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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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At least 19 records

Spatially Resolved Performance Analysis for Perovskite Solar Cells

This review explores the current state of the art in spatially resolved characterization of mixed-halide perovskite solar cells. As the size of perovskite cells and modules continues to grow, quantification of the spatial distribution of key cell parameters will become increasingly valuable in predicting ultimate cell-level performance and tracking process homogeneity. Here, both high resolution microscopic approaches using scanning techniques and camera-based methods for full-area cell and/or module analysis are discussed. The value of this local data in predicting performance losses at the cell level is particularly emphasized. Measurable physical parameters sensitive to losses of voltage, current, fill factor, and efficiency are discussed together with selected experimental results. It is demonstrated that a combination of spatially resolved cell parameter mapping/imaging can be used to quantitatively discriminate various loss contributions at high resolution. The impact and control of inhomogeneities become particularly important when upscaling from small devices to large formats compatible with industrial mass production.

14 SOLAR ENERGY↗

Rich methane oxidation on Pt/Pd/Al 2 O 3 : Steady state performance, multiplicity features, and spatial patterns

Performance features are reported for the catalytic sub-stoichiometric (rich) oxidation of methane on a Pt + Pd/ Al 2 O 3 washcoated monolith over a range of feed temperatures and O 2 /CH 4 for both dry and wet feeds. Near isothermal steady state multiplicity and co-existing states with different methane conversions are presented. The methane conversion vs. O 2 feed concentration consists of a higher conversion regime at lower concentrations and a lower conversion, inhibited regime at higher concentration. Here, the conversion maximum is accompanied by an overlap of the two regimes in the form of a clockwise hysteresis loop. Spatial concentration profiles for the dry feed reveal an upstream oxidation zone and downstream stream reforming zone. Measurements extending beyond the catalyst imply the co-existence of active and inhibited states. Addition of water promotes oxidation and steam reforming while the multiplicity and nonuniform states persist. Underlying mechanistic aspects responsible for the inhibition, rate multiplicity and co-existing states are discussed.

03 NATURAL GAS↗

Spatially resolved performance and degradation in a perfluorinated anion exchange membrane fuel cell

Anion exchange membrane fuel cells may enable future operation with non-precious metal-based catalysts. These systems have a delicate sensitivity to operating conditions such as humidification levels and the presence of CO2 in the air oxidant stream. We present spatially resolved in-situ performance results that shed light on phenomena that are unique to anion exchange membrane fuel cells. For cell construction, a highly conductive perfluorinated anion exchange polymer was used as the membrane and the material in powder form as the ionomer. Experiments were conducted to investigate the effects of humidification, fuel/oxidant concentration, and carbonation effects on the performance and its distribution in the cell. The results indicated that (i) dry conditions at the cathode have a stronger effect than at the anode on overall cell performance, (ii) performance significantly suffered when humidification was below 90%, (iii) fuel and oxidant dilution effects lead mass-transport losses and were stronger than flow rate effects, (iv) CO2 in the cathode feed stream creates an equilibration disparity between the inlet and outlet sections and CO2 purging is affected by flooding conditions, and (v) after >500 h of operation, performance deteriorates predominantly at the inlet.

2+1D fuel cell model↗

Impact of electrode thick spot irregularities on polymer electrolyte membrane fuel cell initial performance

Polymer electrolyte membrane fuel cells have great potential for power generation in many applications, but to implement them on a larger scale, understanding of quality requirements, tolerances, and controls during manufacturing must improve. As part of this broad challenge, irregularities resulting from the membrane electrode assembly production process must be studied to determine if they impact the performance of the cell. One potential irregularity is a locally increased thickness of the coated or deposited electrode. In order to understand and provide insight into the impact of such irregularities, we intentionally created thick spots in the center of cathode electrodes. The thick spots fabricated by two different approaches were carefully characterized by optical microscopy, X-ray fluorescence spectroscopy and scanning electron microscopy (SEM). We found that the impact of the thick spots on the electrochemically active catalyst area and mass activity was minimal. However, specific electrode thick spot irregularities significantly impacted the mass transport properties of the cells. Based on SEM analysis, the likely cause of the performance drop is morphological changes associated with the creation of the thick spot irregularity. Spatial performance results obtained with a segmented cell system further indicated that the area of the performance impact exceeded that of the intentionally created thick spot.

25 ENERGY STORAGE↗

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Autonomous GI↗

Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning

In powder bed fusion additive manufacturing, machines are often equipped with in-situ sensors to monitor the build environment as well as machine actuators and subsystems. The data from these sensors offer rich information about the consistency of the fabrication process within a build and across builds. This information may be used for process monitoring and defect detection; however, little has been done to leverage this data from the machines for more than just coarse-grained process monitoring. In this work we demonstrate how these inherently temporal data may be mapped spatially by leveraging scan path information. We then train a XGBoost machine learning model to predict localized defects—specifically soot–using only the mapped process data of builds from a laser powder bed fusion process as input features. The XGBoost model offers a feature importance metric that will help to elucidate possible relationships between the process data and observed defects. Finally, we analyze the model performance spatially and rationalize areas of greater and lesser performance.

