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DOE OSTI2024

Comprehensive Study of Carrier Recombination in High‐Efficiency CdTe Solar Cells Using Transient Photovoltage

Cadmium telluride (CdTe) solar cells represent a commercially successful photovoltaic technology, with an annual production capacity approaching 20 GW. However, improving the open-circuit voltage (V OC ) remains challenging. This study aims to deepen the understanding of charge carrier recombination in CdTe solar cells and to explore alternative dynamical characterization methods that address the limitations found in conventionally used time-resolved photoluminescence for CdTe solar cells. Transient photovoltage and transient photocurrent techniques are utilized to investigate charge carrier dynamics under conditions resembling real-world solar cell operation. The results reveal that an effective nonradiative recombination lifetime of 580 ns dominates the charge dynamics at VOC values below 850 mV. Above this threshold, radiative recombination becomes significant, with a radiative recombination coefficient of 1.1 × 10 −9 cm 3 s −1 . Additionally, the stationary charge carrier density at 1 sun is determined to be around 1 × 10 14 cm −3 . By accurately determining both radiative and nonradiative recombination, this work provides a comprehensive understanding of carrier dynamics in high-performing CdTe devices and paves the way for improving the V OC and performance of CdTe solar cells.

CdTe solar cells↗

DOE OSTI2019

Comprehensive genomic and transcriptomic analysis of polycyclic aromatic hydrocarbon degradation by a mycoremediation fungus, sp. KUC8613

The environmental accumulation of polycyclic aromatic hydrocarbons (PAHs) is of great concern due to potential carcinogenic and mutagenic risks, as well as their resistance to remediation. While many fungi have been reported to break down PAHs in environments, the details of gene-based metabolic pathways are not yet comprehensively understood. Specifically, the genome-scale transcriptional responses of fungal PAH degradation have rarely been reported. In this study, we report the genomic and transcriptomic basis of PAH bioremediation by a potent fungal degrader, Dentipellis sp. KUC8613. The genome size of this fungus was 36.71 Mbp long encoding 14,320 putative protein-coding genes. The strain efficiently removed more than 90% of 100 mg/l concentration of PAHs within 10 days. The genomic and transcriptomic analysis of this white rot fungus highlights that the strain primarily utilized non-ligninolytic enzymes to remove various PAHs, rather than typical ligninolytic enzymes known for playing important roles in PAH degradation. PAH removal by non-ligninolytic enzymes was initiated by both different PAH-specific and common upregulation of P450s, followed by downstream PAH-transforming enzymes such as epoxide hydrolases, dehydrogenases, FAD-dependent monooxygenases, dioxygenases, and glycosyl- or glutathione transferases. Among the various PAHs, phenanthrene induced a more dynamic transcriptomic response possibly due to its greater cytotoxicity, leading to highly upregulated genes involved in the translocation of PAHs, a defense system against reactive oxygen species, and ATP synthesis. Finally, our genomic and transcriptomic data provide a foundation of understanding regarding the mycoremediation of PAHs and the application of this strain for polluted environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Magnetic resonance imaging as a non-invasive method for the assessment of pancreatic fibrosis (MINIMAP): a comprehensive study design from the consortium for the study of chronic pancreatitis, diabetes, and pancreatic cancer

Characteristic features of chronic pancreatitis (CP) may be absent on standard imaging studies. Quantitative Magnetic Resonance Imaging (MRI) techniques such as T{sub 1} mapping, extracellular volume (ECV) fraction, diffusion-weighted imaging (DWI) with apparent diffusion coefficient map (ADC), MR elastography (MRE), and T{sub 1}-weighted signal intensity ratio (SIR) have shown promise for the diagnosis and grading severity of CP. However, radiologists still use the Cambridge classification which is based on traditional ductal imaging alone. There is an urgent need to develop new diagnostic criteria that incorporate both parenchymal and ductal features of CP seen by MRI/MRCP. Designed to fulfill this clinical need, we present the MINIMAP study, which was funded in September 2018 by the National Institutes of Health. This is a comprehensive quantitative MR imaging study which will be performed at multiple institutions in well-phenotyped CP patient cohorts. We hypothesize that quantitative MRI/MRCP features can serve as valuable non-invasive imaging biomarkers to detect and grade CP. We will evaluate the role of T{sub 1} relaxometry, ECV, T{sub 1}-weighted gradient echo SIR, MRE, arteriovenous enhancement ratio, ADC, pancreas volume/atrophy, pancreatic fat fraction, ductal features, and pancreatic exocrine output following secretin stimulation in the assessment of CP. We will attempt to generate a multi-parametric pancreatic tissue fibrosis (PTF) scoring system. We anticipate that a quantitative scoring system may serve as a biomarker of pancreatic fibrosis; hence this imaging technique can be used in clinical practice as well as clinical trials to evaluate the efficacy of agents which may slow the progression or reverse measures of CP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

