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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Synthetic Electricity Market Data Generation and HERON Use Case Setup of Advanced Nuclear Reactors Coupled with Thermal Energy Storage Systems

This study evaluates and optimizes advanced nuclear reactors coupled with thermal energy storage (TES) systems in an Integrated Energy System (IES) architecture to enable advanced nuclear power plants (A NPP) to participate in multi-commodity markets, thus enhancing their economic competitiveness. Nuclear-TES coupling scenarios studied herein are designed attenuate the nuclear heat dynamics and defer energy delivery to a later time, enabling the nuclear reactor to continue operating at or near steady-state design conditions as usual while also enabling flexible generation. Three A-NPPs, namely, an advanced light-water reactor (A LWR), a high temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating the technoeconomic of thermally balanced energy storage coupling design for thermal power extraction. Each of the reactor technologies were evaluated in two different electricity markets. Stochastic optimization approach was adopted which included the evaluation of price signals from the Pennsylvania-New Jersey-Maryland (PJM) market, and Electric Reliability Council of Texas (ERCOT), using an autoregressive moving average (ARMA) model. Risk Analysis Virtual Environment (RAVEN) tool and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON), were used to perform dispatch and capacity optimization, using the price data provided by the ARMA models. The results from the Nuclear-TES use cases will be used to design and characterize dynamic integrated system behavior and feedback.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

THE STRUCTURE FUNCTION OF THE FREE NEUTRON AT HIGH X-BJORKEN

Understanding the internal structure of nucleons is one of the primary goal of nuclear physicists. As protons and neutrons are only the bound state solution of the QCD lagrangian (at least inside atomic nuclei), studying protons and neutrons helps uncover nuclear struc ture. Due to its easy availability, many studies on protons have been done on a wide range of kinematics. However, free neutron targets are not readily achievable. So, any information on neutrons has to be extracted from neutron-rich nuclei, and some nuclear models have to be used to subtract the contributions from other nucleons to extract the information on neutrons. So, the Barely Off-shell Nucleon Structure (BONuS12) experiment at Jefferson Lab was conducted to overcome these challenges by using spectator tagging. The experiment effectively created a quasi-free neutron target by scattering electrons off a deuterium target and detecting low-momentum, backward-moving protons using a custom-built Radial Time Projection Chamber (RTPC). Selecting the low momentum and backward-moving spectators would enable us to minimize the model-dependent effects due to final state interactions and target fragmentation. The RTPC was a 40 cm-long cylindrical detector that works on the principle of gaseous ionization. It had three layers of Gas Electron Multipliers (GEMs) for charge amplification and a surrounding readout pad. The scattered electrons were measured using the CLAS12 detector, and data were collected using a 10.4 GeV electron beam dur ing Spring and Summer 2020. Using spectator tagging, we extracted the structure function ratio Fn 2 of the quasi-free neutron in the deep inelastic scattering at high x, upto x ~ 0.8. The result was extracted in the region with the invariant mass W > 1.8 GeV/c2, and Q2 in the range 1.3 to 11 GeV2. This dissertation presents the methodology, event selection criteria and refinements, estimation and subtraction of backgrounds, and complete analysis of extraction of Fn 2/Fp 2 in a model-independent way. Also, systematic uncertainties in our final analysis will be discussed in detail.

Pokhrel, Madhusudhan [Old Dominion Univ., Norfolk,↗
DOE OSTI2022

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Clean energy infrastructure depends on chalcopyrite: the mineral that contains 70% of the world’s copper reserves, as well as a range of precious and critical metals. Smelting is the only commercially viable route to process chalcopyrite, where the oxygen-rich environment dictates the distribution of impurities and numerous upstream and downstream unit operations to manage noxious gases and by-products. However, unique opportunities to address urgent challenges faced by the copper industry arise by excluding oxygen and processing chalcopyrite in the native sulfide regime. Through electrochemical experiments and thermodynamic analysis, gaseous sulfur and electrochemical reduction in a molten sulfide electrolyte are shown to be effective levers to selectively extract the elements in chalcopyrite for the first time. We present a new process flow to supply the increasing demand for copper and byproduct metals using electricity and an inert anode, while decoupling metal production from fugitive gas emissions and oxidized by-products.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗
DOE OSTI2022

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗
DOE OSTI2022

Product specific thermal degradation kinetics of bisphenol F epoxy in inert and oxidative atmospheres using evolved gas analysis–mass spectrometry