3D printing↗

A Coupled Deep Learning Model for Estimating Surface NO 2 Levels from Remote Sensing Data: 15-Year Study Over the Contiguous United States

This study proposes a novel two-step deep learning (DL) model for estimating surface NO 2 concentrations using satellite data over the contiguous United States (CONUS) from 2005 to 2019. The first phase of the model uses partial convolutional neural network (PCNN), an advanced DL model that accurately imputes gaps between surface NO 2 stations and creates 5,478 daily-mean NO 2 grids (PCNN-NO 2 ) of the 2005-2019 period over the study area. We then feed the PCNN-NO 2 , along with other predictor variables, into a deep neural network (DNN) to estimate surface NO 2 levels, achieving exceptional performance with a correlation coefficient of 0.975 to 0.978, a mean absolute bias of 0.99 ppb to 1.38 ppb, and a root mean square error of 1.47 ppb to 1.97 ppb. Spatial cross-validation results also indicate strong spatial performance of PCNN-DNN surface NO 2 estimates. In addition to its accurate estimates, the PCNN-DNN model consistently generates estimated NO 2 grids without any missing values, improving the quality of various applications such as emission reduction strategies and public health studies. Between 2005 and 2019, the 5,478 daily estimated NO 2 grids over the CONUS reveal significant reductions in NO 2 levels in fourteen major urban environments: Washington D.C. (-43%), New York (-45%), Los Angeles (-38%), Chicago (-25%), Boston (-43%), Houston (-34%), Dallas (-40%), Philadelphia (-41%), Phoenix (-38%), Detroit (-20%), Denver (-23%), Atlanta (-0.7%), Cincinnati (-38%), and Pittsburgh (-56%). Furthermore, the study shows that the denser urban regions that in-situ stations are installed in, the higher the difference between in-situ observations and regional-mean NO 2 levels.

54 ENVIRONMENTAL SCIENCES↗

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution

Laser ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the ‘LAESI microscope’ source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. In this work, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high mass resolution and high mass accuracy metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗

Preserved and variable spatial‐chemical changes of lipids across tomato leaves in response to central vein wounding reveals potential origin of linolenic acid in signal transduction cascade

Abstract Membrane lipids serve as substrates for the generation of numerous signaling lipids when plants are exposed to environmental stresses, and jasmonic acid, an oxidized product of 18‐carbon unsaturated fatty acids (e.g., linolenic acid), has been recognized as the essential signal in wound‐induced gene expression. Yet, the contribution of individual membrane lipids in linolenic acid generation is ill‐defined. In this work, we performed spatial lipidomic experiments to track lipid changes that occur locally at the sight of leaf injury to better understand the potential origin of linolenic and linoleic acids from individual membrane lipids. The central veins of tomato leaflets were crushed using surgical forceps, leaves were cryosectioned and analyzed by two orthogonal matrix‐assisted laser desorption/ionization mass spectrometry imaging platforms for insight into lipid spatial distribution. Significant changes in lipid composition are only observed 30 min after wounding, while after 60 min lipidome homeostasis has been re‐established. Phosphatidylcholines exhibit a variable pattern of spatial behavior in individual plants. Among lysolipids, lysophosphatidylcholines strongly co‐localize with the injured zone of wounded leaflets, while, for example, lysophosphatidylglycerol (LPG) (16:1) accumulated preferentially toward the apex in the injured zone of wounded leaflets. In contrast, two other LPGs (LPG [18:3] and LPG [18:2]) are depleted in the injured zone. Our high‐resolution co‐localization imaging analyses suggest that linolenic acids are predominantly released from PCs with 16_18 fatty acid composition along the entire leaf, while it seems that in the apex zone PG (16:1_18:3) significantly contributes to the linolenic acid pool. These results also indicate distinct localization and/or substrate preferences of phospholipase isoforms in leaf tissue.

