Formation of secondary mineral coatings and the persistence of reduced metal-bearing phases in soils developing on historic coal mine spoil
Abstract not provided
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “accomplishments”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Piston geometry and stroke optimization for high efficiency propane spark ignition engines
Propane has unique properties and offers interesting characteristics for high-efficiency spark ignition engines. Its high volatility reduces or completely eliminates fuel-wall wetting and facilitates fuel air mixing. Furthermore, propane has a research octane number of 112 and a high octane sensitivity of 15. Finally, its laminar flame speed is on the same order as that of conventional gasoline, and it exhibits high dilution tolerance. Modern spark ignition internal combustion engines rely on fast combustion rates and high dilution to achieve high brake thermal efficiencies. To accomplish this, high stroke-to-bore ratios and high geometric compression ratios have been used in new engine designs. Therefore, propane’s relatively high laminar flame speeds, high knock resistance, and dilution tolerance make it an excellent candidate fuel for modern spark ignition engines. The objective of this work is to co-optimize the piston geometry and the engine stroke to maximize the efficiency of a spark-ignition engine fueled with propane. 3D computational fluid dynamics (CFD) simulations employing the extended coherent flamelet model were used to study the parametric effects of piston shape and stroke length. A piston geometry based on high performing pistons was parameterized using four controlling parameters. The piston geometry and engine stroke design space was explored using deterministic and quasi-random sampling techniques. In conclusion, a Gaussian process regression model was built using the simulation data to explain the results observed.
33 ADVANCED PROPULSION SYSTEMS↗
Unveiling the mechanism of surface corrugation formation on a quasi free-standing bi-layer graphene via experimental and modeling investigations
Extensive studies have been conducted to accomplish the controls over the formation of surface corrugations on chemical vapor deposited (CVD) graphene. However, the underlying mechanism of the surface corrugation formation on graphene remains elusive, due to the difficulty delineating the growth-induced surface corrugations from wrinkles formed during graphene transfer with the use of a supporting layer casted on top of the sample. Here, in this study, “quasi free-standing” graphene was realized using the weakly-interacting h-BN layer during a wet transfer process to study the surface corrugation formation on graphene. The weak interaction of graphene with the supporting h-BN layer allows for the growth-induced surface corrugations to be released, enabling the investigation of the primary mechanism for the graphene corrugation behavior during the transfer process. The experimental measurements of surface corrugations were conducted using atomic force microscopy (AFM) to reveal that surface corrugations are formed following the graphene’s crystallographic directions. Density functional theory calculations using the projector augmented-wave (PAW) method and Perdew-Burke-Ernzerhof (PBE) exchange correlation functional were also conducted for two models of “atomic-scale ripples” and “nanoscale wrinkles” and showed that all of them are formed along the crystallographic axis of graphene, which is in good agreement with the experimental observations.
36 MATERIALS SCIENCE↗
Imaginary admittance and charge transfer resistance correlate to the physiological status of Shewanella oneidensis cultures in real time
Monitoring microbial activity is essential for industrial and environmental applications to proceed efficiently. To minimize time and labor-intensive monitoring, a new paradigm is required for in-situ, real time analysis. Since bioconversion of organics is accomplished by microorganisms through the oxidation of feedstocks linked to the reduction of electron acceptors, microorganisms can be viewed as electrochemical catalysts. In this respect, cell membranes have an electrical potential, which is analogous to a conventional capacitor and linked dynamically to cellular activity. Here, in this study, we demonstrate the use of electrochemical impedance spectrometry (EIS) and cyclic voltammetry (CV) for monitoring microbial metabolic activity in real time, in-situ. The effect of organic electron donors as a function of concentration to the physiological status of strains of Shewanella oneidensis was determined. In this study, the pyomelanin overproducer (S. oneidensis ΔhmgA) and the pyomelanin deficient mutant (S. oneidensis ΔmelA) were chosen due to different surface electrochemical characteristics along with differences in oxygen utilization efficiency. CV, relative admittance, phase shift and permittivity changed with growth status and correlated with electron flow from organic carbon sources and terminal electron acceptor availability. This work offers a novel and inexpensive approach to real time monitoring with the advantage of abundant data.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mechanical separations of corn stover anatomical fractions in an integrated feedstock preprocessing system: An experimental and data-driven modeling study
High variabilities of material attributes in lignocellulosic biomass present risks for biofuel and biochemical productions and must be mitigated via preprocessing. Since almost no mechanical device is originally designed for processing biomass, how to operate existing apparatuses with efficient performance has not been investigated extensively. This work presents a study on an integrated screening and air classification to separate cobs and stalks from husks and leaves in corn stover. Prototype machine learning models were developed to assess the feasibility of predicting the process outcome based on the measurable parameters. The models trained upon limited experimental data rendered decent predictive accuracy of yield and purity. The experimental data and modeling results collectively suggest decreasing throughput leads to a higher purity. To the contrary, if throughput increases, a lower purity is likely. A possible trade-off between yield and purity of the separated streams indicates the need for optimal combinations of feedstock size, moisture, and throughput to achieve optimized separations. The results of this study also suggest the need to further improve model predictability by developing more accurate formulations for physics governing the integrated unit operations. To accomplish this, additional experimental data needs to be generated for model training.