Knowledge of the degradation kinetics for polymer materials is important for understanding thermal stability. In this study, evolved gas analysis–mass spectrometry and pyrolysis gas-chromatography-mass spectrometry were evaluated for the potential to deliver additional insight into thermal degradation kinetics of diglycidal ether of bisphenol F (DGEBF) epoxy thermoset under inert and oxidative atmospheres. Degradation products of selected precursor ions were evaluated for their uniqueness to the specific precursor using extracted ion thermographs. Unique mass peaks, solely attributed to a single reaction pathway of a specific product, were determined from extracted ion thermographs and used to determine both activation energy (E a ) and pre-exponential factors for the specific primary reaction pathways. These primary reaction pathways for DGEBF epoxy degradation were then evaluated in the context of transition state theory (TST) and related transition state enthalpies (ΔH ‡ ) and entropies (ΔS ‡ ) of activation to further elucidate the degradation process. It was determined under pyrolysis conditions, as suggested by the E a , the formation of bisphenol F monomer was the rate-limiting step toward the formation of xanthene and phenol. In contrast, under thermo-oxidative conditions, reactions involving oxygen containing species were identified as the rate-limiting step for all observed products based on the large negative ΔS ‡ calculated from TST. This work demonstrates a powerful combination of technique and theory that can provide new insight into the degradation of polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Surface effects on deuterium permeation through vanadium membranes

Dense vanadium-based membranes offer high permeability and perfect selectivity to hydrogen isotopes, maintain favorable neutronic properties, and are compatible with liquid metals such as PbLi. These properties make vanadium membranes a promising fusion fuel cycle technology for processes such as tritium extraction from PbLi and exhaust processing. Surface contamination has a deleterious effect on the gas-phase hydrogen permeation through vanadium, and the reported permeabilities range from 10 -14 to 10 -7 mol m -1 s -1 Pa -0.5 . Thin dense films of palladium applied to clean vanadium surfaces enable a consistently high hydrogen permeability. In this study, uncoated vanadium resulted in deuterium permeabilities ranging from 2.8 × 10 -11 to 6.4 × 10 -9 mol m -1 s -1 Pa -0.5 at 300 °C–700 °C, respectively. Post-test analysis revealed a VO x surface layer and VC x subsurface layer formed on the feed side, while the as-received surface oxide dissolved leaving a submonolayer oxide on the permeate surface. Furthermore, the Pd-coated V resulted in a maximum deuterium permeability of 2.1 × 10 -7 m -1 s -1 Pa -0.5 at 375 °C upon activation of the Pd surface by oxidation and reduction. The deuterium permeation declined upon heating to 500 °C due to intermetallic diffusion between the Pd and V. The Mo 2 C-coated V resulted in deuterium permeabilities ranging from 2.7 × 10 -10 to 1.8 × 10-9 at 500 °C–700 °C, respectively, and a post-test analysis found the carbon in the Mo 2 C layer had dissolved into the V near the interface.

13 HYDRO ENERGY↗
DOE OSTI2023

Aftercooler exhaust duct protection

A turbine engine assembly includes a condenser that is at least partially disposed within the core flow path where water is extracted from the exhaust gas flow, an evaporator system that is at least partially disposed within the core flow path that is upstream of the condenser where thermal energy from the exhaust gas flow is utilized to generate a steam flow. An aftercooler provides a cooling flow that is selectively injected into the core flow path upstream of at least the condenser for cooling the exhaust gas flow in response to a parameter that is indicative of an engine operating parameter that exceeds a predefined condition.

Sobanski, Jon Erik↗
DOE OSTI2025

A new database website for nuclear level densities

We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. Here, this platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

LIQUID AIR COMBINED CYCLE

Hybrid integration of thermal energy storage with gas turbines can provide compact, cost-effective, long-duration energy storage while reducing the fuel consumption of dispatchable resources needed for the reliability of renewable dominant electric grids. The Liquid Air Combined Cycle™ (LACC) is a hybrid energy storage system using cryogenic liquid air as an energy storage medium and gas turbine exhaust heat to extract stored energy. The storage tank is charged using liquefaction processes employing electric motor-driven compressors to pressurize the air, heat exchangers to reject heat of compression, and expanders to reduce the temperature and liquefy the air. Proven cryogenic refrigeration processes can be selected based on capital cost (per kg/s of liquid air produced), efficiency (kJ per kg of air produced), and operating factors including startup speed and load following capability. This paper presents results of studies undertaken for the U.S. Department of Energy to evaluate cost and performance tradeoffs for charge and discharge cycle components, optimize charge and discharge cycles, and assess the techno-economic potential of LACC technology.

