetermining hydrogen atom transfer (HAT), followed by a lower-barrier diastereoselectivity determining radical rebound step. In-enzyme molecular dynamics (MD) simulations reveal a predominantly hydrophobic pocket with favorable dispersion interactions with the substrate. Here, by offering a direct path from saturated precursors, these enzymes present a new biochemical logic for accessing nitrogen-containing compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Two-Coordinate Coinage Metal Complexes as Solar Photosensitizers

Generating a sustainable fuel from sunlight plays an important role in meeting the energy demands of the modern age. Herein we report two-coordinate carbene-metal-amide (cMa, M = Cu(I) and Au(I)) complexes can be used as sensitizers to promote the light driven reduction of water to hydrogen. The cMa complexes studied here absorb visible photons (ε vis > 10 3 M -1 cm -1 ), maintain long excited state lifetimes (τ ~ 0.2-1 μs) and perform stable photo-induced charge transfer to a target substrate with high photoreducing potential (E +/* up to 2.33 V vs. Fc +/o based on a Rehm-Weller analysis). We pair these coinage metal complexes with a cobalt-glyoxime electrocatalyst to photocatalytically generate hydrogen and compare the performance of the copper- and gold-based cMa complexes. We also find that these two-coordinate complexes presented can perform photo-driven hydrogen production from water without the addition of the cobalt-glyoxime electrocatalyst. In this “catalyst free” system the cMa sensitizer partially decomposes to give metal nanoparticles that catalyze water reduction. Furthermore, this work identifies two-coordinate coinage metal complexes as promising abundant metal, solar fuels photosensitizers that offer exceptional tunability and photoredox properties.

14 SOLAR ENERGY↗
DOE OSTI2023

Enhancing Substrate–Metal Catalyst Affinity via Hydrogen Bonding: Pd(II)-Catalyzed β-C(sp 3 )–H Bromination of Free Carboxylic Acids

Achieving sufficient substrate-metal catalyst affinity is a fundamental challenge for developing synthetically useful C–H activation reactions of weakly coordinating native substrates. While hydrogen bonding has been harnessed to bias site selectivity in existing C(sp 2 )–H activation reactions, the potential for designing catalysts with hydrogen bond donors (HBDs) to enhance catalyst substrate affinity, and thereby facilitate otherwise unreactive C(sp 3 )–H activation, remains to be demonstrated. Herein, we report the discovery of a ligand scaffold containing a remote amide motif that can form a favorable meta-macrocyclic hydrogen bonding interaction with the aliphatic acid substrate. The utility of this ligand scaffold is demonstrated through the development of an unprecedented C(sp 3 )–H bromination of α-tertiary and α-quaternary free carboxylic acids, which proceeds in exceedingly high mono-selectivity. Furthermore, the geometric relationship of the NHAc hydrogen bond donor and the coordinating quinoline ligand is crucial for forming the meta-macrocyclophane-like hydrogen bonding interaction, providing a guideline for the future design of catalysts employing secondary interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Luminescent Bimetallic Two-Coordinate Gold(I) Complexes Utilizing Janus Carbenes

A series of bimetallic carbene-metal-amide (cMa) complexes have been prepared with bridging biscarbene ligands to serve as a model for the design of luminescent materials with large oscillator strengths and small energy differences between the singlet and triplet states (ΔE ST ). The complexes have a general structure (R 2 N)Au(:carbene—carbene:)Au(NR 2 ). The bimetallic complexes show solvation-dependent absorption and emission that is analyzed in detail. It is found that the molar absorptivity of the bimetallic complexes is correlated with the energy barrier to rotation of the metal–ligand bond. The bimetallic cMa complexes also exhibit short emission lifetimes (τ = 200–300 ns) with high photoluminescence efficiencies (Φ PL > 95%). The radiative rates of bimetallic cMa complexes are 3–4 times faster than that of the corresponding monometallic complexes. Analysis of temperature-dependent luminescence data indicates that the lifetime for the singlet state (τS 1 ) of bimetallic cMa complexes is near 12 ns with a ΔE ST of 40–50 meV. Here the presented compounds provide a general design for cMa complexes to achieve small values for ΔE ST while retaining high radiative rates. Solution-processed organic light-emitting devices (OLEDs) made using two of the complexes as luminescent dopants show high efficiency and low roll-off at high luminance.