09 - BIOMASS FUELS↗
Ten questions concerning reinforcement learning for building energy management
As buildings account for approximately 40% of global energy consumption and associated greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The increased integration of variable energy sources, such as renewables, introduces uncertainties and unprecedented flexibilities, necessitating buildings to adapt their energy demand to enhance grid resiliency. Consequently, buildings must transition from passive energy consumers to active grid assets, providing demand flexibility and energy elasticity while maintaining occupant comfort and health. This fundamental shift demands advanced optimal control methods to manage escalating energy demand and avert power outages. Reinforcement learning (RL) emerges as a promising method to address these challenges. Here, in this paper, we explore ten questions related to the application of RL in buildings, specifically targeting flexible energy management. We consider the growing availability of data, advancements in machine learning algorithms, open-source tools, and the practical deployment aspects associated with software and hardware requirements. Our objective is to deliver a comprehensive introduction to RL, present an overview of existing research and accomplishments, underscore the challenges and opportunities, and propose potential future research directions to expedite the adoption of RL for building energy management.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
CIEL ∗ Ch color map for visualization and analysis of sea ice motion
The International Commission on Illumination (CIE) designed its color space to be perceptually uniform so that a given numerical change in the color code corresponds to perceived change in color. This color encoding is demon- strated to be advantageous in scientific visualization and analysis of vector fields. The specific application is analysis of ice motion in the Arctic where patterns in smooth monthly-averaged ice motion are seen. Furthermore, fractures occurring in the ice cover result in discontinuities in the ice motion. This vector jump in displacement can also be visualized. We then analyze modeled and observed fractures through the use of a metric on the color space, and image amplitude and phase metrics. Amplitude and phase met- rics arise from image registration that is accomplished by sampling images using space filling curves, thus reducing the image registration problem to the more reliable functional alignment problem. We demonstrate this through an exploration of the metrics to compare model runs to an observed ice crack.
97 MATHEMATICS AND COMPUTING↗
Effects of ion adsorption on graphene oxide films and interfacial water structure: A molecular-scale description
Herein we discuss graphene oxide as a promising, emerging separation material, as it is durable, dispersible in water, and has naturally forming functional groups. Bulk studies using graphene oxide flakes have demonstrated impressive metal adsorption. However, little interfacial information about water and metal organization near graphene oxide is available. A mechanistic understanding of water and ions interactions with graphene oxide films is critical toward advanced separations, including improved sorption efficiency and membrane regeneration. We study metal ion and local water organization near graphene oxide thin films formed at the air/water interface. These films are not typical membranes and allow us to determine nanoscale information about the graphene oxide-water interface. We accomplish this with x-ray reflectivity (XR), x-ray fluorescence near total reflection (XFNTR), and vibrational sum frequency generation spectroscopy (SFG). These interface-specific techniques provide the electron density profile normal to the interface, number of adsorbed ions, and information about the orientational ordering and hydrogen-bonding network of interfacial water, respectively. Via XFNTR and SFG, we find that trivalent yttrium ions preferentially adsorb to graphene oxide and affect its structure, compared to divalent strontium and monovalent cesium ions. Two different interfacial water populations can be described, based on their hydrogen bonding strength, and the adsorbed ions affect these populations differently. These results provide fundamental information about ion and water organization at the interface and help address the large computational-experimental agreement gap for graphene oxide systems. Additionally, they are relevant for improved soft-scaffold graphene oxide membranes and downstream applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effective biomass fractionation and lignin stabilization using a diol DES system