Comprehensive Evaluation of Fast-Response, Reynolds-Averaged Navier–Stokes, and Large-Eddy Simulation Methods Against High-Spatial-Resolution Wind-Tunnel Data in Step-Down Street Canyons

Three computational fluid dynamics (CFD) methods with different levels of flow-physics modelling are comprehensively evaluated against high-spatial-resolution wind-tunnel velocity data from step-down street canyons (i.e., a short building downwind of a tall building). The first method is a semi-empirical fast-response approach using the Quick Urban Industrial Complex (QUIC-URB) model. The second method solves the Reynolds-averaged Navier–Stokes (RANS) equations, and the third one utilizes a fully-coupled fluid-structure interaction large-eddy simulation (LES) model with a grid-turbulence inflow generator. Unlike typical point-by-point evaluation comparisons, here the entire two-dimensional wind-tunnel dataset is used to evaluate the dynamics of dominant flow topological features in the street canyon. Each CFD method is scrutinized for several geometric configurations by varying the downwind-to-upwind building-height ratio (H d /H u ) and street canyon-width to building-width aspect ratio (S / W) for inflow winds perpendicular to the upwind building front face. Disparities between the numerical results and experimental data are quantified in terms of their ability to capture flow topological features for different geometric configurations. Ultimately, all three methods qualitatively predict the primary flow topological features, including a saddle point and a primary vortex. But, the secondary flow topological features, namely an in-canyon separation point and secondary vortices, are only well represented by the LES method despite its failure for taller downwind building cases. Misrepresentation of flow-regime transitions, exaggeration of the coherence of recirculation zones and wake fields, and overestimation of downwards vertical velocity into the canyon are the main defects in QUIC-URB, RANS and LES results, respectively. All three methods underestimate the updrafts and, surprisingly, QUIC-URB outperforms RANS for the streamwise velocity component, while RANS is superior to QUIC-URB for the vertical velocity component in the street canyon.

58 GEOSCIENCES↗

DOE OSTI2020

A Comprehensive Scientific Survey of Excipients Used in Currently Marketed, Therapeutic Biological Drug Products

The steady development of biotechnology-derived therapeutic biologics over the last few decades has generated drugs that are now standard medical treatments for a range of indications. While the development of protein products has surged in recent years, the formulation and delivery of these complex molecules have relied on drug-specific studies and, in some instances, data from non-proteinaceous drug products. The commonalities, trends, and gaps in excipient technologies used to support the development of therapeutic proteins largely remain unexplored due to the drug-specific nature of many formulations. Using a comprehensive and relational database approach, we aimed to provide a scientific survey of all approved or licensed biotechnology-derived drug products with the goal of providing evidence-based information on common attributes and trending features in protein product excipients. We examined 665 formulations, and 395 unique formulations based on having unique excipients within them, that supported 211 therapeutic proteins as of June 2020. We report the prevalence of each excipient class and excipient chemical used in eight different drug types including monoclonal antibodies, antibody conjugates, cytokines and growth factors, enzymes, polypeptide hormones, pulmonary surfactants, recombinant fusion proteins, and toxins. We also report the prevalence by excipient type among all therapeutic proteins, in the context of each drug’s recommended pH range, concentration ranges for excipients, and route of administration. The results of our analyses indicate certain excipients common to monoclonal antibodies, cytokines, and polypeptide hormones. We also report on excipients unique to protein drug products, such as amino acids, solubilizers, and lyoprotectants. Overall, our report summarizes the current landscape of excipients used in marketed biotechnology-derived therapeutic biologic products.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Exploring urban typologies using comprehensive analysis of transportation dynamics

