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At least 541 records · Page 30

Oxidative coupling of methane (OCM) conversion into C 2 products through a CO 2 /O 2 co-transport membrane reactor

Oxidative coupling of methane (OCM), which transforms CH 4 into C 2 products (C 2 H 6 and C 2 H 4 ) with molecular O 2 as the oxidant, is one of the most studied direct methane conversions (DMCs). However, a major technical hurdle to the OCM process is to achieve high CH 4 conversion at high C 2 (C 2 H 6 and C 2 H 4 ) selectivity. One rudimentary cause for this “tradeoff” behavior is the high chemical reactivity of the products (C 2 H 6 or C 2 H 4 ), which can be re-oxidized by O 2 . To overcome this thermodynamic challenge, minimizing the oxidizing power of the oxidant and lowering the local oxygen partial pressure are keys. Here, In this work, we demonstrate a new membrane reactor that capture CO 2 /O 2 from a flue gas and uses it for OCM conversion. The results show that the co-captured CO 2 /O 2 mixture converts CH 4 into C 2 H 6 in the presence of a 2%Mn–5%Na 2 WO 4 /SiO 2 catalyst, followed by thermal cracking of C 2 H 6 into C 2 H 4 and H 2 . The presence of CO 2 decreases the local partial pressure of O 2 , thus reducing the propensity of C 2 -products re-oxidation and leading to a higher C 2 selectivity. We show that a small button-type membrane reactor can achieve 12% C 2 yield with ~57% C 2 -selectivity using a diluted CH 4 -Ar mixture as the feedstock. We expect higher C 2 yield with tubular plug-flow membrane reactors in the future. We also highlight the unique advantage of the membrane reactor in intensifying CO 2 capture from both flue gas and OCM purification process into one single step.

42 ENGINEERING↗

Synthetic and Mechanistic Implications of Chlorine Photoelimination in Nickel/Photoredox C(sp 3 )–H Cross-Coupling

In recent years, the development of light-driven reactions has contributed numerous advances in synthetic organic chemistry. A particularly active research area combines photoredox catalysis with nickel catalysis to accomplish otherwise inaccessible cross-coupling reactions. In these reactions, the photoredox catalyst absorbs light to generate an electronically excited charge-transfer state that can engage in electron or energy transfer with a substrate and the nickel catalyst. Our group questioned whether photoinduced activation of the nickel catalyst itself could also contribute new approaches to cross-coupling. Over the past 5 years, we have sought to advance this hypothesis for the development of a suite of mild and site-selective C(sp 3 )–H cross-coupling reactions with chloride-containing coupling partners via photoelimination of a Ni–Cl bond. On the basis of a report from the Nocera laboratory, we reasoned that photolysis of a Ni(III) aryl chloride species, generated by single-electron oxidation of a typical Ni(II) intermediate in cross-coupling, might allow for the catalytic generation of chlorine atoms. Combining this with the ability of Ni(II) to accept alkyl radicals, we hypothesized that photocatalytically generated chlorine atoms could mediate hydrogen atom transfer (HAT) with C(sp 3 )–H bonds to generate a substrate-derived alkyl radical that is captured by the Ni center in cross-coupling. A photoredox catalyst was envisioned to promote the necessary single-electron oxidation and reduction of the Ni catalyst to facilitate an overall redox-neutral process. Overall, this strategy would offer a visible-light-driven mechanism for chlorine radical formation enabled by the sequential capture of two photons. As an initial demonstration, we developed a Ni/photoredox-catalyzed α-oxy C(sp 3 )–H arylation of cyclic and acyclic ethers. This method was extended to a mild formylation of abundant and complex aryl chlorides through selective 2-functionalization of 1,3-dioxolane. Seeking to develop a suite of reactions that introduce carbon at all different oxidation states, we explored C(sp 3 )–H cross-coupling with trimethyl orthoformate, a common laboratory solvent. We found that trimethyl orthoformate serves as a source of methyl radical for a methylation reaction via β-scission from a tertiary radical generated upon chlorine-mediated HAT. Since chlorine radical is capable of abstracting unactivated C(sp 3 )–H bonds, our efforts have also been directed at cross-coupling with a range of feedstock chemicals, such as alkanes and toluenes, along with late-stage intermediates, using chloroformates as coupling partners. Overall, this platform enables access to valuable synthetic transformations with (hetero)aryl chlorides, which despite being the most ubiquitous and inexpensive aryl halide coupling partners, are rarely reactive in Ni/photoredox catalysis. Little is known about the photophysics and photochemistry of organometallic Ni complexes relevant to cross-coupling. We have conducted mechanistic investigations, including computational, spectroscopic, emission quenching, and stoichiometric oxidation studies, of Ni(II) aryl halide complexes common to Ni/photoredox reactions. These studies indicate that chlorine radical generation from excited Ni(III) is operative in the described C(sp 3 )–H functionalization methods. More generally, the studies illustrate that the photochemistry of cross-coupling catalysts cannot be ignored in metallaphotoredox reactions. We anticipate that further mechanistic understanding should facilitate catalyst design and lead to the development of new synthetic methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a Chemistry-Based Isotherm Model and Techno-Economic Optimization of a Moving Bed Process for CO2 Capture Using a Functionalized Metal-Organic Framework

