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At least 1,279 records · Page 71

Two-Photon Fluorescence Microscope for Microgravity Research

A two-photon fluorescence microscope has been developed for the study of biophysical phenomena. Two-photon microscopy is a novel form of laser-based scanning microscopy that enables three-dimensional imaging without many of the problems inherent in confocal microscopy. Unlike one-photon optical microscopy, two-photon microscopy utilizes the simultaneous nonlinear absorption of two near-infrared photons. However, the efficiency of two-photon absorption is much lower than that of one-photon absorption, so an ultra-fast pulsed laser source is typically employed. On the other hand, the critical energy threshold for two-photon absorption leads to fluorophore excitation that is intrinsically localized to the focal volume. Consequently, two-photon microscopy enables optical sectioning and confocal performance without the need for a signal-limiting pinhole. In addition, there is a reduction (relative to one-photon optical microscopy) in photon-induced damage because of the longer excitation wavelength. This reduction is especially advantageous for in vivo studies. Relative to confocal microscopy, there is also a reduction in background fluorescence, and, because of a reduction in Rayleigh scattering, there is a 4 increase of penetration depth. The prohibitive cost of a commercial two-photon fluorescence-microscope system, as well as a need for modularity, has led to the construction of a custom-built system (see Figure 1). This system includes a coherent mode-locked titanium: sapphire laser emitting 120-fs-duration pulses at a repetition rate of 80 MHz. The pulsed laser has an average output power of 800 mW and a wavelength tuning range of 700 to 980 nm, enabling the excitation of a variety of targeted fluorophores. The output from the laser is attenuated, spatially filtered, and then directed into a confocal scanning head that has been modified to provide for side entry of the laser beam. The laser output coupler has been replaced with a dichroic filter that reflects the longer-wavelength excitation light and passes the shorter-wavelength fluorescence light. Also, the confocal pinhole has been removed to increase the signal strength. The laser beam is scanned by a twoperpendicular- axis pair of galvanometer mirrors through a pupil transfer lens into the side port of an inverted microscope. Finally, the beam is focused by a 63-magnification, 1.3-numerical- aperture oil-immersion objective lens onto a specimen. The pupil transfer lens serves to match the intermediate image planes of the scanning head and the microscope, and its location is critical. In order to maximize the quality of the image, (that is, the point spread function of the objective lens for all scan positions), the entire system was modeled in optical-design software, and the various free design parameters (the parameters of the spatial-filter components as well as the separations of all of the system components) were determined through an iterative optimization process. A modular design was chosen to facilitate access to the optical train for future fluorescence correlation spectroscopy and fluorescence-lifetime experiments.

Fischer, David G.↗

3D-Sonification for Obstacle Avoidance in Brownout Conditions

Helicopter brownout is a phenomenon that occurs when making landing approaches in dusty environments, whereby sand or dust particles become swept up in the rotor outwash. Brownout is characterized by partial or total obscuration of the terrain, which degrades visual cues necessary for hovering and safe landing. Furthermore, the motion of the dust cloud produced during brownout can lead to the pilot experiencing motion cue anomalies such as vection illusions. In this context, the stability and guidance control functions can be intermittently or continuously degraded, potentially leading to undetected surface hazards and obstacles as well as unnoticed drift. Safe and controlled landing in brownout can be achieved using an integrated presentation of LADAR and RADAR imagery and aircraft state symbology. However, though detected by the LADAR and displayed on the sensor image, small obstacles can be difficult to discern from the background so that changes in obstacle elevation may go unnoticed. Moreover, pilot workload associated with tracking the displayed symbology is often so high that the pilot cannot give sufficient attention to the LADAR/RADAR image. This paper documents a simulation evaluating the use of 3D auditory cueing for obstacle avoidance in brownout as a replacement for or compliment to LADAR/RADAR imagery.

