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DOE OSTI2024

A synthetic co-culture for bioproduction of ammonia from methane and air

Abstract Fixed nitrogen fertilizers feed 50% of the global population, but most fixed nitrogen production occurs using energy-intensive Haber–Bosch-based chemistry combining nitrogen (N2) from air with gaseous hydrogen (H2) from methane (CH4) at high temperatures and pressures in large-scale facilities sensitive to supply chain disruptions. This work demonstrates the biological transformation of atmospheric N2 into ammonia (NH3) using CH4 as the sole carbon and energy source in a single vessel at ambient pressure and temperature, representing a biological “room-pressure and room-temperature” route to NH3 that could ultimately be developed to support compact, remote, NH3 production facilities amenable to distributed biomanufacturing. The synthetic microbial co-culture of engineered methanotroph Methylomicrobium buryatense (now Methylotuvimicrobium buryatense) and diazotroph Azotobacter vinelandii converted three CH4 molecules to l-lactate (C3H6O3) and powered gaseous N2 conversion to NH3. The design used division of labor and mutualistic metabolism strategies to address the oxygen sensitivity of nitrogenase and maximize CH4 oxidation efficiency. Media pH and salinity were central variables supporting co-cultivation. Carbon concentration heavily influenced NH3 production. Smaller-scale NH3 production near dispersed, abundant, and renewable CH4 sources could reduce disruption risks and capitalize on untapped energy resources. One-Sentence Summary Co-culture of engineered microorganisms Methylomicrobium buryatense and Azotobacter vinelandii facilitated the use of methane gas as a sole carbon feedstock to produce ammonia in an ambient temperature, atmospheric pressure, single-vessel system.

Biotechnology & Applied Microbiology↗

DOE OSTI2021

Evaluating the effects of structural disorder on the magnetic properties of Nd 2 Zr 2 O 7

Motivated by the variation in reported lattice parameters of floating-zone-grown Nd 2 Zr 2 O 7 crystals, we have performed a detailed study of the relationship between synthesis environment, structural disorder, and magnetic properties. Using a combination of polycrystalline standards, electron-probe microanalysis, and scattering techniques, we show that crystals grown under atmospheric conditions have a reduced lattice parameter relative to pristine polycrystalline powders due to occupation of the Nd site by excess Zr (i.e., negative stuffing). In contrast, crystals grown under high-pressure Ar are nearly stoichiometric with an average lattice parameter approaching the polycrystalline value. While minimal disorder of the oxygen sublattices is observed on the scale of the average structure, neutron pair-distribution function analysis indicates a highly local disorder of the oxygen coordination, which is only weakly dependent on growth environment. Most importantly, our magnetization, heat capacity, and single-crystal neutron scattering data show that the magnetic properties of crystals grown under high-pressure Ar match closely with those of stoichiometric powders. Neutron scattering measurements reveal that the signature of magnetic moment fragmentation—the coexistence of all-in-all-out (AIAO) magnetic Bragg peaks and diffuse pinch-point scattering due to spin-ice correlations–persists in these nearly stoichiometric crystals. However, in addition to an increased AIAO transition temperature, the diffuse signal is seemingly stabilized and remains nearly unchanged upon warming to 800 mK. This behavior indicates that both the AIAO magnetic order and spin-ice correlations are sensitive to deviations of the Nd stoichiometry.