Amine-appended metal-organic frameworks of the class Mg2(dobpdc) are promising candidates for efficient carbon capture in part due to their step-shaped CO2 adsorption behavior. However, the existing isotherm models are lacking as they are unable to capture the complicated chemisorption mechanisms which are still not well known for these materials. Here, a chemistry-based isotherm model is developed and fit to experimental CO2 adsorption data for dmpn-Mg2(dobpdc). Reactions for a cooperative adsorption mechanism are proposed, and the reaction pathway is optimally selected. The chemistry-based model shows an improvement in prediction by a factor of 6 when compared to a recent isotherm model in literature. A plant-wide model is developed for a moving bed based adsorber/desorber and techno-economic optimization is performed. For likely values of price and lifespan, the moving bed process gives a significant improvement in economics when compared to a fixed bed contactor process and a traditional MEA capture system.

carbon capture↗

Selective pseudocapacitive immobilization of REE elements on carbon based electrodes

Current extraction technologies for rare earth elements at ambient conditions are reagent and energy intensive, giving rise to significant quantities of secondary waste streams. Exploration of the removal of common cations from aqueous streams has been undertaken with carbon materials and have shown promising results. However, those promising materials have not been explored extensively for rare earth element capture from aqueous process streams. In this study, a carbon electrode was investigated for the adsorption and immobilization of REE elements from aqueous solutions. Cyclic voltammetry studies of the carbon electrode displayed a pseudocapacitive behavior where it was verified that cation adsorption is accompanied by an electron transfer process. Preliminary tests showed that a current density of 89.1 mA. g -1 , allowed for the pseudocapacitive adsorption (PSA) of Nd 3+ cation without the formation of rare earth hydroxides. Hence, the selective PSA of Nd 3+ was verified in an electrolyte solution with equimolar concentrations of Nd 3+ , Mg 2+ , Li + , Na + and K + , achieving separation factors of 8.6, 1.1, and 10.9 for Nd 3+ /Li + , Nd 3+ /Na + , and Nd 3+ /Mg 2+ , respectively. Analysis of the potential-time curves for the various cations suggests that storage of ions in the electrode involved pore-spacings rather than interlayer spacings and was corroborated by XRD analysis. Specific capacitance as high as >640 F.g -1 for Nd 3+ was also observed for the carbon electrode, with Faradaic efficiencies (FE) of > 20% for Nd 3+ and Mg 2+ , and > 9% for Na + . Furthermore, adsorption capacity of >125 mg g -1 after 4hrs of electrosorption was observed for Nd 3+ . In the presence of the Nd 3+ electrolyte, the electrode achieved increasing storage of Nd 3+ with >94% retention of Nd 3+ with a FE > 20% over 6 cycles between loading and releases in 1 M KCl solution. In conclusion, these preliminary results provide information and some guidance on the selective recovery of rare earth elements, such as Nd, in aqueous streams in the presence of competitive cations employing the use of carbon-based materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resolving extreme jet substructure

We study the effectiveness of theoretically-motivated high-level jet observables in the extreme context of jets with a large number of hard sub-jets (up to N = 8). Previous studies indicate that high-level observables are powerful, interpretable tools to probe jet substructure for N ≤ 3 hard sub-jets, but that deep neural networks trained on low-level jet constituents match or slightly exceed their performance. We extend this work for up to N = 8 hard sub-jets, using deep particle-flow networks (PFNs) and Transformer based networks to estimate a loose upper bound on the classification performance. A fully-connected neural network operating on a standard set of high-level jet observables, 135 N-subjetiness observables and jet mass, reach classification accuracy of 86.90%, but fall short of the PFN and Transformer models, which reach classification accuracies of 89.19% and 91.27% respectively, suggesting that the constituent networks utilize information not captured by the set of high-level observables. We then identify additional high-level observables which are able to narrow this gap, and utilize LASSO regularization for feature selection to identify and rank the most relevant observables and provide further insights into the learning strategies used by the constituent-based neural networks. The final model contains only 31 high-level observables and is able to match the performance of the PFN and approximate the performance of the Transformer model to within 2%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy cost savings and expected payback for Re-tuning the controls of US Army buildings