3D audio↗

Evapotranspiration-Based Irrigation Scheduling in Cool-Season Vegetables

Crop evapotranspiration (ETc) is strongly linked with photosynthetically active vegetation fraction (Fc). Estimation of ETc may support efficiency gains in irrigation water management, which in turn can mitigate nitrate leaching, promote water supply sustainability, and reduce energy costs associated with water pumping or transport. The University of California Cooperative Extension operates the CropManage (CM) model as a freely-available web-application for growers and consultants to support irrigation and nitrogen scheduling decisions. CM accounts for the rapid growth and typically brief cycle of cool-season vegetables, where Fc and crop coefficient (fraction of reference ET) can change daily during canopy development. Daily weather conditions are inherently accounted for by use of grass reference ETo data imported from the California Dept. Water Resources. Crop water requirement calculations are output in terms of irrigation system runtime. Empirical equations are used to estimate daily Fc time-series for a given crop type, primarily as a function of planting date and expected harvest. An applications programming interface (API) enables CM to import satellite-based Fc observations from NASA's Satellite Irrigation Management Support, which uses Landsat imagery to monitor about eight million irrigation acres statewide. The API is intended to provide a check on internal CM predictions of Fc and to facilitate expansion of the web-app to new crops and regions. A replicated irrigation trial was performed on cauliflower during spring/summer 2018 at the USDA Agricultural Research Station in Salinas, CA. The crop was established by sprinkler irrigation, and CropManage was then used to guide a series of drip irrigation treatments at 50%, 75%, 100%, and 150% of ETc replacement levels. Results will be presented with respect to water use efficiency, nitrogen use efficiency, biomass yield, and marketable yield. Additional findings will be presented for a celery trial harvested during autumn 2018.

Johnson, Lee↗

Mechanistic origins of excitonic properties in 2D perovskites: Implications for exciton engineering

As the field of 2D halide perovskites (HPs) matures, state-of-the-art techniques to measure important properties, such as the band gap (E g ) and exciton binding energy (E b ), continue to produce inconsistent values. Here, we tackle this long-standing problem by obtaining direct measurements of E g and E b for 31 unique HP structures. The E b values are lower than in previous literature reports and lower than expected from standard theory that assumes excitons are screened by optical-frequency dielectric constants. These low E b values are shown to be a consequence of unique screening effects, such as superlattice screening and phonon screening. Here, we find a strikingly strong correlation between E b and E g and provide design principles to a priori tune E g and E b to their optimal values. As such, this work offers a blueprint for E g -E b engineering of low-dimensional semiconductors as an even more useful replacement for simply band-gap engineering.

14 SOLAR ENERGY↗

Experimental and Computational Evaluation of Nicotinamide Cofactor Biomimetics

Oxidoreductase enzymes are widely used biocatalysts due to their high enantioselectivity and broad substrate compatibility in useful transformations. Many oxidoreductases require nicotinamide cofactors (i.e., NAD(P)H). To replace this costly natural cofactor, synthetic nicotinamide cofactor biomimetics (NCBs) offer different shapes, binding affinities, and reducing potentials that exceed the capabilities of wild-type NAD(P)H. However, the ill-defined structure–activity relationships (SARs) of various NCBs slow rationally guided innovation, such as customized reducing potentials. Here, we dissect two essential elements of NCB design, holding the nicotinamide invariant. First, the linker length between the nicotinamide and an unconjugated aromatic ring uncovered unexpected benefits to redox activity for two or three carbon linkers. Second, substitution on this unconjugated aryl group (Ring 2) might not be expected to affect activity. However, SAR trends demonstrate substantial benefits to reductive potential conferred by electron-donating functionalities on Ring 2. Furthermore, catalysis by two enzymes demonstrates enzyme-dependent tolerance or sensitivity to the NCB structures. Density functional theory (DFT) and computational modeling provide a theoretical framework to understand and build upon these observations. Ring 2 reaches up to the nicotinamide to stabilize its positive charge after oxidation through π–π stacking and charge transfer. Thus, the systematic examination of NCB’s stability, electrochemical redox potentials, and kinetics uncovers trends for the improved design of NCBs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trap passivation of 4H-SiC/SiO 2 interfaces by nitrogen annealing

We report an N 2 based annealing treatment to passivate interface traps (D it ) in n- and p-type 4H-SiC. The process has the potential to replace the commonly used hazardous and expensive gas nitric oxide (NO). N 2 postoxidation annealing reduces D it in both the upper and lower halves of the 4H-SiC bandgap, with a greater impact at the valence band edge. N 2 annealing at 1500 °C is observed to be more effective in passivating traps and positive fixed charges than NO annealing for p-type devices, whereas for n-type devices, the opposite is true. The breakdown voltages for these devices are found to be lower than that of NO annealed devices. X-ray photoelectron spectroscopy has been performed to estimate the nitrogen areal density at the interface. D it is measured as a function of nitrogen areal densities in the near interfacial regions for the different processes. Additionally, theoretical analysis through density functional theory is consistent with the measured D it profiles by showing the generation of additional states near the valence band edge due to increased nitrogen concentration. In addition to reporting the effect of N 2 annealing on both n- and p-type 4H-SiC, this work correlates the nitrogen areal densities at the interface to the D it and explains the difference in D it characteristics with nitrogen areal density between n- and p-type interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)

This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mathematical Morphological Filtering with a Self-Adaptive Reconstruction Technique and Application to Local Seismic Data

Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.