Abstract As urban areas continue to expand and develop, categorizing cities into typologies offers a valuable framework for understanding metropolitan dynamics and fostering inter-city collaboration. However, existing typologies related to urban mobility have limitations, failing to consider cities within a single large urban region and often overlooking crucial dimensions such as trip demand and traffic flow. In this paper, we introduce a transportation-focused characterization for cities within a large urban region, specifically the San Francisco Bay Area, California. We incorporate over 40 metrics across five transportation dimensions: trip demand, road network, multi-modal network, traffic flow, and land use. Specifically, for the trip demand dimension, we include metrics capturing residents’ trip characteristics, such as mode share, intra-city trips, and inter-city trips. Additionally, we analyze the purpose of trips entering the city to gain a deeper understanding of incoming trip patterns. In the traffic flow dimension, we examine metrics like vehicle miles traveled, delay, and congestion to assess the traffic conditions on the street network. These, combined with other dimensions, provide a comprehensive view of a city’s transportation dynamics. Using unsupervised machine learning clustering methods, we identified eight distinct typologies for the Bay Area: Live Work Cities; Job and Activity Magnet Cities; Anchor Cities; Multi-modal Cities; Hyper-connected Cities; Low-density Residential Cities; Medium-density Residential Cities; and Mixed-use Residential Cities. Our findings show that many clusters are strongly influenced by trip demand and traffic flow metrics. Finally, we examine the practicality of this typology and its potential to guide collaborative transportation management strategies. The typologies provide a foundation for dialogue among Bay Area cities, focusing on evaluating shared characteristics and leveraging successes or challenges to develop unified strategies for transportation management.

Kuncheria, Anu↗

DOE OSTI2026

Thermokinetic mixing compounding for polymer composites – a comprehensive review

High-speed thermokinetic mixers (K-mixers) represent an advanced compounding technology that employs intense shear and friction to convert kinetic energy directly into thermal energy. This mechanism enables rapid mixing cycles, often under one minute, facilitating exceptional filler dispersion while minimizing the material’s thermal history. This is particularly effective for compounding challenging materials, including heat-sensitive biopolymers, wet filler feedstocks, and nanofillers prone to agglomeration. As the first comprehensive review of this technology, this article synthesizes the fundamental principles of thermokinetic mixing (K-mixing) and surveys recent advances in polymer composite fabrication. We contrast the working principles of K-mixers with conventional twin-screw extrusion, highlighting distinct advantages in dispersing nanoscale fillers, exfoliating layered materials, and processing wet cellulosic feedstocks and ultra-high filler loadings (e.g., 85 wt%). Furthermore, strategies to optimize filler–matrix interfacial bonding under rapid-processing constraints, such as the kinetic selection of compatibilizers and fiber surface treatments, are evaluated. Finally, we analyze key structure-processing-property relationships and outline future directions in scaling up, reactive processing, and hybrid material development.

Zhang, Xuefeng [University of Maine]↗

DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

DOE OSTI2020

A comprehensive diffusion mobility database comprising 23 elements for magnesium alloys