The Headquarters Department of the Army (HQDA) sponsored a study to determine the national impact of deploying the Re-tuning™ methodology in 5 buildings types that account for over 40% of the Army’s conditioned building stock. Re-tuning is a systematic process that improves operational efficiency and reduces energy consumption at no- or low-cost through the building automation system (BAS) by correcting operational problems that plague buildings. The study relied on successful demonstration of the re-tuning methodology at 4 pilot US Army installations that informed a holistic effort that included simulating 12 individual re-tuning energy efficiency measures (EEMs) and 6 packages of EEMs in 5 selected Army building prototype models that represent 311 million ft2 (28.9 million m2) of the Army’s conditioned floor space. Both the baseline buildings and the packages were customized to capture the expected outcomes of re-tuning a diverse set of buildings. The study highlighted the benefit of individual re-tuning EEMs and economics of implementing packages of EEMs in applicable Army buildings across 16 climates and 2 building vintages. The average whole-building energy savings ranged from 10.8% to 40.5% by building type, with the company operations facility (COF) building having the highest value proposition from re-tuning. In addition, the study reveals that all large office (LO) buildings in the Army are economical to re-tune. The total modeled cost savings potential for re-tuning the five building types across the US Army is $204/1,000 sf ($220/100 m2), or $64M annually. This cost savings represents 5.6% of all the Army’s energy expenditures.

Fernandez, Nicholas EP↗

Machine Learning for Adaptive Model Refinement to Bridge Scales

This whitepaper is responsive to focal area (2) Predictive modeling through the use of AI techniques and AI-derived model components: the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI driven model/component/parameterization selection). Here we describe scale-aware ML models for adaptive model refinement that allow us to bridge the spatial and/or temporal scales in simulation models and observation data for capturing and predicting extreme water cycles.

58 GEOSCIENCES↗

Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting

Advancing the capabilities of earthquake nowcasting, the real-time forecasting of seismic activities, remains crucial for reducing casualties. This multifaceted challenge has recently gained attention within the deep learning domain, facilitated by the availability of extensive earthquake datasets. Despite significant advancements, the existing literature on earthquake nowcasting lacks comprehensive evaluations of pre-trained foundation models and modern deep learning architectures; each focuses on a different aspect of data, such as spatial relationships, temporal patterns, and multi-scale dependencies. This paper addresses the mentioned gap by analyzing different architectures and introducing two innovative approaches called Multi Foundation Quake and GNNCoder. We formulate earthquake nowcasting as a time series forecasting problem for the next 14 days within 0.1-degree spatial bins in Southern California. Earthquake time series are generated using the logarithm energy released by quakes, spanning 1986 to 2024. Our comprehensive evaluations demonstrate that our introduced models outperform other custom architectures by effectively capturing temporal-spatial relationships inherent in seismic data. The performance of existing foundation models varies significantly based on the pre-training datasets, emphasizing the need for careful dataset selection. However, we introduce a novel method, Multi Foundation Quake, that achieves the best overall performance by combining a bespoke pattern with Foundation model results handled as auxiliary streams.

97 MATHEMATICS AND COMPUTING↗

Corrosion Prevention of Additively Manufactured Aluminum Packing Devices Developed for Process Intensification of CO 2 Capture by Aqueous Amines

Corrosion of additively manufactured (i.e., 3D printed) aluminum packing devices, developed to enhance heat and mass transfer in CO 2 absorption columns using amine-CO 2 scrubbing solutions, is investigated in this paper. The aluminum structures printed by selective laser melting with Al-10Si-0.3Mg feed powder are susceptible to corrosion in aqueous monoethanolamine, both fresh and used CO 2 -saturated solutions. The efficacy of corrosion-protective surface layers of aqueous polyether–ketone–ketone (PEKK) dip coating to provide amine corrosion resistance to the 3D printed aluminum structure is also evaluated. PEKK nanothick layers were coated on the corrugated surface of a 3D printed structure, identical to that of the intensified device, yielding 27 times higher corrosion resistance than the uncoated Al alloy surface. Finally, a systematic long-term electrochemical corrosion analysis revealed that a multilayer PEKK dip coating protocol enables protection of the 3D printed Al alloy surface in various CO 2 –monoethanolamine solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low Temperature CO2 Capture from an NGCC Flue Gas Using a Magnetically Stabilized, Inductively Heated Fluidized Bed Reactor

The lab sorbent testing finalized the sorbent composition and operating conditions for the integrated unit. The bench unit design included COMSOL simulation to finalize the coil design and select initial operating conditions of the power supply system. Fluidized bed testing with the induction heating verified that a heating efficiency of up to 90% can be achieved. The integrated bench unit operations provided valuable data confirming the feasibility of using induction heating for the desorption of CO2. Major challenge observed was the limited working capacity of the sorbent, requiring additional development in future projects. In addition, a large-scale reactor demonstration is required to mitigate the risk of uniform temperature distribution and heating efficiency over a large cross-sectional area when using induction heating.

