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DOE OSTI2023

Method for conversion of diols to olefin products

A method for converting a diol in solution to an olefin fraction, the method comprising: (i) reacting a diol of the formula HO—R—OH in solution with a carbonyl-containing molecule of the formula: in the presence of an acid catalyst to result in a dioxolane molecule of the formula: wherein R is a hydrocarbon linker containing 1-12 carbon atoms, and R 1 and R 2 are independently selected from hydrogen atom and hydrocarbon groups containing 1-12 carbon atoms, wherein R 1 and R 2 optionally interconnect; (ii) removing the dioxolane molecule from the solution by phase separation; and (iii) contacting the dioxolane molecule with a metal-loaded zeolite at a temperature of 100-500° C. to convert the dioxolane molecule to an olefin fraction.

Li, Zhenglong↗

DOE OSTI2024

Electromagnetic field-assisted method for chemical conversion

Embodiments relate to methods for enhancing chemical conversions. One or more embodiments relate to a method for enhancing a multi-step chemical conversion reaction. The method includes providing a reactant mixture comprising one or more reacting specie(s); and providing a catalyst or sorbent comprising one or more support materials and one or more deposited catalytically active materials. The method further includes applying an electromagnetic field with a prescribed power, frequency, and pulsing strategy specific to interactions of reactant species and an electromagnetic field with at least one of the support materials, sorbent, and catalytically active materials in a particular chemical reaction.

Shekhawat, Dushyant↗

DOE OSTI2023

Methods for the conversion of fermentable sugars to ethanol

Methods and systems for the enhancement of bioproduct process yields. The present invention provides systems and methods for improvement of the carbon conversion efficiency by yeast of an organic substrate such as a fermentable sugar to a fermentation product such as ethanol. Exemplary yield-increasing/growth-inhibitory compounds include tyrosol (TyrOH), 2-phenylethanol (PheOH), and tryptophol (TrpOH). Immobilization of the yeast, such as in a porous bead or pellet, can further increase yield. Exemplary immobilization included immobilization in calcium alginate beads. The system and methods taught herein demonstrate that product yield such as ethanol yield can be improved by adding yeast yield-increasing/growth-inhibitory molecules to reduce cell growth of yeast species, such as S. cerevisiae , suggesting a strategy to improve the yield of ethanol and other yeast fermentation products by manipulating native biological control systems.

Reardon, Kenneth F.↗

DOE OSTI2021

Plastic waste upcycling toward a circular economy

Large amounts of plastics are discarded worldwide each year, leading to a significant mass of waste in landfills and pollution to soil, air, and waterways. Upcycling is an efficient way to transform plastic waste into high-value products and can significantly lessen the environmental impact of plastic production/consumption. In this article, current advances and future directions in plastic waste upcycling technologies are discussed. In particular, this review focuses on the production of high-value materials from plastic waste conversion methods, including pyrolysis, gasification, photoreforming, and mechanical reprocessing. Plastic waste compositions, conversion products, reaction mechanisms, catalyst selection, conversion efficiencies, polymer design, and polymer modification are also explored. Furthermore, the main challenges facing the adoption and scale-up of these technologies are highlighted. Suggestions are given for focusing future research and development to increase the efficiency of upcycling practices.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Reducing roughness and improving efficiency of MAPbI3 perovskite solar cells made by high-throughput photonic curing

For perovskite solar cells (PSCs) to be commercially viable, the slow and energy-insufficient thermal annealing step must be eliminated. Among the photo-irradiation methods proposed to replace thermal annealing, photonic curing is the fastest conversion method. Photonic curing delivers short (20 μs to 100 ms) but intense light pulses from a broadband (200-1500 nm) xenon flash lamp, making it the only method to convert perovskite under 20 ms. This processing time can be extrapolated to a roll-to-roll web speed of 40 m/min based on laboratory processing conditions. However, most reported PSCs made by photonic curing under 1 second have inferior performance (~10% PCE). Although SEM images show dense and pinhole-free perovskite films, AFM images indicate secondary wavy features of 500 nm-wide ridge and 80 nm-deep trenches on photonically cured perovskite films, the existence of which correlates with poor device performance. We suggest that this morphology feature is produced by volatile solvent evaporation during the fast photonic curing process. Two approaches have been made to remedy this issue: (1) adding CH2I2 as the third solvent in the conventional DMF-DMSO system and (2) applying a controlled air-blowing step before photonic curing to remove excess solvent further. Combining these two approaches produces photonically- cured perovskite films with a comparable film roughness and device performance. Alkyl halide additives have been reported to enhance PSC performance by modulated solvent-solute interactions and C-X (X = Cl, Br, and I) cleavage. Photonic curing can cleave CH2I2, producing disassociated iodide ions to replenish iodine loss induced by photonic curing, which is confirmed by EDX. As a co-solvent, the high boiling point of CH2I2 can also make the solvent less volatile, reducing surface roughness in photonically cured perovskite films. Additionally, photonically-cured perovskite films have longer PL lifetimes and a higher recombination resistance compared to thermally-annealed counterparts. As a result, we demonstrate that photonic curing is a suitable method to replace thermal annealing in high-throughput PSC fabrication.