A sustainable and renewable biorefinery will increase the economic viability of lignocellulose-derived products. In this study, a diol-based deep eutectic solvent (DES) was developed to reduce the recalcitrance of bamboo, facilitate saccharification and valorize the lignin fraction. The DES pretreatment dramatically enhanced glucan digestibility by the effective removal of lignin (as high as 85.45%) and xylan (91.12%). Notably, the recovered lignin from DES pretreatment was protected during the fractionation, showing well-preserved β-O-4 structures (31.82%–59.06%). The mechanism of lignin protection was analyzed to be accomplished by incorporating the diol hydroxyl functional groups into the α position of the lignin β-O-4 structure via etherification. This work highlighted that diol DES is a promising pretreatment solvent to valorize both cellulose and lignin fractions with high enzymatic hydrolysis yield and high-quality lignin co-product.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Toward Rational Design of Supported Vanadia Catalysts of Lignin Conversion to Phenol
In sustainable chemical engineering, catalytic upgrading of lignocellulosic biomass has recently gained attention for producing renewable platform chemicals. To achieve maximal biomass utilization, upgrading the underutilized lignin components is essential. Among various catalysts for lignin upgrading, supported vanadia (V2O5) catalysts are promising because of their cost-effectiveness and tunability of either dopant metals or catalyst supports. Here, computational studies are conducted to derive rational design guidelines of supported V2O5 catalysts for accomplishing the high catalytic activity of lignin upgrading to phenol, a key compound for producing bioplastics and biofuel blendstocks. Guaiacol was used as the model compound since it comprises the highest portion of depolymerized lignin. Computational mechanistic studies for the catalytic guaiacol conversion to phenol were performed for the V2O5 catalysts on Titania (TiO2) and silica (SiO2) to explain higher experimental phenol yields on V2O5/SiO2 than V2O5/TiO2. The hydrogen migration from the methoxy group to the aryl ring was identified as a rate-determining step, and the overall activation energies on the two catalysts were compared. A structural analysis was carried out for the catalysts and rate-determining transition states to gain further insights from mechanistic studies. It was concluded that the tilt angle of the aryl group in the hydrogen migration transition state is a key descriptor determining the catalytic activity of phenol formation. These features correlate well with activation energies and experimental phenol yields, indicating that they provide design guidelines for supported metal catalysts for lignin upgrading before experiments.
BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
Separation of rare earth element radioisotopes by reverse-phase high-speed counter-current chromatography
Analytical scale purification of rare earth element (REE) radioisotopes is typically accomplished using cation-exchange resins (e.g. AG 50W-X8) and high-performance liquid chromatography (HPLC). Despite the variety of improvements made since the development of this separation process in the 1950s, nearest neighbor separations remain a challenge, as does the issue of irreversible sample adsorption. Herein, we report a study that evaluates the potential of high-speed counter-current chromatography (HSCCC) as an alternative method for purifying REE elements, with specific reference to separations of fission product REE of interest to nuclear forensics. Complementary HSCCC REE separation experiments, one spiked with radiotracer and REE fission product activity, allowed for in depth analysis of resulting fractions from both an elemental (inductively coupled plasma atomic emission spectroscopy, ICP-AES) and radiological (gamma-ray spectrometry, beta counting) purity perspective. The highly reproducible nature of separation profiles generated from HSCCC instruments was leveraged to simplify work-up of samples containing radioisotopes. Subsequent radioanalytical evaluation revealed minimal carryover of Eu into neighboring Sm and Tb fractions (as indicated by presence of 150Eu), and trace contamination of the Tb fraction with Y (as indicated by presence of 91Y). Subtle differences in stationary phase retention across the two columns were reflected in significant variations in decontamination factors of duplicate parallel separations. Furthermore, these differences paired with obtained distribution of radioisotopes provided valuable insights into future improvements. Collectively, this study represents a significant step forward in development of HSCCC technology for task specific REE radioisotope purification.