36 MATERIALS SCIENCE↗

DOE OSTI2020

OPTIMAL CONTROL AND ENERGY-SAVING ANALYSIS OF COMMON PRESSURE RAIL ARCHITECTURES: HHEA & STEAM

In recent years several novel hydraulic architectures have been proposed with the intention of significantly increasing system efficiency. Two of these architectures, Steigerung der Energieeffizienz in der Arbeitshydraulik mobiler Arbeitsmaschinen (STEAM), and the Hybrid Hydraulic-Electric Architecture (HHEA), use a system of multiple common pressure rails (CPRs) to serve the multiple degrees-of-freedom of the machine. The key difference is that STEAM throttles hydraulic power from these rails while HHEA combines electric and hydraulic power to meet actuator demands. As a throttle-less architecture, HHEA is expected to save more energy than STEAM at the expense of added complexity. Therefore, it is useful to quantify this additional energy saving. Both systems have discrete operational choices corresponding to how the CPRs are utilized for each actuator. It is necessary to determine optimal operation for each of these architectures for analysis and fair comparison. Techniques for optimal operation of the HHEA have been developed previously from the Langrange multiplier method. Applying the same optimal control method to STEAM encountered some technical challenge leading to the optimal control algorithm not being able to satisfy certain constraints. The issue is analyzed and solved by adding noise to the optimization. Using this proposed algorithm, case studies are performed to compare the energy-saving potentials of STEAM and HHEA for two sizes of excavators and a wheel-loader performing representative duty cycles. The baseline is a standard load-sensing architecture. Results show that STEAM and HHEA can reduce energy consumption between 35-65% and 50-80% respectively

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Local structure analysis of low-temperature neutron pair distribution function coupled with molecular dynamics simulations of CH 4 and CO 2 hydrates from 2 to 210 K

CH 4 hydrates occur naturally and are an abundant potential fuel source with a corresponding risk of potent greenhouse gas release, due to their stability conditions at low temperature and high pressure. Byproduct CO 2 can be exchanged with CH 4 in these natural deposits and can potentially stabilize the hydrates at higher temperatures. CH 4 , CO 2 , and mixed CH 4 -CO 2 hydrates are studied with in situ neutron pair distribution function experiments from 2 to 210 K to investigate the impact of varying the CH 4 -CO 2 guest composition in the gas hydrate structure. These experiments combined with Reverse Monte Carlo analysis allow for the characterization of intermolecular CH 4 and CO 2 interactions with the water molecules which form the hydrate lattice and how they impact the local structure of the lattice itself. Results indicate that when CH 4 and CO 2 co-occupy the hydrate, the host is more strongly distorted than in the pure CH 4 and CO 2 hydrates, but this becomes less defined with increasing temperature. The presence of CO 2 in mixed hydrate increases the stability range and creates a barrier for CH 4 to completely leave the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗

DOE OSTI2020

Scalable Substitutional Re‐Doping and its Impact on the Optical and Electronic Properties of Tungsten Diselenide

Abstract Reliable, controlled doping of 2D transition metal dichalcogenides will enable the realization of next‐generation electronic, logic‐memory, and magnetic devices based on these materials. However, to date, accurate control over dopant concentration and scalability of the process remains a challenge. Here, a systematic study of scalable in situ doping of fully coalesced 2D WSe 2 films with Re atoms via metal–organic chemical vapor deposition is reported. Dopant concentrations are uniformly distributed over the substrate surface, with precisely controlled concentrations down to <0.001% Re achieved by tuning the precursor partial pressure. Moreover, the impact of doping on morphological, chemical, optical, and electronic properties of WSe 2 is elucidated with detailed experimental and theoretical examinations, confirming that the substitutional doping of Re at the W site leads to n‐type behavior of WSe 2 . Transport characteristics of fabricated back‐gated field‐effect‐transistors are directly correlated to the dopant concentration, with degrading device performances for doping concentrations exceeding 1% of Re. The study demonstrates a viable approach to introducing true dopant‐level impurities with high precision, which can be scaled up to batch production for applications beyond digital electronics.

Kozhakhmetov, Azimkhan↗

DOE OSTI2021

Structural Insights into the Mechanisms and Pharmacology of K 2P Potassium Channels