14 SOLAR ENERGY↗

DOE OSTI2026

Deep Learning enabled spectral energy conversion for in situ exposure measurements

A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2025

Theoretical and Experimental Insights into CO 2 Capture and Methanation over Amine-Grafted Ru-Based Catalysts

Carbon capture and storage (CCS) technologies, along with CO 2 capture and conversion methods, have emerged as crucial research areas to address rising CO 2 emissions. In this study, we seek to understand the mechanistic role of amines in enabling lower-energy pathways for CO 2 conversion. Our research focuses on the development and analysis of dual-functional materials (DFMs) engineered for the reactive capture and conversion (RCC) of CO 2 into methane, utilizing Ru catalysts grafted with amine groups. We employ Density Functional Theory (DFT) calculations using methylamine as a model amine to investigate the impact of amine groups on CO 2 methanation on a Ru(0001) surface, both in the presence and absence of amine groups. The amine ligand alters the carbon coordination environment, promoting direct C–O dissociation and potentially destabilizing the CO* adsorbate, thereby reducing the risk of CO poisoning. Additionally, we observe a preference for hydrogenation, although it becomes more energetically uphill in the amine-bound scenario. Our experiments, however, report similar CO 2 conversion and CH 4 production rates over the synthesized catalysts “Ru/TiO 2 ” and the amine (N-(2-aminoethyl)-3-aminoproplytrimethoxysilane (“diaminosilane”)) deposited catalyst “Diamine−Ru/TiO 2 ”. By constructing comparative reaction-free energy diagrams and performing microkinetic modeling (MKM) simulations, we link our theoretical findings with experimentally observed CO 2 uptake, conversion, and methane production rates. A microkinetic model was employed to investigate the anomaly, showing reduced amine–carbon complex coverage and increased CO 2 coverage at all temperatures. The MKM simulations consistently confirmed these trends. In conclusion, this comprehensive approach offers key insights into the role of the amine-CO 2 bond in methanation, highlighting a pathway toward lower-energy, more efficient CO 2 capture and conversion processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Electrically interfaced Brillouin-active waveguide for microwave photonic measurements

New strategies for converting signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Traditional approaches to optical-to-microwave transduction typically perturb or destroy the information encoded on intensity of the light field, eliminating the possibility for further processing or distribution of these signals. In this paper, we introduce an optical-to-microwave conversion method that allows for both detection and spectral analysis of microwave photonic signals without degradation of their information content. This functionality is demonstrated using an optomechanical waveguide integrated with a piezoelectric transducer. Efficient electromechanical and optomechanical coupling within this system permits bidirectional optical-to-microwave conversion with a quantum efficiency of up to -54.16 dB. Leveraging the preservation of the optical field envelope in intramodal Brillouin scattering, we demonstrate a multi-channel microwave photonic filter by transmitting an optical signal through a series of electro-optomechanical waveguide segments, each with distinct resonance frequencies. Such electro-optomechanical systems could offer flexible strategies for remote sensing, channelization, and spectrum analysis in microwave photonics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Learning local equivariant representations for large-scale atomistic dynamics

Abstract A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Systems and methods for biological conversion of carbon dioxide pollutants into useful products

Methods and systems to achieve clean fuel processing systems in which carbon dioxide emissions (1) from sources (2) may be processed in at least one processing reactor (4) containing a plurality of chemoautotrophic bacteria (5) which can convert the carbon dioxide emissions into biomass (6) which may then be used for various products (21) such as biofuels, fertilizer, feedstock, or the like. Sulfate reducing bacteria (13) may be used to supply sulfur containing compounds to the chemoautotrophic bacteria (5).

09 BIOMASS FUELS↗

DOE OSTI2026

Opportunities and challenges in thermochemical conversion of municipal solid waste: A comprehensive review

Recent advancements in thermochemical conversion processes have elucidated new pathways for converting municipal solid waste into valuable resources. This review explores the primary thermochemical conversion methods, including combustion, gasification, pyrolysis, torrefaction, hydrothermal carbonization, and hydrothermal liquefaction, emphasizing their potential roles in waste management and energy recovery. Key challenges including feedstock variability, ash behavior, and scale-up limitations are discussed alongside opportunities for hybrid systems and circular economy integration. A comparative analysis of research publications indicates a significant focus on thermochemical pathways within the broader context of municipal solid waste research, underscoring the growing interest in these technologies. Recent advancements in each thermochemical process, alongside their operational, technical, and economic challenges, are discussed. Comparative data reveal that torrefaction enhances the hydrophobicity and grindability of municipal solid waste components, though its energy densification benefits are more modest than those observed in biomass. Hydrothermal carbonization and liquefaction are highlighted for their ability to process high-moisture and heterogeneous waste streams. The review also synthesizes recent findings on reactor configurations, emissions control, and synergistic effects in co-processing municipal solid waste fractions. The findings underscore the importance of developing standardized protocols for municipal solid waste characterization and the need for innovative hybrid systems to improve efficiency.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Abstract The poor electrical conductivity of two‐dimensional (2D) crystalline frameworks greatly limits their utilization in optoelectronics and sensor technology. Herein, we describe a conductive metallophthalocyanine‐based NiPc‐CoTAA framework with cobalt(II) tetraaza[14]annulene linkages. The high conjugation across the whole network combined with densely stacked metallophthalocyanine units endows this material with high electrical conductivity, which can be greatly enhanced by doping with iodine. The NiPc‐CoTAA framework was also fabricated as thin films with different thicknesses from 100 to 1000 nm by the steam‐assisted conversion method. These films enabled the detection of low‐concentration gases and exhibited remarkable sensitivity and stability. This study indicates the enormous potential of metallophthalocyanine‐based conductive frameworks in advanced stand‐off chemical sensors and provides a general strategy through tailor‐make molecular design to develop sensitive and stable chemical sensors for the detection of low‐concentration gases.