07 ISOTOPE AND RADIATION SOURCES↗
An attached microalgae platform for recycling phosphorus through biologically mediated fertilizer formation and biomass cultivation
Nutrient management is a global challenge for protecting water bodies from eutrophication and for retaining and sustainably recycling phosphorus within the biosphere. This challenge is especially important for water resource recovery facilities (WRRFs) in jurisdictions that limit nutrient loads in plant effluent. A microalgae-based biofilm platform has been designed, constructed, and tested to remove phosphorus and nitrogen from anaerobic digester (AD) effluent filtrate through cultivating biomass and inducing the precipitation of a mineral called struvite (NH₄MgPO₄ · 6H₂O) using a rotating algae biofilm reactor (RABR). RABRs function by rotating a growth substratum through nutrient rich water and then into the atmosphere, immersing microalgae in both sunlight and water. Photosynthesis is utilized in RABR operation to enhance struvite formation by increasing the pH value within the biofilm through the uptake of carbon dioxide from solution. Measurements of pH trended higher with depth through the biofilm when exposed to light confirming the function of photosynthesis in increasing pH and, as a consequence, struvite formation. In addition, reducing RPM allows more time for water to evaporate through exposure of the biofilm to the atmosphere and provides a management option to exceed struvite solubility product. Struvite precipitation was predicted based on chemical analysis and MINTEQ modeling of ADE, was confirmed using Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy, and quantified by determining ash content. Increase in pH within the biofilm was confirmed as photosynthetic photon flux density increased. While struvite precipitation and removal from wastewater is conventionally accomplished through physicochemical methods, this research is the first report of struvite enhanced formation through algae biofilm-based photosynthesis processes.
09 BIOMASS FUELS↗
Peridynamic elastic waves in two-dimensional unbounded domains: Construction of nonlocal Dirichlet-type absorbing boundary conditions
The focus of this paper is on application of peridynamics (PD) to propagation of elastic waves in unbounded domains. We construct absorbing boundary conditions (ABCs) derived from a semi-analytical solution of the PD governing equation at the exterior region. This solution is made up of a finite series of plane waves, as fundamental solutions (modes), which satisfy the PD dispersion relations. The modes are adjusted to transmit the energy from the interior region (near field) to the exterior region (far field). The corresponding unknown coefficients of the series are found in terms of the displacement field at a layer of points adjacent to the absorbing boundary. This is accomplished through a collocation procedure at subregions (clouds) around each absorbing point. The proposed ABCs offer appealing advantages, which facilitate their application to PD. They are of Dirichlet-type, hence their implementation is relatively simple as no derivatives of the field variables are required. They are constructed in the time and space domains and thus application of Fourier and Laplace transforms, cumbersome for nonlocal models, is not required. At the discrete level, the modes satisfy the same numerical dispersion relations of the near field, which makes the far-field solution compatible with that of the near field. We scrutinize the performance of the proposed ABCs through several examples. So our investigation shows that the proposed ABCs perform stably in time with an appropriate level of accuracy even in problems characterized by highly-dispersive propagating waves, including crack propagation in semi-unbounded brittle solids.
42 ENGINEERING↗
A conservative discontinuous-Galerkin-in-time (DGiT) multirate time integration framework for interface-coupled problems with applications to solid–solid interaction and air–sea models
In this paper we extend the DGiT multirate framework, developed in Connors and Sockwell (2022) for scalar transmission problems, to a solid–solid interaction (SSI) problem involving two coupled elastic solids and a coupled air–sea model with the rotating, thermal shallow water equations. In so doing we aim to demonstrate the broad applicability of the mathematical theory and governing principles established in Connors and Sockwell (2022) to coupled problems characterized by subproblems evolving at different temporal scales. Further, multirate time integration algorithms employing different time steps, optimized for the dynamics of each subproblem, can significantly improve simulation efficiency for such coupled problems. However, development of multirate algorithms is a highly non-trivial task due to the coupling, which can impact accuracy, stability or other desired properties such as preservation of system invariants. DGiT provides a general template for multirate time integration that can achieve these properties. To elucidate the manner in which DGiT accomplishes this task, we fully detail each step in the application of the framework to the SSI and air–sea coupled problems. Numerical examples illustrate key properties of the resulting multirate schemes for both problems.