14 SOLAR ENERGY↗
DOE OSTI2024

Heterogeneous Fe-N-C Catalyst for Aerobic Dehydrogenation of Hydrazones to Diazo Compounds Used for Carbene Transfer

Organic diazo compounds are versatile reagents in chemical synthesis and would benefit from improved synthetic accessibility, especially for larger scale applications. Here, we report a mild method for the synthesis of diazo compounds from hydrazones using a heterogeneous Fe-N-C catalyst, which has Fe ions dispersed within a graphitic nitrogen-doped carbon support. The reactions proceed readily at room temperature using O 2 (1 atm) as the oxidant. Aryl diazoesters, ketones, and amides are accessible, in addition to less stable diaryl diazo compounds. Initial-rate data show that the Fe-N-C catalyst achieves faster rates than a heterogeneous Pt/C catalyst. The oxidative dehydrogenation of hydrazones may be performed in tandem with Rh-catalyzed enantioselective C–H insertion and cyclopropanation of alkenes, without requiring isolation of the diazo intermediate. Furthermore, this sequence is showcased by using a flow reactor for continuous synthesis of diazo compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Field-Coupled Water Splitting with Metal-Free Donor–Acceptor Covalent Organic-Framework Junctions

Advancing metal-free electrocatalysts for hydrogen and oxygen evolution reactions (HER/OER) across acidic and alkaline media requires coordinated control of intermediate binding thermodynamics, interfacial charge delivery, and near-electrode transport dynamics. Here, we design amide-linked benzene–triazine covalent organic frameworks (BTA/TzTA-Hz COFs) and integrate them with carbon nanotubes (CNTs) to form COF–CNT junctions that establish a built-in interfacial electric field. Density functional theory (DFT) and electrostatic potential maps indicate complementary active motifs, with benzene-proximal fragments associated with HER and triazine-proximal motifs associated with OER. CNT integration shifts the contact-potential difference by ≈0.20 V, while operando electrochemical impedance spectroscopy suggests partially separable high-frequency junction-charging and lower-frequency Faradaic/transport responses. A 300 mT static magnetic field lowers the HER and OER overpotentials by tens of millivolts. Under anodic bias, the effective interfacial charging capacitance increases, and Mott–Schottky analysis shows an apparent ∼0.15 V flat-band shift with an essentially unchanged slope. Together, these observations are consistent with field-perturbed interfacial charging and altered bias partitioning. Field-dependent impedance and bubble imaging are consistent with magnetohydrodynamic convection that promotes bubble detachment and near-electrode mass transport for both half-reactions, and they reveal an OER-specific high-frequency perturbation under anodic bias. Under field, the heterostructure reaches an OER onset overpotential of ∼261 mV and requires an overpotential of 366 mV at 10 mA cm –2 in alkaline electrolyte. These results illustrate how reticular-framework chemistry, junction engineering, and both built-in and applied fields can program reactivity through interfacial electrostatics and near-electrode transport in organic-framework electrocatalysts.

Garcia-Enriquez, Lissette [Univ. of Texas at El Pa↗
DOE OSTI2021

An Improved Zhang's Dynamic Water Balance Model Using Budyko-Based Snow Representation for Better Streamflow Predictions

Understanding the water balance of a catchment in relation to its regional climate forcings and catchment characteristics is critical for predicting current and future water resources amid changing climate and land cover. This study intends to improve Zhang's monthly water balance model (a physics-based conceptual hydrologic model) that reflects the physical partitioning process of the hydrological cycle at the basin level based on regional climate and catchment characteristics. The existing model does not include snow process and has confronted evident limitations in snow-affected areas, which is a critical aspect since snowmelt water has been a significant source of water resources for many regions, especially in the temperate and frigid zones. We introduce a snow module based on surface energy balance and Budyko-limits on melting and combine it with the existing water balance equations. Moreover, monthly parameterization is applied to the model to better explain the time-varying hydrological characteristics of a catchment. The proposed model involves five different monthly parameters, which determine the physical partitioning process of the hydrological cycle, and they are regionally calibrated and validated under Budyko-type constraints. The model is applied to 1,210 basins across the continental United States (CONUS), and the simulated streamflow is compared to the observed data. The proposed model significantly outperformed the original model, improving the median NSE by 31% (from 0.51 to 0.67) and increasing the number of catchments with an acceptable NSE by 58%. The spatial variability of the basin characteristics across the CONUS is also investigated based on the calibrated parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Scaling Individual Tree Transpiration With Thermal Cameras Reveals Interspecies Differences to Drought Vulnerability

Abstract Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements ( R 2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m 2 (Niwot) and 52.8 W/m 2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements.