Leak currents, defined as voltage and time independent flows of ions across cell membranes, are central to cellular electrical excitability control. The K 2P (KCNK) potassium channel class comprises an ion channel family that produces potassium leak currents that oppose excitation and stabilize the resting membrane potential in cells in the brain, cardiovascular system, immune system, and sensory organs. Due to their widespread tissue distribution, K 2P s contribute to many physiological and pathophysiological processes including anesthesia, pain, arrythmias, ischemia, hypertension, migraine, intraocular pressure regulation, and lung injury responses. Structural studies of six homomeric K 2P s have established the basic architecture of this channel family, revealed key moving parts involved in K 2P function, uncovered the importance of asymmetric pinching and dilation motions in the K 2P selectivity filter (SF) C-type gate, and defined two K 2P structural classes based on the absence or presence of an intracellular gate. Further, a series of structures characterizing K 2P :modulator interactions have revealed a striking polysite pharmacology housed within a relatively modestly sized (~70 kDa) channel. Binding sites for small molecules or lipids that control channel function are found at every layer of the channel structure, starting from its extracellular side through the portion that interacts with the membrane bilayer inner leaflet. This framework provides the basis for understanding how gating cues sensed by different channel parts control function and how small molecules and lipids modulate K 2P activity. Such knowledge should catalyze development of new K 2P modulators to probe function and treat a wide range of disorders.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Design of a SiC-Si moving packed-bed particle-to-sCO 2 heat exchanger for high temperature concentrating solar power applications

Particle-based concentrating solar power systems integrated with sCO 2 power cycles offer high thermal efficiencies but require durable heat exchangers to transfer heat from high-temperature particles to the sCO 2 working fluid. Here, this study presents the design and optimization of a silicon carbide-silicon moving packed-bed heat exchanger for fabrication via binder jetting additive manufacturing. The heat exchanger was designed to withstand a 20 MPa sCO 2 pressure and operate at particle inlet temperatures up to 750 °C. The final design features 152 sCO 2 channels distributed across 19 plates, with elliptical corners and a minimum wall thickness of 3 mm. Flow restrictors at the sCO 2 channel inlets significantly improved flow uniformity, reducing thermal stresses and achieving a structural reliability of 99 % under representative operating conditions. The heat exchanger delivers a thermal duty of 9 kW and a volumetric power density of approximately 1 MW/m 3 in the channel region. Sensitivity studies confirmed the heat exchanger’s robustness under varying operating conditions, demonstrating its viability as a high-performance alternative to metallic heat exchangers for particle-based high-temperature concentrating solar power applications.

Barua, Bipul [Argonne National Laboratory (ANL), A↗

DOE OSTI2024

Voltage waveform tailoring for high aspect ratio plasma etching of SiO 2 using Ar/CF 4 /O 2 mixtures: Consequences of low fundamental frequency biases

The use of non-sinusoidal waveforms in low pressure capacitively coupled plasmas intended for microelectronics fabrication has the goal of customizing ion and electron energy and angular distributions to the wafer. One such non-sinusoidal waveform uses the sum of consecutive harmonics of a fundamental sinusoidal frequency, f 0 , having a variable phase offset between the fundamental and even harmonics. In this paper, we discuss results from a computational investigation of the relation between ion energy and DC self-bias when varying the fundamental frequency f 0 for capacitively coupled plasmas sustained in Ar/CF 4 /O 2 and how those trends translate to a high aspect ratio etching of trenches in SiO 2 . The fundamental frequency, f 0 , was varied from 1 to 10 MHz and the relative phase from 0° to 180°. Two distinct regimes were identified. Average ion energy onto the wafer is strongly correlated with the DC self-bias at high f 0 , with there being a maximum at φ = 0° and minimum at φ = 180°. In the low frequency regime, this correlation is weak. Average ion energy onto the wafer is instead dominated by dynamic transients in the applied voltage waveforms, with a maximum at φ = 180° and minimum at φ = 0°. The trends in ion energy translate to etch properties. In both, the high and low frequency regimes, higher ion energies translate to higher etch rates and generally preferable final features, though behaving differently with phase angle.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Nanodiamonds with SiV colour centres for quantum technologies

Properties of silicon-vacancy (SiV) colour centres in ultra-nanosize diamonds are studied. Nanodiamonds are obtained at a high temperature and pressure, which induced transformations in mixtures of organic and hetero-organic compounds without metal-catalysts. The size distribution of grown nanodiamonds is determined by the methods of transmission electron microscopy and atomic-force microscopy, as well as by using the model of phonon spatial localisation. In addition, Raman spectra of various nanodiamonds and luminescence properties of SiV-centres are investigated. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications

Abstract An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.