Conlon, William↗
DOE OSTI2024

Targeted Rare Earth Element Extraction from Mine Drainage Treatment Solids Informed by Advanced Characterization

In support of a clean energy transition in the U.S., National Energy Technology Laboratory (NETL) has collaborated with staff at Hedin Environmental and students at the University of Pittsburgh to characterize critical mineral content and recovery potential from acid mine drainage treatment solids (AMD solids). AMD solids in Appalachia are an unconventional feedstock of rare earth elements (REEs), with potential of suppling 1,102 tons REE/year. To inform recovery efforts, select AMD solids were examined using synchrotron microprobe analysis in conjunction with USGS-developed geochemical modeling to indicate likely phases hosting critical minerals (REE, Co, Ni, etc.) and associated metals . More than 100 AMD solids were collected from 94 passive AMD treatment systems in Pennsylvania, where limestone aggregates are used for acidity neutralization. As pH increases, dissolved metals and critical minerals in AMD are attenuated as surface coatings on limestone. The collected AMD solids contained up to 2000 mg/kg REE, up to 13,000 mg/kg transition metals (Co, Ni, Zn) and up to 440 mg/kg Li. Regardless of the diverse chemical compositions from AMD solids (Al-rich, Mn-rich, or Al,Fe,Mn-rich), REEs were mostly associated with Al and Mn (hydr)oxides, while select heavy REEs (e.g., Gd, Dy) were co-localized with Fe (hydr)oxides. Co and Ni have different distribution zones, while both co-localized with Mn (hydr)oxides. Based on this characterization, NETL developed a patent-pending innovative step-leaching protocol, “Targeted Rare Earth Extraction (TREE)” to effectively recover up to 90% REE and 60% Co in separate steps. In addition, select post-TREE solid residuals (purified Al oxides, or Mn oxides) can be further developed into functional materials (e.g., lithium and CO2 sorbents) needed for green energy transition and carbon management. This characterization-informed approach as well as TREE processing from AMD solids can be used for other legacy wastes (e.g., coal ash, oil and gas drill cutting, mine tailings), and offers an opportunity to transform waste streams into environmental and economic assets that meet U.S. Department of Energy and U.S. Environmental Protection Agency goals.

characterization and extraction of rare earth elem↗
DOE OSTI2021

Magnetic Nanoparticle Extraction of Lithium from Produced Waters: CRADA 483 [Abstract only]

In this project, we will synthesize, evaluate, and screen a set of new sorbents that have high capacity and selectivity for lithium. Sorbent performance will be evaluated by conducting Li extraction tests with produced water samples supplied by ConocoPhillips Company, Moselle Technologies, and Cascade Natural Resources. The best performing of these sorbents based on Li uptake capacity and selectivity will be produced as a magnetic nanoparticle and subjected to extended cycle testing in our laboratory bench-scale magnetic separator system. Moselle has acquired an exclusive license to the background IP associated with this magnetic nanoparticle mineral extraction technology and wishes to foster implementation of the technology in the oil & gas industry through this CRADA. Moselle will support PNNL in the design of a commercial-scale magnetic separator system tailored for lithium production. The goal is to collect sufficient information to support a decision by our industry partners to invest in a subsequent field demonstration at one of our partner’s field sites as a prerequisite to advancing this technology towards commercialization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimizing the fuel efficiency of an opposed piston engine for electric power generation

This paper investigates the optimal crankshaft motion for an opposed piston (OP) engine in a novel hybrid architecture to maximize fuel efficiency. The OP engine was selected for this work due to its inherent thermodynamic benefits and the balanced nature of the engine which can achieve downsizing through reducing the number of cylinders rather than the individual cylinder volume. The typical geartrain required on an OP engine was exchanged for two electric motors, reducing friction loss and decoupling the crankshafts. Using the motors to control the crankshaft motion profiles, this architecture introduces capabilities to dynamically vary compression ratio, combustion volume, and scavenging dynamics. To leverage these opportunities, an optimization scheme was developed utilizing nonlinear optimization of a 0-D model to compute the crankshaft motion profile that maximizes the work generated by the system. This optimization was then iteratively coupled with a high fidelity model which supplies the cylinder flow boundary conditions. This iterative approach reduces the model complexity used in the optimal control problem (OCP) while capturing the gas exchange dynamics critical to the 2-stroke cycle of the OP engine. By using the rate of change of motor torque as the input to the OCP, the torque fluctuation in a single cycle can be limited to ensure tracking feasibility. The results show crankshaft velocity slows during the compression stroke and conversely accelerates during the expansion stroke, reducing the peak motor torque required for control and thus reducing the motor losses. The extended residence time at top dead center, however, leads to an increase in heat transfer, illustrating the trade-off between the work extraction efficiency and the indicated engine efficiency.