Javadian, Mostafa↗
DOE OSTI2025

Quantifying Moisture Sources of Arctic Atmospheric Rivers During the Recent Historical Period

Atmospheric rivers (ARs), filaments of intense atmospheric moisture transport, play a significant role in delivering moisture poleward into the Arctic and triggering weather extremes. Although previous studies have focused on large‐scale circulations driving these events, this study investigates ARs through attributing their moisture sources using the Community Atmosphere Model version 5 (CAM5) with moisture‐tagging capability. Examining ARs in the Atlantic and Pacific sectors of the Arctic separately revealed distinct contributions from remote versus local, and ocean versus land, moisture sources. Unlike non‐AR events, Arctic ARs primarily draw moisture from their respective ocean basins in lower‐latitude regions during the cold season, and shift to land sources in the warm season. Cold‐season ARs in the Atlantic and Pacific sectors source 73.2% and 85.3% of their moisture from their respective ocean basins at lower latitudes, however warm‐season contributions decrease to 41.3% and 29.4%. In contrast, mid‐ and high‐latitude continents combined contribute 40.1% and 51.3% in the warm season. Trajectory clustering analysis shows that AR moisture sources depend on both their genesis regions and transport pathways. In recent decades, the Arctic has experienced a moistening trend in both the cold and warm seasons. Our results suggest that local and remote sources equally drive the observed cold‐season moistening, whereas remote sources predominantly drive the warm‐season moistening. A better understanding of Arctic AR moisture sources under current climate conditions provides valuable insights into their potential future changes amid the projected heterogeneous northern hemispheric warming.

Arctic↗
DOE OSTI2025

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗
DOE OSTI2020

Switchable encapsulation of polysulfides in the transition between sulfur and lithium sulfide

Encapsulation strategies are widely used for alleviating dissolution and diffusion of polysulfides, but they experience nonrecoverable structural failure arising from the repetitive severe volume change during lithium-sulfur battery cycling. Here we report a methodology to construct an electrochemically recoverable protective layer of polysulfides using an electrolyte additive. The additive nitrogen-doped carbon dots maintain their “dissolved” status in the electrolyte at the full charge state, and some of them function as active sites for lithium sulfide growth at the full discharge state. When polysulfides are present amid the transition between sulfur and lithium sulfide, nitrogen-doped carbon dots become highly reactive with polysulfides to form a solid and recoverable polysulfide-encapsulating layer. This design skilfully avoids structural failure and efficiently suppresses polysulfide shuttling. The sulfur cathode delivers a high reversible capacity of 891 mAh g -1 at 0.5 C with 99.5% coulombic efficiency and cycling stability up to 1000 cycles at 2 C.

25 ENERGY STORAGE↗
DOE OSTI2023

Elucidating the molecular programming of a nonlinear non-ribosomal peptide synthetase responsible for fungal siderophore biosynthesis

Abstract Siderophores belonging to the ferrichrome family are essential for the viability of fungal species and play a key role for virulence of numerous pathogenic fungi. Despite their biological significance, our understanding of how these iron-chelating cyclic hexapeptides are assembled by non-ribosomal peptide synthetase (NRPS) enzymes remains poorly understood, primarily due to the nonlinearity exhibited by the domain architecture. Herein, we report the biochemical characterization of the SidC NRPS, responsible for construction of the intracellular siderophore ferricrocin. In vitro reconstitution of purified SidC reveals its ability to produce ferricrocin and its structural variant, ferrichrome. Application of intact protein mass spectrometry uncovers several non-canonical events during peptidyl siderophore biosynthesis, including inter-modular loading of amino acid substrates and an adenylation domain capable of poly-amide bond formation. This work expands the scope of NRPS programming, allows biosynthetic assignment of ferrichrome NRPSs, and sets the stage for reprogramming towards novel hydroxamate scaffolds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors

Abstract Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m 2 /g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm 2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H 2 SO 4 . This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation

Abstract Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates an EC mechanism, an interfacial electron transfer ( E step) followed by a solution reaction ( C step), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns the EC mechanism’s presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of the C step spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