58 GEOSCIENCES↗

Biocatalytic Membranes for Carbon Capture and Utilization

Innovative carbon capture technologies that capture CO 2 from large point sources and directly from air are urgently needed to combat the climate crisis. Likewise, corresponding technologies are needed to convert this captured CO 2 into valuable chemical feedstocks and products that replace current fossil-based materials to close the loop in creating viable pathways for a renewable economy. Biocatalytic membranes that combine high reaction rates and enzyme selectivity with modularity, scalability, and membrane compactness show promise for both CO 2 capture and utilization. This review presents a systematic examination of technologies under development for CO 2 capture and utilization that employ both enzymes and membranes. CO 2 capture membranes are categorized by their mode of action as CO 2 separation membranes, including mixed matrix membranes (MMM) and liquid membranes (LM), or as CO 2 gas–liquid membrane contactors (GLMC). Because they selectively catalyze molecular reactions involving CO 2 , the two main classes of enzymes used for enhancing membrane function are carbonic anhydrase (CA) and formate dehydrogenase (FDH). Small organic molecules designed to mimic CA enzyme active sites are also being developed. CO 2 conversion membranes are described according to membrane functionality, the location of enzymes relative to the membrane, which includes different immobilization strategies, and regeneration methods for cofactors. Parameters crucial for the performance of these hybrid systems are discussed with tabulated examples. Progress and challenges are discussed, and perspectives on future research directions are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability study of aqueous foams under high-temperature and high-pressure conditions relevant to Enhanced Geothermal Systems (EGS)

In Enhanced Geothermal System (EGS) hydraulic fracturing is carried out by injecting cold water into deep Hot Dry Rocks (HDR) under carefully controlled conditions to create new or reopen existing fractures. Water-based fracturing fluids demonstrate some challenges including immense quantity of water usage, water sensitivity of the formations, water blocking, and lack of proppant carrying capacity and transportation. Thus, an alternative is to use foam-based fracturing fluid which offers potential advantage over conventional water-based fracturing fluid such as minimum water usage, reduced wellbore damage, high proppant carrying capacity, and less environmental damage. However, foams are complex mixture of gaseous phase and liquid phase which are thermodynamically unstable at downhole conditions, and their stability can decrease over time due to liquid drainage, bubble coarsening, and coalescence. This paper shows laboratory experiments executed to study foam stability at high temperature (200°C) and high pressure (6.9MPa) conditions which simulates the geothermal environment. Foam stability was characterized by half-life of foam, which is defined as the time taken by the foam to decreases by 50% of its original height due to drainage. In this paper, two types of gaseous phases, nitrogen (N 2 ) and carbon dioxide (CO 2 ) were investigated. Also, based on successful practice of foam-based fracturing fluid in oil and gas industries, four surfactants, including Alpha olefin sulfonate (AOS), Sodium dodecyl sulfonate (SDS), Tergitol™ (NP – 40), and Cetyltrimethylammonium chloride (CTAC) at optimum concentration of 1wt.% were tested for best stability performance. In addition, different stabilizing agents including guar gum, bentonite clay, crosslinker, silicon dioxide nanoparticles (SiO 2 ), graphene oxide (GO) were also studied. Experimental results showed that N 2 foams were more stable than CO 2 foams. It was observed that foam half-life decreased with the increase in temperature. Among all the surfactants, AOS foams showed the most promising thermal stability at high temperatures. Moreover, with the addition of stabilizing agents, foam's half-life was enhanced. Stabilizing agents such as crosslinker and GO dispersion showed the most stable foams with half-life recorded at 20min and 17min, respectively, at 200°C and 6.9MPa. Finally, pressure also showed a positive effect on foam stability; with increased pressure, foam half-life was increased. Based on the experimental data, analytical models for the effect of temperature and pressure were developed, considering foam degradation is a first-order kinetic reaction that linearly depends on the foam drainage mechanism. The effect of temperature on foam half-life was studied as an exponential decay model. In this model, foam half-life is a function of drainage rate constant (D A ) and activation energy (E a ) of the foam system. The effect of pressure on foam half-life was found to obey a power-law model where an increase in pressure showed an increase in foam half-life. Furthermore, a linear relation was studied for the effect of pressure on foam activation energy and drainage rate. Then the combined effects of temperature and pressure were studied, which yielded an analytical model to predict the foam stabilities in terms of half-life for different foam compositions. In conclusion, this research indicates that with an appropriate selection of surfactants and stabilizing agents, it is possible to obtain stable foams, which could replace conventional water fracturing fluid under EGS conditions.