Donlan, Connor F. (ORCID:0000000223317882)↗

DOE OSTI2026

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗

DOE OSTI2021

Screening of Lost Circulation Materials for Geothermal Applications: Experimental Study at High Temperature

Abstract This study presents a laboratory experimental research to determine the characteristics of lost circulation materials (LCMs) capable of addressing thermal degradation, providing bridging and sealing in geothermal conditions. Eleven different materials were tested: Walnut Fine, Walnut Medium, Sawdust, Altavert, Graphite Blend, Bentonite Chips, Micronized Cellulose (MICRO-C), Magma Fiber Fine, diatomaceous earth/amorphous silica powder (DEASP), Cotton Seed Hulls, and a Calcium Carbonate Blend. The filtration and sealing pressure of the LCMs were measured with HPHT equipment up to 149 °C (300 °F). Besides, the particle size distribution (PSD) of fine granular materials was measured. The results show that the performance of some LCM materials commonly used in geothermal operations is affected by high temperature. Characteristics such as shape and size made some materials more prone to thermal degradation. Also, it was found that the PSD of LCMs is a key factor in the effectiveness of bridging and sealing fractures. The results suggest that granular materials with a wide particle size distribution PSD are suitable for geothermal applications.

Energy & Fuels↗

DOE OSTI2021

ADVANCED THERMAL-HYDRAULIC MODEL OF HEAT RECOVERY STEAM GENERATORS

Steam-side oxidation at elevated temperatures in heat recovery steam generators (HRSGs) can lead to overheating of local tubes, potential oxide scale exfoliation, and damage to critical equipment. Predicting the oxide growth distribution requires detailed knowledge of the distribution of tube metal temperatures. To address these challenges, a computational fluid dynamics (CFD) model of a high-pressure superheater (HPSH) was developed within the Siemens’ STAR-CCM+ CFD commercial software. The HPSH section of the steam generator was selected for modeling because of its high oxidation rates.The model development included several steps. In the first step, an oxidation model based on a parabolic oxidation relationship was implemented. The oxidation growth predicted by the model was then verified for a full-load boiler operation case. In the second step, a three-dimensional CFD model was developed to account for the thermal and flow physics involved in HRSGs. The CFD model was then verified and validated on a simplified geometry that contained six row-tubes which mimicked the tube arrangements of an HPSH section. Numerical results compared well with published experimental results. In the third step, the oxidation model was coupled to the HRSG’s CFD model, and a comparison study was performed for two cases: (a) regular finless tubes and (b) finned tubes. Preliminary results showed that the oxide thickness predicted by the case with tube fins was higher compared to that of the finless tube case, thus demonstrating the need to model the effects of the tube fins on oxide thickness.

Panicker, Nithin↗

DOE OSTI2022

Tundra SGS – Critical Importance of Site-Specific Injectivity Testing for Carbon Dioxide Injection Well Simulation Calibration

Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Brine injectivity tests were conducted on both the Broom Creek (BC) and Deadwood (DW) storage formations in one of the cored stratigraphic test wells prior to finalized simulations. The injectivity tests entailed injection of brine into the formations, followed by shutting in the wells. The shut-in duration represents the fall-off period which was used to carry out pressure transient analyses of the tests. The analysis of injectivity tests indicated that core-indicated and modeled permeability distributions should be conservatively multiplied by 2.5× and 5× in the BC and DW geologic models, respectively, prior to numerical simulations of CO 2 injection using Computer Modelling Group’s (CMG’s) GEM equation-of-state reservoir simulator. The scaler permeability multipliers allowed the fluid flow simulations to fully represent well test-measured injection well rates in the respective formations.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Single-Particle Studies Reveal a Nanoscale Mechanism for Elastic, Bright, and Repeatable ZnS:Mn Mechanoluminescence in a Low-Pressure Regime