We report that reliable experimental diffusion coefficients of 10 key alloying elements in Mg obtained by the present authors together with experimental data in the literature enabled us to perform a systematic test of the reliability of diffusion coefficients obtained from DFT calculations. The computed activation energy values were found to be quite accurate (mostly within 0.2 eV) but the computed pre-factors were less reliable. Such insights allowed us to develop a practical and yet robust strategy to perform diffusion mobility assessments by adopting the computed activation energy while fitting only the pre-factor when available experimental data are limited to a narrow temperature range. The overall good agreement between the DFT data and experimental data also gave us the confidence to employ the computed data for those that were still missing or inaccessible from experimental measurements. A systematic assessment of both the measured and computed diffusion data in hcp Mg was performed using the above holistic approach to yield the most comprehensive open Mg mobility database to date, comprising 23 elements (Mg, Ag, Al, Be, Ca, Cd, Ce, Cu, Fe, Ga, Gd, In, La, Li, Mn, Nd, Ni, Pu, Sb, Sn, U, Y, Zn). This more reliable mobility database will contribute to future development of advanced Mg alloys. The holistic approach developed in this study will be very beneficial to the future establishment of reliable mobility databases for other alloy systems as well.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A comprehensive review of solar only and hybrid solar driven multigeneration systems: Classifications, benefits, design and prospective

Depending on the application and demands, different products can be generated utilizing multigeneration systems. To drive such systems, solar energy can be used as a primary energy source or in hybridization with other renewable or nonrenewable energy sources. Solar driven multigeneration systems are appealing due to the broad availability of solar energy and related technologies. Here, the objective of this study is to review, categorize and discuss different configurations, benefits, potentials, challenges, future research directions and market perspectives of solar energy-driven multigeneration systems, comprehensively. This study also reviews how solar energy systems can be used to hybridize systems for multigeneration purposes. Regardless of using fossil fuel backup sources, these systems are classified as (1) solar only-driven and (2) hybrid solar-driven, in which solar energy is used together with other renewable sources. Reviewing the literature demonstrates numerous ways to build solar energy-driven multigeneration systems by coupling a variety of different cycles and devices. Such systems offer multiple benefits such as enhancing the efficiency, reducing capital and operating costs and carbon dioxide emission. Hybridizing solar with other renewable energies enables continuous operation and dispatchability management. This review shows that for configuration selection and design, different thermodynamics, economic and environmental aspects should be considered. To advance the solar driven multigeneration systems development, further multidisciplinary research on different aspects of such systems is necessary. Particularly, investigations should focus on building different prototypes and on conducting experimental assessments. Also, new incentives and long-term purchase agreements for the products must be established.

14 SOLAR ENERGY↗

DOE OSTI2016

First comprehensive structural and biophysical analysis of MAPK13 inhibitors targeting DFG-in and DFG-out binding modes

Background: P38 MAP kinases are centrally involved in mediating extracellular signaling in various diseases. While much attention has previously been focused on the ubiquitously expressed family member MAPK14 (p38α), recent studies indicate that family members such as MAPK13 (p38δ) display a more selective cellular and tissue expression and might therefore represent a specific kinase to target in certain diseases. Methods: To facilitate the design of potent and specific inhibitors, we present in this paper the structural, biophysical, and functional characterization of two new MAPK13-inhibitor complexes, as well as the first comprehensive structural, biophysical, and functional analysis of MAPK13 complexes with four different inhibitor compounds of greatly varying potency. Results: These inhibitors display IC 50 values either in the nanomolar range or micromolar range (> 800-fold range). The nanomolar inhibitors exhibit much longer ligand-enzyme complex half-lives compared to the micromolar inhibitors as measured by biolayer interferometry. Crystal structures of the MAPK13 inhibitor complexes reveal that the nanomolar inhibitors engage MAPK13 in the DFG-out binding mode, while the micromolar inhibitors are in the DFG-in mode. Detailed structural and computational docking analyses suggest that this difference in binding mode engagement is driven by conformational restraints imposed by the chemical structure of the inhibitors, and may be fortified by an additional hydrogen bond to MAPK13 in the nanomolar inhibitors. Conclusions: These studies provide a structural basis for understanding the differences in potency exhibited by these inhibitors. General significance: They also provide the groundwork for future studies to improve specificity, potency, pharmacodynamics, and pharmacokinetic properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Qualitative and quantitative estimation of comprehensive synaptic connectivity in short- and long-term cultured rat hippocampal neurons with new analytical methods inspired by Scatchard and Hill plots