15 GEOTHERMAL ENERGY↗

Ce stabilized Ni–SrO as a catalytic phase transition sorbent for integrated CO 2 capture and CH 4 reforming

Integration of carbon dioxide capture from flue gas with dry reforming of CH 4 represents an attractive approach for CO 2 utilization. The selection of a suitable bifunctional material serving as a catalyst/sorbent is the key. This paper reports Ni decorated and CeO x -stabilized SrO (SrCe 0.5 Ni 0.5 ) as a multi-functional, phase transition catalytic sorbent material. The effect of CeO x on the morphology, structure, decarbonation reactivity, and cycling stability of the catalytic sorbent was determined with TEM-EDX, XRD, in situ XRD, CH 4 -TPR and TGA. Here, cyclic process tests were conducted in a packed bed reactor. The results indicate that large Ni clusters were present on the surface of the SrNi sorbent, and the addition of CeO 2 promoted even distribution of Ni on the surface. Moreover, the Ce–Sr interaction promoted a complex carbonation/decarbonation phase-transition, i.e. SrCO 3 + CeO 2 ↔ Sr 2 CeO 4 + CO 2 as opposed to the conventional, simple carbonation/decarbonation cycles (e.g. SrCO 3 ↔ SrO + CO 2 ). This double replacement crystalline phase transition mechanism not only adjusts the carbonation/calcination thermodynamics to facilitate SrCO 3 decomposition at relatively low temperatures but also inhibits sorbent sintering. As a result, excellent activity and stability were observed with up to 91% CH 4 conversion, >72% CO 2 capture efficiency and ~100% residual O 2 capture efficiency from flue gas by utilizing the CeO 2 ↔ Ce 2 O 3 redox transition. This renders an intensified process with zero coke deposition. Moreover, the SLDRM with SrCe 0.5 Ni 0.5 has the flexibility to produce concentrated CO via CO 2 -splitting while co-producing a syngas with tunable H 2 /CO ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultra-Light Hybrid Composite Door Design, Manufacturing and Demonstration

New Corporate Average Fuel Economy regulations require improved fuel efficiency of the future vehicle fleet. Weight reduction is key to achieving these targets. Replacing metallic body and chassis components with carbon fiber-reinforced composites offers the most weight reduction potential at up to 70%. Introduction of the BMW i3 and i8 in 2014 required mass production processes to meet 20,000+ units per year. Preforming with High Pressure Resin Transfer Molding has been implemented and meets rate, cost, and performance requirements. We will advance these technologies to develop an ultra-light driver’s side door for the vehicle with production rates of 40,000 units annually per plant in Detroit, Michigan. This project sought to employ a comprehensive systems approach for designing, manufacturing, and demonstrating an ultra-light hybrid composite automotive door. Composite structural components are integrated with other functional systems to reduce part count and full-system weight by a minimum of 42.5%. The approach will be demonstrated on a driver’s- side front door and will consider all fit, functional, safety, and cost requirements. These concepts will be evaluated using structural and crash simulations and linked to a manufacturing feasibility study, resulting in producible designs of an integrated door system. A cost model will evaluate part of the cost for the various designs and will ensure the cost target of less than $5 per pound of weight saved is met. Hybrid composites consisting of carbon, glass, and metal components will be included in our trade-off studies to satisfy these cost and performance goals.

02 PETROLEUM↗

End-to-End Differentiable Modeling and Management of the Environment

Focal Area: (2) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization. We emphasize the importance of leveraging optimization techniques from AI/machine learning (ML) to solve challenging problems in Earth system modeling. Science Challenge: Automatic differentiation has had a transformative effect on ML by allowing the calculation of gradients of arbitrary functions in an incredibly large class of models. We can potentially realize similar improvements in parameter estimation and control for Earth system models (ESMs) by reimplementing them in computational frameworks from ML. Practitioners working with large (>10 7 parameters) models in ML and AI can obtain good predictive performance in a range of spatiotemporal tasks by making use of optimization via stochastic gradient descent and incorporating prior knowledge at multiple levels. We propose writing ESMs in open-source computational frameworks such as Torch, Tensorflow, and JAX to greatly expand the scope of environmental forecasting and management challenges, which can be addressed by leveraging automatic differentiation and gradient descent-like algorithms. We do not call for a wholesale replacement of physical models with data-driven surrogates, but rather advocate for interleaving physical and empirical equations in a manner that is most faithful to the extent of our scientific knowledge and observational data. Central to this topic is the merging of differentiable physical simulations with differentiable optimization layers, which are now both beginning to come to the forefront.