Yue, Yan↗

DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Yue, Yan↗

DOE OSTI2020

Electrochemical Reduction Selectivity of Crotonaldehyde on Copper

Lignocellulosic waste is a potential feedstock for the generation of fuels and commodity chemicals, but existing conversion methods are too cost-intensive to be viable long-term solutions. Electrochemical reductions are promising for decentralized biomass valorization due to their modular scaling and capacity to run intermittently and without high temperatures or pressures. Using crotonaldehyde as a multi-functional model compound for the many partially unsaturated oxygenates found in processed biomass, we here demonstrate the production of butanal, butanol, butene, and butane (variously useful as commodity chemicals and major components of liquified petroleum gas) under ambient conditions by reductive bulk electrolysis with a copper mesh working electrode. We identify an optimum potential for reduced organic production under the reaction conditions and compare product distributions from reductions of intermediate species to further propose branching reaction pathways. Though butanal is typically the most abundant product from crotonaldehyde reduction, most of the butene and butane appear to result from a pathway involving initial reduction of the aldehyde group. We discuss evidence that selectivity is driven by interplay between crotonaldehyde reduction, local pH shifts due to the hydrogen evolution reaction, and changes in site reactivity and availability due to electrode fouling. This demonstration of model electrochemical biomass valorization also serves to inform further exploration into reduction of multi-functional molecules and electrochemical biomass processing in general.

biomass↗

DOE OSTI2020

Measuring multiple cosmogenic nuclides in glacial cobbles sheds light on Greenland Ice Sheet processes

The behavior of the Greenland Ice Sheet during the Pleistocene remains uncertain due to the paucity of evidence predating the Last Glacial Maximum. In this study, we employ a novel approach, cosmogenic nuclide analysis of individual subglacially-derived cobbles, which allows us to make inferences about ice sheet processes and subglacial erosion. From three locations in western Greenland, we collected 86 cobbles from the current ice sheet margin and nine cobbles exposed on the modern proglacial land surface. We measured the concentration of in situ 10 Be in all cobbles (n = 95) and 26 Al and 14 C in a subset (n = 14). Cobbles deposited during Holocene retreat have 10 Be exposure ages generally consistent with the timing of ice retreat determined by other methods. Conversely, most of the 86 subglacial cobbles contain very low concentrations of 10 Be (median 1.0×10 3 atoms g –1 ), although several have ~10 4 and one has ~10 5 atoms g –1 . The low concentrations of 10 Be in most subglacial cobbles imply that their source areas under the Greenland Ice Sheet are deeply eroded, preserving minimal evidence of surface or near-surface exposure. The presence of measurable 14 C in ten of the cobbles requires that they experienced cosmogenic nuclide production within the past ~30 ka; however, 14 C/ 10 Be ratios of ~6 suggest that nuclide production occurred during shielding by overlying material. Only two of the 86 subglacial cobbles definitively have cosmogenic nuclide concentrations consistent with prior surface exposure. Overall, isotopic analysis of subglacial cobbles indicates that much of western Greenland's subglacial landscape is characterized by deep erosion and minimal subaerial exposure.

58 GEOSCIENCES↗

DOE OSTI2023

Data-driven precision determination of the material budget in ALICE

The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

On the prescription of boundary conditions for nonlocal Poisson's and peridynamics models

We introduce a technique to automatically convert local boundary conditions into nonlocal volume constraints for nonlocal Poisson’s and peridynamic models. The proposed strategy is based on the approximation of nonlocal Dirichlet or Neumann data with a local solution obtained by using available boundary, local data. The corresponding nonlocal solution converges quadratically to the local solution as the nonlocal horizon vanishes, making the proposed technique asymptotically compatible. The proposed conversion method does not have any geometry or dimensionality constraints and its computational cost is negligible, compared to the numerical solution of the nonlocal equation. The consistency of the method and its quadratic convergence with respect to the horizon is illustrated by several two-dimensional numerical experiments conducted by meshfree discretization for both the Poisson’s problem and the linear peridynamic solid model.

97 MATHEMATICS AND COMPUTING↗