To investigate comprehensive synaptic connectivity, we examined Ca{sup 2+} responses with quantitative electric current stimulation by indium-tin-oxide (ITO) glass electrode with transparent and high electro-conductivity. The number of neurons with Ca{sup 2+} responses was low during the application of stepwise increase of electric current in short-term cultured neurons (less than 17 days in-vitro (DIV)). The neurons cultured over 17 DIV showed two-type responses: S-shaped (sigmoid) and monotonous saturated responses, and Scatchard plots well illustrated the difference of these two responses. Furthermore, sigmoid like neural network responses over 17 DIV were altered to the monotonous saturated ones by the application of the mixture of AP5 and CNQX, specific blockers of NMDA and AMPA receptors, respectively. This alternation was also characterized by the change of Hill coefficients. These findings indicate that the neural network with sigmoid-like responses has strong synergetic or cooperative synaptic connectivity via excitatory glutamate synapses. - Highlights: • We succeed to evaluate the maturation of neural network by Scathard and Hill Plots. • Long-term cultured neurons showed two-type responses: sigmoid and monotonous. • The sigmoid-like increase indicates the cooperatevity of neural networks. • Excitatory glutamate synapses cause the cooperatevity of neural networks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

The critical role of lignin in lignocellulosic biomass conversion and recent pretreatment strategies: A comprehensive review

Heterogeneity and rigidity of lignocellulose causing resistance to its deconstruction have provided technical and economic challenges in the current biomass conversion processes. Lignin has been considered as a crucial recalcitrance component in biomass utilization. An in-depth understanding of lignin properties and their influences on biomass conversion can provide clues to improve biomass utilization. Also, utilization of lignin can significantly increase the economic viability of biorefinery. Recent lignin-targeting pretreatments have aimed not only to overcome recalcitrance for biomass conversion but also to selectively fractionate lignin for lignin valorization. Numerous studies have been conducted in biomass characteristics and conversion technologies, and the role of lignin is critical for lignin valorization and biomass pretreatment development. In this review, we provide a comprehensive review of lignin-related biomass characteristics, the impact of lignin on the biological conversion of biomass, and recent lignin-targeting pretreatment strategies. The desired lignin properties in biorefinery and future pretreatment directions are also discussed.

09 BIOMASS FUELS↗

DOE OSTI2025

Hempseed cell wall polysaccharides are dominated by linear xylans and cellulose: Comprehensive structural profiling of ten cultivars of industrial hemp, Cannabis sativa L .

Hempseed is a rich source of dietary fiber; however, there has been limited research on the variability of carbohydrate composition in hempseed cell walls. The primary aim of this study was to conduct a comprehensive chemical and structural analysis of the cell wall polysaccharides in ten hempseed cultivars. Water-soluble polysaccharides (WSP) and water-insoluble residues (WIR) were isolated and subsequently analyzed for their monosaccharide composition using HPAEC-PAD, glycosyl linkage analysis using GC–MS, and structural characterization via NMR spectroscopy. All hempseed cultivars contained a high proportion of insoluble fibers and smaller amounts of soluble polysaccharides. Glucose and xylose were the most abundant components of the WIR fractions, while the WSP fractions contained abundant amounts of galactose, galacturonic acid, arabinose, rhamnose, and mannose. The results of linkage and spectroscopic analysis were consistent with the compositional analysis, identifying cellulose and acetylated linear xylans as primary components of WIR, and arabinogalactans, rhamnogalacturonans, heteromannans, xyloglucans, and arabinan as predominant in WSP. Altogether, the study revealed a comparable cell wall structure among the analyzed hemp seed varieties. The high fiber content of whole hempseed-based ingredients presents significant potential for food manufacturers seeking to develop products with enhanced dietary fiber content, offering both functional and nutritional benefits for consumers.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Automated coupling of NanoIndentation and Quantitative Energy-Dispersive Spectroscopy (NI-QEDS): A comprehensive method to disclose the micro-chemo-mechanical properties of cement pastes