Engineering↗
DOE OSTI2025

Extraction, purification, and reuse of dyes from coloured polyester textiles

The removal of dyes from coloured textile waste represents a sustainable approach to textile recycling, enabling the recovery of valuable chemical, and material resources that would otherwise be discarded. Up to 40% of the greenhouse gas emissions from textiles originate from dye production, making efficient recycling of dyes a major opportunity for curbing emissions and minimizing waste in both textile manufacturing and recycling. Here, in this study, we demonstrate a process for the extraction, purification, and reuse of mixed dyes from polyester textiles using bio-based, non-hazardous solvents selected on the basis of computational predictions for polyester and dye solubilities. Extracted dyes are purified to individual compounds using counter-current chromatography and analysed via liquid chromatography-mass spectrometry. Post-extraction characterization of the extracted dyes and polymer substrate confirms dye colour retention and polyester fabric property preservation. Dye recycling is demonstrated by redyeing colour-free fabrics with the recovered dyes. We further show a potential process configuration for dye removal using a flow-through reactor packed with a textile substrate. The proposed dye removal process produces reusable, recyclable dyes, and dye-free fabrics, thus facilitating textile recycling.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measurement of $d^2 \sigma/d|\vec{q}|d E_{avail}$ and 2p2h contribution using charged current $\nu_\mu$ interactions in the NOvA Near Detector

This Thesis presents the analysis methods and measurement of the $d^2 \sigma/d|\vec{q}|d E_{avail}$-CC inclusive cross section that describes neutrino scattering in a predominantly hydrocarbon medium. Studies that are prerequisite for the analysis including, variable determinations, event selections, efficiency, purity determinations, and systematic uncertainty estimations, are summarized. Tests of the analysis are also detailed, and shown to reproduce the input distributions. The double-differential cross-section measurement provides the foundation for determination of the inclusive rate for the excess induced by 2p2h processes together with nuclear medium effects that are not described by the Fermi gas model. The methodology for the extraction of this rate, defined as the excess observed relative to the rate estimated for known single-nucleon interactions, is described in detail. The following new measurements are reported in this Thesis: (1) The $\nu_\mu-$CC inclusive double-differential cross section as a function of three-momentum transfer and available hadronic energy, for an average $E_\nu$ of 1.8 GeV, is obtained. The double-differential cross section value that obtains when the bin widths are taken to be the dimensions of the entire analysis domain, e.g. $0.2 \le |\vec{q}| \le 2.0 GeV/c$ and $0.0 \le E_{avail} \le 2.0$ GeV, is inclusive cross section is $(6.05 \pm 0.75)\times10^{-39}$ cm$^2$/GeV/GeV/$c$/nucleon. An event excess attributed to 2p2h-MEC processes is observed; most of the rate occurs in a contiguous phase space region $0.3 \le |\vec{q}| \le 1.0$ GeV$/c$ $0.0 \le E_{avail} \le 0.35$ GeV. This rate represents $12.0\pm 6.5\%$ of the observed CC inclusive cross section; its cross section ratio relative to CCQE scattering is estimated to be $44.3 \pm 23.9\%$.

Olson, Travis Grant↗
DOE OSTI2022

Triton Field Trials - Changes in Habitats, a Literature Review of Monitoring Technologies

Marine energy devices are installed in highly dynamic environments and have the potential to affect benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats. Selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years, as well as national and international guidelines for surveying habitats around offshore activities. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Sampling designs varied considerably among the reviewed studies but transect was the predominant design for surveying seafloor, epifauna, and pelagic habitats. The most common data analyses were univariate and multivariate statistical analyses aimed at calculating and comparing biodiversity indices, characterizing faunal assemblages or sediment classes, or modeling the distribution of animals related to abiotic parameters. Technologies and sampling methods adaptable and designed to work efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

What’s in My Toolkit? A Review of Technologies for Assessing Changes in Habitats Caused by Marine Energy Development

Marine energy devices are installed in highly dynamic environments and have the potential to affect the benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats, and selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Technologies and sampling methods that are designed for working efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Bioremediation of heavy oily sludge: a microcosms study

Oily sludge is a residue from the petroleum industry composed of a mixture of sand, water, metals, and high content of hydrocarbons (HCs). The heavy oily sludge used in this study originated from Colombian crude oil with high density and low American Petroleum Institute (API) gravity. The residual waste from heavy oil processing was subject to thermal and centrifugal extraction, resulting in heavy oily sludge with very high density and viscosity. Biodegradation of the total petroleum hydrocarbons (TPH) was tested in microcosms using several bioremediation approaches, including: biostimulation with bulking agents and nutrients, the surfactant Tween 80, and bioaugmentation. Select HC degrading bacteria were isolated based on their ability to grow and produce clear zones on different HCs. Degradation of TPH in the microcosms was monitored gravimetrically and with gas chromatography (GC). The TPH removal in all treatments ranged between 2 and 67%, regardless of the addition of microbial consortiums, amendments, or surfactants within the tested parameters. The results of this study demonstrated that bioremediation of heavy oily sludge presents greater challenges to achieve regulatory requirements. Additional physicochemical treatments analysis to remediate this recalcitrant material may be required to achieve a desirable degradation rate.

59 BASIC BIOLOGICAL SCIENCES↗