42 ENGINEERING↗
Major element composition controls rare earth element solubility during leaching of coal fly ash and coal by-products
Coal combustion ash and pre-combustion coal refuse are currently under consideration as potential sources of rare earth elements. One of the early steps in recovering REEs from coal by-products is often acid leaching, which can result in low pH leachates with complex aqueous chemistry. The aim of this work was to understand the connection between REE solubility, pH, and major elemental components of leachates for coal by-products. To accomplish this, we investigated the effects of solids concentration (i.e., pulp density) and pH adjustment on REE solubility in acid leachates of coal fly ashes from the Powder River Basin (PRB) and Appalachian Basin in the United States, and a coal processing refuse from the Southwestern U.S. For PRB ashes, the concentrations of soluble REEs generally increased with increasing pulp density; however, at pulp density values above 80–100 g/L, the soluble REE concentrations in the leachates were markedly lower. Similarly, the soluble concentrations of other major solutes (Fe, Al, Si) that leached from PRB fly ashes were also non-linear with pulp density. These major elements tended to reach maximum concentration values at 60–70 g/L pulp density. In contrast, for the Appalachian fly ashes and the coal by-product, soluble concentrations of REE and major elements in leachates increased linearly with pulp density. Chemical equilibria calculations of mineral saturation indices indicated that trends in soluble REE concentrations could be explained by saturation conditions for Fe and Al-(hydr)oxides and possibly sulfate minerals, but not lanthanide hydroxides. Furthermore, pH adjustment of the acid leachates showed that REEs and many major solutes were removed from solution at pH values above 4.5, also consistent with Fe- and Al-(hydr)oxide precipitation. These results highlight the importance of understanding the chemical composition of leachates when designing REE recovery processes for low-grade geologic feedstocks and that precipitation of hydr(oxide) or sulfate minerals of major elements rather than discreet formation of REE mineral phases could be used for process optimization.
01 COAL, LIGNITE, AND PEAT↗
A Potts Model parameter study of particle size, Monte Carlo temperature, and “Particle-Assisted Abnormal Grain Growth”
A Potts Model was proposed to account for temperature and particle heterogeneity-dependent Zener Pinning. This was accomplished by relating the random fluctuations of grain boundary position allowed by the Potts Model switching probability at finite simulation temperature to experimentally observed grain growth stagnation behavior. We assume that these fluctuations arise from random fluctuations in the thermodynamic and kinetic properties of the grain boundaries and/or interfaces as they change with temperature. As an application of this model, the grain growth kinetics of U-10 wt. % Mo nuclear fuels were simulated with the input of microstructural images during different heat treatment processes. Simulated average grain growth behavior is in good agreement with experiments.
Frazier, William E.↗
Overcoming small minirhizotron datasets using transfer learning
Minirhizotron technology is widely used to study root growth and development. Yet, standard approaches for tracing roots in minirhiztron imagery is extremely tedious and time consuming. Machine learning approaches can help to automate this task. However, lack of enough annotated training data is a major limitation for the application of machine learning methods. Transfer learning is a useful technique to help with training when available datasets are limited. In this paper, we investigated the effect of pre-trained features from the massives-cale, irrelevant ImageNet dataset and a relatively moderate-scale, but relevant peanut root dataset on switchgrass root imagery segmentation applications. We compiled two minirhizotron image datasets to accomplish this study: one with 17,550 peanut root images and another with 28 switchgrass root images. Both datasets were paired with manually labeled ground truth masks. Deep neural networks based on the U-net architecture were used with different pre-trained features as initialization for automated, precise pixel-wise root segmentation in minirhizotron imagery. We observed that features pre-trained on a closely related but relatively moderate size dataset like our peanut dataset were more effective than features pre-trained on the large but unrelated ImageNet dataset. Here, we achieved high quality segmentation on peanut root dataset with 99.04% accuracy at the pixel-level and overcame errors in human-labeled ground truth masks. By applying transfer learning technique on limited switchgrass dataset with features pre-trained on peanut dataset, we obtained 99% segmentation accuracy in switchgrass imagery using only 21 images for training (fine tuning). Furthermore, the peanut pre-trained features can help the model converge faster and have much more stable performance.
59 BASIC BIOLOGICAL SCIENCES↗
The sum is greater than the parts: exploiting microbial communities to achieve complex functions
We report multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.
59 BASIC BIOLOGICAL SCIENCES↗