Tong, Andrew↗

HopBox: An image analysis pipeline to characterize hop cone morphology

Abstract Hop cone morphology can influence picking and drying ability, and color can impact consumer preference and may be indicative of quality. However, these characteristics are not generally evaluated in hop breeding programs due to the tedious nature of trait quantification and the extensive variation among cones within a genotype. We developed the HopBox, which is a simply constructed light box with a camera mount, and a publicly available image processing pipeline that identifies hop cones within color‐corrected images, reads a QR code within the image, and outputs data on hop cone length, width, area, perimeter, openness, weight, color, and density. The trained model was applied to images of 500 cones each from 15 replicated advanced hop genotypes from the USDA‐ARS breeding program in Prosser, Washington. Analysis of variance revealed significant ( p < 0.001) differences between genotypes for all traits measured, enabling breeders to discriminate between genotypes for selection purposes. Broad sense heritability for all traits ranged from 0.23 to 0.59. A random sampling of hop cones from the complete dataset revealed that imaging only 5–10 cones adequately captured genotypic variation and provided acceptable rank correlations ( r s > 0.75); however, increasing the sample size to 30 provided optimal precision. Instructions for constructing a HopBox and the code for the analysis pipeline are publicly available online and have wide applicability for hop breeding and research.

Altendorf, Kayla R.↗

Review of the Effects of Polymer Binder Properties on Microstructure and Irreversible Volume Growth of Plastic Bonded Explosives Formulations

The rational design of effective polymeric binders for the formulation of plastic-bonded explosives (PBX) is challenging due to their inherent compositional complexity. The composites comprise irregularly shaped energetic material (EM) powders coated with low weight fractions of polymer via non-equilibrium processes such as slurry coating. Defects can deleteriously affect PBX stability and performance: nano- to micrometer-scale voids can act as loci for hot spots, lowering deflagration and detonation temperatures in unpredictable ways. Furthermore, some nominally desirable polymer properties are at odds with each other: e. g. good flow characteristics are desirable for coating and adhesion, but mechanical stiffness is needed to prevent deformation and cracking of PBX under mechanical stress. Good binder adhesion is critical, but the best means to predict and measure adhesion in PBX is not obvious. Experimental methods of determining binder adhesion on model surfaces may not capture polymer structural configurations relevant to deposition during coating. Molecular dynamics-based computational models have predicted key observables in PBX formulation, suggesting that they may be powerful tools for binder selection. In this review, primarily recent (~2006 and later) literature on polymeric binders for insensitive HE (IHE) is surveyed. We focus on how binder properties influence observable PBX properties as resistance to irreversible volume growth and void formation in PBX formulations mainly (but not exclusively) featuring 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) as the EM (e. g. PBX 9502, LX-17 and others). Conclusions from these studies yield useful guidelines for choosing HE binder candidates, as well as for the general design of highly-filled polymer composite materials. Finally, studies describing challenges in PBX formulation with the newer and more energetically dense high explosive, LLM-105, will be discussed.

adhesion↗

Kinetics of amorphous defect phases measured through ultrafast nanocalorimetry

Recognition of the role of extended defects on local phase transitions has led to the conceptualization of the defect phase, localized thermodynamically stable interfacial states that have since been applied in a myriad of material systems to realize significant enhancements in material properties. Here, we explore the kinetics of grain boundary confined amorphous defect phases, utilizing the high temperature and scanning rates afforded by ultrafast differential scanning calorimetry to apply targeted annealing/quenching treatments at high rates capable of capturing the kinetic behavior. Four Al-based nanocrystalline alloys, including two binary systems, Al–Ni and Al–Y, and two ternary systems, Al–Mg–Y and Al–Ni–Y, are selected to probe the materials design space (enthalpy of mixing, enthalpy of segregation, chemical complexity) for amorphous defect phase formation and stability, with correlative transmission electron microscopy applied to link phase evolution and grain stability to nanocalorimetry signatures. A series of targeted isothermal annealing heat treatments is utilized to construct a Time–Temperature-Transformation curve for the Al–Ni system, from which a critical cooling rate of 2400 °C/s was determined for the grain boundary confined disordered-to-ordered transition. Finally, a thermal profile consisting of 1000 repeated annealing sequences was created to quantify the recovery of the amorphous defect phase following sequential annealing treatments, with results indicating remarkable microstructural stability after annealing at temperatures above 90% of the melting temperature. This work contributes to a deeper understanding of grain boundary localized thermodynamics and kinetics, with potential implications for the design and optimization of advanced materials with enhanced stability and performance.