Mechanoluminescent materials, which emit light in response to elastic deformation, are demanded for use as in situ stress sensors. ZnS doped with Mn is known to exhibit one of the lowest reported thresholds for appearance of mechanoluminescence, with repeatable light emission under contact pressure <10 MPa. Here, the physical basis for such behavior remains as yet unclear. Here, reliable microscopic detection of mechanoluminescence of single ZnS:Mn microparticles, in combination with nanoscale structural characterization, provides evidence that the mechanoluminescent properties of these particles result from interplay between a non-centrosymmetric crystal lattice and its defects, viz., dislocations and stacking faults. Statistical analysis of the distributions of mechanoluminescence energy release trajectories reveals two distinct mechanisms of excitation: one attributable to a piezo-phototronic effect and the other due to dislocation motion. At pressures below 8.1 MPa, both mechanisms contribute to mechanoluminescent output, with a dominant contribution from the piezo-phototronic mechanism. In contrast, above 8.1 MPa, dislocation motion is the primary excitation source. For the piezo-phototronic mechanism, we propose a specific model that accounts for elastic ZnS:Mn mechanoluminescence under very low pressure. The charged interfaces in stacking faults lead to the presence of filled traps, which otherwise would be empty in the absence of the built-in electric field. Upon application of external stress, local enhancement of the piezoelectric field at the stacking faults’ interfaces facilitates release of the trapped carriers and subsequent luminescence. This field enhancement explains how <10 MPa pressure produces thousands of photons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Large-Eddy Simulation of Flow Over Boeing Gaussian Bump Using Multiagent Reinforcement Learning Wall Model: Preprint

We develop a wall model for large-eddy simulation (LES) that takes into account various pressure-gradient effects using multi-agent reinforcement learning. The model is trained using low-Reynolds-number flow over periodic hills with agents distributed on the wall at various computational grid points. It utilizes a wall eddy-viscosity formulation as the boundary condition to apply the modeled wall shear stress. Each agent receives states based on local instantaneous flow quantities at an off-wall location, computes a reward based on the estimated wall-shear stress, and provides an action to update the wall eddy viscosity at each time step. The trained wall model is validated in wall-modeled LES of flow over periodic hills at higher Reynolds numbers, and the results show the effectiveness of the model on flow with pressure gradients. The analysis of the trained model indicates that the model is capable of distinguishing between the various pressure gradient regimes present in the flow. To further assess the robustness of the developed wall model, simulations of flow over the Boeing Gaussian bump are conducted at a Reynolds number of 2 x 10^6, based on the free-stream velocity and the bump width. The results of mean skin friction and pressure on the bump surface, as well as the velocity statistics of the flow field, are compared to those obtained from equilibrium wall model (EQWM) simulations and published experimental data sets. The developed wall model is found to successfully capture the acceleration and deceleration of the turbulent boundary layer on the bump surface, providing better predictions of skin friction near the bump peak and exhibiting comparable performance to the EQWM with respect to the wall pressure and velocity field. We also conclude that the subgrid-scale model is crucial to the accurate prediction of the flow field, in particular the prediction of separation.

boundary layer↗

DOE OSTI2021

A Parameterization of Turbulent Dissipation and Pressure Damping Time Scales in Stably Stratified Inversions, and its Effects on Low Clouds in Global Simulations

Abstract It is difficult for coarse‐resolution global models of the atmosphere to accurately simulate the observed distribution of low clouds. In particular, it is difficult for moist turbulence closure models to simulate sufficiently bright near‐coastal stratocumulus (Sc) without simulating overly bright marine shallow cumuli (Cu). To parameterize bright Sc, a turbulence parameterization must damp the turbulent fluxes of heat and moisture above cloud top in order to prevent excessive entrainment of dry air into cloud top. To parameterize dim shallow Cu, the subgrid variances of temperature and moisture must remain large, in order to permit partial cloudiness. However, damping the fluxes but not the variances just above cloud top is difficult if a parameterization uses a single “master” time scale to damp both. In nature, the above‐cloud fluxes are damped by pressure fluctuations, whereas scalar variances are damped by a different process, namely, turbulent dissipation. In a stably stratified inversion above cloud, pressure damping is large but turbulent dissipation is small. To avoid this problem, a multitime scale parameterization for damping has been developed. The damping parameterization has been implemented in a global model and evaluated. The parameterization is capable of dimming shallow Cu while producing adequately bright Sc.

54 ENVIRONMENTAL SCIENCES↗