54 ENVIRONMENTAL SCIENCES↗

Computer program for solving laminar, transitional, or turbulent compressible boundary-layer equations for two-dimensional and axisymmetric flow

A numerical algorithm and computer program are presented for solving the laminar, transitional, or turbulent two dimensional or axisymmetric compressible boundary-layer equations for perfect-gas flows. The governing equations are solved by an iterative three-point implicit finite-difference procedure. The software, program VGBLP, is a modification of the approach presented in NASA TR R-368 and NASA TM X-2458, respectively. The major modifications are: (1) replacement of the fourth-order Runge-Kutta integration technique with a finite-difference procedure for numerically solving the equations required to initiate the parabolic marching procedure; (2) introduction of the Blottner variable-grid scheme; (3) implementation of an iteration scheme allowing the coupled system of equations to be converged to a specified accuracy level; and (4) inclusion of an iteration scheme for variable-entropy calculations. These modifications to the approach presented in NASA TR R-368 and NASA TM X-2458 yield a software package with high computational efficiency and flexibility. Turbulence-closure options include either two-layer eddy-viscosity or mixing-length models. Eddy conductivity is modeled as a function of eddy viscosity through a static turbulent Prandtl number formulation. Several options are provided for specifying the static turbulent Prandtl number. The transitional boundary layer is treated through a streamwise intermittency function which modifies the turbulence-closure model. This model is based on the probability distribution of turbulent spots and ranges from zero to unity for laminar and turbulent flow, respectively. Several test cases are presented as guides for potential users of the software.

Harris, J. E.↗

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗

Regioisomer-Specific Crystallization of Diglycidyl Ether of Bisphenol F Epoxy Resin

Diglycidyl ether of bisphenol F (DGEBF) is a common industrial epoxy resin, desired for its possible replacement of the bisphenol A (BPA) analogue DGEBA due to potential health hazards of BPA. During curing, crystallization of the DGEBF resin can cause inaccurate resin-to-hardener ratios, resulting in incomplete crosslinking; therefore, understanding the crystallization of DGEBF is important for proper industrial control of the material. Here, in this work, we utilized a combination of single-crystal x-ray diffraction, Raman spectroscopy, and 1 H-NMR to investigate the crystallization of DGEBF. We observed crystallization of two DGEBF regioisomers: ortho-ortho’-DGEBF and ortho-para’-DGEBF, and report their crystal structures. Notably, para-para’-DGEBF crystallization is not observed, indicating crystallization of this regioisomer does not occur under ambient conditions. Density functional theory calculations were performed to describe the phonon modes of the ortho-ortho’- and ortho-para’-DGEBF structures, corroborating Raman signatures for the respective isomers. Using a phonon mode analysis, we identify the presence of three specific optical vibrational modes at 631.3, 344.1, and 345.6 cm -1 that are unique to the para monomer. This work offers insights into the crystallization behavior of DGEBF resins under ambient conditions and may inform potential industrial application of this material.

Neu, Jennifer [Oak Ridge National Laboratory (ORNL↗

Reaction mechanism and kinetics for N 2 reduction to ammonia on the Fe–Ru based dual-atom catalyst

Environmental and energy considerations demand that the Haber-Bosch process for reducing N 2 to NH 3 be replaced with electrochemical ammonia synthesis where the H atoms come from water instead of from H 2 . But a practical realization of electrochemical N 2 reduction reaction (NRR) requires the development of new generation electrocatalysts with low overpotential and high Faraday efficiency (FE). A major problem here is that the hydrogen evolution reaction (HER) competes with NRR. Herein, we consider new generation dual-site catalysts involving two different metals incorporated into a novel two-dimensional C 3 N–C 2 N heterostructure that provides a high concentration of well-defined but isolated active sites that bind two distinct metal atoms in a framework that facilitates electron transfer. We report here the mechanism and predicted kinetics as a function of applied potential for both NRR and HER for the (Fe–Ru)/C 3 N–C 2 N dual atom catalyst. These calculations employ the grand canonical potential kinetics (GCP-K) methodology to predict reaction free energies and reaction barriers as a function of applied potential. The rates are then used in a microkinetic model to predict the turn-over-frequencies (TOF) as a function of applied potential. At U = 0 V, the FE for NRR is 93%, but the current is only 2.0 mA cm –2 . The onset potential (at 10 mA cm –2 ) for ammonia on Fe–Ru/C 3 N–C 2 N is –0.22 V RHE . This leads to a calculated TOF of 434 h –1 per Fe–Ru site. In conclusion, we expect that the mechanisms for NRR and HER developed here will help lead to new generations of NRR with high TOF and FE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