Engineering cement-based composites requires a comprehensive understanding of the microstructure features governing macroscopic properties. This work aims to foster the latest chemo-mechanical technique to disclose the micro-mechanical properties of intimately intermixed phases. Considering a typical Portland cement paste as a study case, we compared the so-far developed nanoindentation analysis methods with a new automatic method coupling Nano-Indentation and Quantitative Energy-Dispersive Spectroscopy (NI-QEDS). Besides evincing advantages and disadvantages of previous methods, the NI-QEDS analyses enabled distinguishing chemical phases having strongly overlapping mechanical properties. Results suggested the presence at the sub-micrometre scale of extra calcium, aluminum and sulfur into (or in the vicinity of) outer C–S–H. The quantitative chemistry allowed identifying the rare occurrence of nanoindentation volumes located on ''pure'' phases (e.g., inner C–S–H). Finally, NI-QEDS provided new knowledge on cement pastes' micro-chemo-visco-mechanical properties and showed to be a powerful tool for investigating even more heterogeneous systems.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Initial hydration process of calcium silicates in Portland cement: A comprehensive comparison from molecular dynamics simulations

As the main components of Portland cement, calcium silicates show substantial differences in their hydration reactivity which have not been fully explained. A comprehensive comparison of the initial hydration process of calcium silicates, namely dicalcium silicate (C{sub 2}S) and tricalcium silicate (C{sub 3}S), was conducted using molecular dynamics simulations. The initial hydration process was divided into three stages using cut-off times of 0.001 ns and 3 ns. The hydration of M{sub 3}-C{sub 3}S (010) was more evident than that of β-C{sub 2}S (100), supported by the hydroxylation degree, radial distribution function, atomic density profile, etc. The coordination number of the surface Ca atoms might be the underlying reason for such a difference. Interactions between cement surfaces and water molecules were mainly characterised by solid OH bonding and Ca-water O bonding. Dissolution of Ca atoms was observed, although quite scarce, while no dissolution of Si atoms was observed.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A comprehensive study of Interatomic Coulombic Decay in argon dimers: Extracting R-dependent absolute decay rates from the experiment

In this paper we present a comprehensive and detailed study of Interatomic Coulombic Decay (ICD) occurring after irradiating argon dimers with XUV-synchrotron radiation. A manifold of different decay channels is observed and the corresponding initial and final states are assigned. Additionally, the effect of nuclear dynamics on the ICD electron spectrum is examined for one specific decay channel. The internuclear distance-dependent width Γ(R) of the decay is obtained from the measured kinetic energy release distribution of the ions employing a classical nuclear dynamics model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Correlation of rocket propulsion fuel properties with chemical composition using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry followed by partial least squares regression analysis

There is an increased need to more fully assess and control the composition of kerosene based rocket propulsion fuels, namely RP-1 and RP-2. In particular, it is crucial to be able to make better quantitative connections between the following three attributes: (a) fuel performance, (b) fuel properties (flash point, density, kinematic viscosity, net heat of combustion, hydrogen content, etc) and (c) the chemical composition of a given fuel (i.e., specific chemical compounds and compound classes present as a result of feedstock blending and processing). Indeed, recent efforts in predicting fuel performance through modeling put greater emphasis on detailed and accurate fuel properties and fuel compositional information. In this regard, advanced distillation curve (ADC) metrology provides improved data relative to classical boiling point and volatility curve techniques. Using ADC metrology, data obtained from RP-1 and RP-2 fuels provides compositional variation information that is directly relevant to predictive modeling of fuel performance. Often, in such studies, one-dimensional gas chromatography (GC) combined with mass spectrometry (MS) is typically employed to provide chemical composition information. Building on approaches using GC-MS, but to glean substantially more chemical composition information from these complex fuels, we have recently studied the use of comprehensive two dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC - TOFMS) to provide chemical composition data that is significantly richer than that provided by GC-MS methods. In this report, by applying multivariate data analysis techniques, referred to as chemometrics, we are able to readily model (correlate) the chemical compositional information from RP-1 and RP-2 fuels provided using GC × GC - TOFMS, to the fuel property information such as that provided by the ADC method and other specification properties. We anticipate that this new chemical analysis strategy will have broad implications for the development of high fidelity composition-property models, leading to an optimized approach to fuel formulation and specification for advanced engine cycles.

fuel↗