Amorphous defect phases↗

Incorporating Valve Switching Losses Into a Static Optimal Control Algorithm for the Hybrid Hydraulic-Electric Architecture (HHEA)

The Hybrid Hydraulic-Electric Architecture (HHEA) has, in recent years, been proposed as an energy efficient alternative to conventional load-sensing architectures in mobile machines such as excavators and wheel-loaders. HHEA leverages the advantages of hydraulic power and electric power to eliminate throttling valves while also improving the energy and control performance of the system. The architecture utilizes a set of common pressure rails to provide a majority of power and and a small electric motor driven pump to modulate this power to meet the exact demand. Previous work has developed a computationally efficient Lagrange Multiplier approach for determining the optimal pressure rail selections that minimizes the energy losses in the system. The static model used considers only the energy use for each pressure rail selection but not the losses associated with the valves during the transition. This paper presents an approach to include the switching losses in the model and in the optimization procedure. To capture the switching losses, switching events between different rails and at various input and output flow rates were simulated with consideration of valve spool dynamics. A parameterized model that summarizes the losses is then obtained, allowing switching losses to be added to the previous energy analysis. The performance of the switching loss model was compared with reference data obtained from a high-fidelity simulation model. To incorporate the switching losses into optimal control algorithm, an efficient dynamic programming approach that prevents frequent switching is adopted in place of the Lagrange multiplier approach. The overall effect of switching losses on the energy consumption and optimal control decisions is presented. In general, switching losses contribute to about 9–10% of input energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of an Amine Oxide Polyzwitterion Brush Martini Model with Polarizable Water and Ions

Abstract In order to accurately simulate the fouling process of proteins onto polyzwitterion brushes, models that accurately capture the hydration properties and chain conformations of such brushes must first be established. We developed a Martini coarse-grained (CG) model for amine oxide polyzwitterion (PNOMA) brushes, a promising class of antifouling materials, in polarizable water and ions by fitting to all-atom bond and angle distributions, monomer hydration free energy, monomer–monomer distance potential of mean force (PMF), and monomer–salt radial distribution functions (RDFs). Martini 2.2P was selected for compatibility with the established polarizable water and ion models. For comparison with PNOMA, we also constructed models for conventional sulfobetaine (PSBMA) and phosphorylcholine (PMPC) polyzwitterions and the polycation PMETAC using established nonbonded bead types from the literature and refitting bond and angle potentials. We simulated each polymer brush chemistry for varying grafting density and chain length, validating brush height scaling relations against experimental data. The CG models captured the relative hydration strengths among different polyzwitterion chemistries, and brush heights extrapolated to higher molecular weights are in agreement with experimental ellipsometry data. We find that chain swelling of the superhydrophilic PNOMA brushes lies between that of the traditional polyzwitterions PSBMA/PMPC and the polycation PMETAC. For PNOMA brushes in NaCl solution, simulated brush height decreases with salt concentration due to the selectively strong interactions between amine oxide and sodium ions.

Walker, Christopher C. [Oak Ridge National Laborat↗

Beta-Amino Carboxylate (BAC) non-aqueous physical solvents for enhanced CO2 separations in pre-combustion carbon capture, industrial CO 2 capture, and biogas upgrading processes

Novel beta-amino carboxylate (BAC) solvents have been synthesized and tested to efficiently capture carbon dioxide (CO 2 ) from process gas streams with CO 2 partial pressure intermediate between pre-combustion and post-combustion capture. The BAC solvents have molecular structures characterized by alkyl-substituted amides or esters containing a secondary amine functional group on the second carbon from the carbonyl carbon (referred to as the beta “β” carbon). The ester or amide functional group combined with optimal steric crowding around the amine nitrogen by proximate alkyl groups are tailored to modify the strength of CO 2 binding in the solvent. The solvents possess high CO 2 solubilities and high gas selectivity including good CO 2 /H 2 O selectivity and can be utilized for CO 2 absorption over a range of partial pressures. Due to low volatility, many of the solvents can be operated at or above ambient temperature which eliminates solvent chilling and allows regeneration using low grade waste heat. These novel solvents offer an opportunity for efficient carbon capture for a range of applications including biogas upgrading, hydrogen production, and pre-combustion carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