59 BASIC BIOLOGICAL SCIENCES↗

Fully Integrated Ultra-thin Intraoperative Micro-imager for Cancer Detection Using Upconverting Nanoparticles

Abstract Purpose Intraoperative detection and removal of microscopic residual disease (MRD) remain critical to the outcome of cancer surgeries. Today’s minimally invasive surgical procedures require miniaturization and surgical integration of highly sensitive imagers to seamlessly integrate into the modern clinical workflow. However, current intraoperative imagers remain cumbersome and still heavily dependent on large lenses and rigid filters, precluding further miniaturization and integration into surgical tools. Procedures We have successfully engineered a chip-scale intraoperative micro-imager array—without optical filters or lenses—integrated with lanthanide-based alloyed upconverting nanoparticles (aUCNPs) to achieve tissue imaging using a single micro-chip. This imaging platform is able to leverage the unique optical properties of aUCNPs (long luminescent lifetime, high-efficiency upconversion, no photobleaching) by utilizing a time-resolved imaging method to acquire images using a 36-by-80-pixel, 2.3 mm $$\times$$ × 4.8 mm silicon-based electronic imager micro-chip, that is, less than 100-µm thin. Each pixel incorporates a novel architecture enabling automated background measurement and cancellation. We have validated the performance, spatial resolution, and the background cancellation scheme of the imaging platform, using resolution test targets and mouse prostate tumor sample intratumorally injected with aUCNPs. To demonstrate the ability to image MRD, or tumor margins, we evaluated the imaging platform in visualizing a single-cell thin section of the injected prostate tumor sample. Results Tested on USAF resolution targets, the imager is able to achieve a resolution of 71 µm. We have also demonstrated successful background cancellation, achieving a signal-to-background ratio of 8 when performing ex vivo imaging on aUCNP-injected prostate tumor sample, improved from originally 0.4. The performance of the imaging platform on single-cell layer sections was also evaluated and the sensor achieved a signal-to-background ratio of 4.3 in resolving cell clusters with sizes as low as 200 cells. Conclusion The imaging system proposed here is a scalable chip-scale ultra-thin alternative for bulky conventional intraoperative imagers. Its novel pixel architecture and background correction scheme enable visualization of microscopic-scale residual disease while remaining completely free of lenses and filters, achieving an ultra-miniaturized form factor—critical for intraoperative settings.

59 BASIC BIOLOGICAL SCIENCES↗

An efficient second-order adaptive procedure for inserting CAD geometries into hexahedral meshes using volume fractions

Here, this paper is concerned with inserting three-dimensional computer-aided design (CAD) geometries into meshes composed of hexahedral elements using a volume fraction representation. An adaptive procedure for doing so is presented. The procedure consists of two steps. The first step performs spatial acceleration using a k-d tree. The second step involves subdividing individual hexahedra in an adaptive mesh refinement (AMR)-like fashion and approximating the CAD geometry linearly (as a plane) at the finest subdivision. The procedure requires only two geometric queries from a CAD kernel: determining whether or not a queried spatial coordinate is inside or outside the CAD geometry and determining the closest point on the CAD geometry’s surface from a given spatial coordinate. We prove that the procedure is second-order accurate for sufficiently smooth geometries and sufficiently refined background meshes. We demonstrate the expected order of accuracy is achieved with several verification tests and illustrate the procedure’s effectiveness for several exemplar CAD geometries.

Adaptive↗

Spin-Valley Locking in 2 H -TaS 2 and Its Co-Intercalated Counterpart: Roles of Surface Domains and Co Intercalation

Tuning and probing spin-valley coupling is key to understanding correlated ground states in 2H-TaS 2 . Its magnetically intercalated analogue, Co 1/3 TaS 2 , introduces additional degrees of freedom, including modified interlayer coupling and magnetism, to modulate spin-valley physics. Surface-sensitive probes like ARPES are essential for accessing surface spin texture, yet previous studies on 2H-TMDs have reported conflicting results regarding spin-polarized bands, leaving open whether these discrepancies are intrinsic or extrinsic. Here, in this study, we performed spatially resolved spin-ARPES measurements on 2H-TaS 2 and Co 1/3 TaS 2 . Our results reveal robust spin-valley locking on both compounds. Importantly, Co intercalation enhances interlayer hybridization and introduces magnetism while preserving the TaS 2 -derived spin texture. We further observe a spatial reversal of the out-of-plane spin polarization, which we attribute to different surface domains. This effect complicates quantifying spin textures and may underlie prior inconsistent observations. Our findings provide microscopic insight into how interlayer interactions and surface domains together govern spin-valley phenomena in layered TMDs.

Spin-resolved angle-resolved photoemission spectro↗

Time‐And‐Space Averaging Applied to Intermittent Multiphase Flow Experiments

Abstract Various researchers have studied fluctuations in pore‐scale phase occupancy during multiphase flow in porous media using synchrotron‐based X‐ray microcomputed tomography (micro‐CT). However, the impact of these fluctuations on the concept of a representative volume is not yet fully understood. In this study, we performed spatial and temporal averaging of multiphase flow experiments visualized with synchrotron‐based micro‐CT, focusing on oil saturation as the key parameter to determine a representative time‐and‐space average. Our findings revealed that a saturation value representative of both time and space was achieved during fractional flow experiments in drainage mode with fractional flows of 0.8, 0.5, and 0.3. Furthermore, we computed a range of relative permeabilities on the basis of whether momentaneous saturation or time‐and‐space averaged saturation was utilized for direct simulation. Our results highlighted the importance of time‐and‐space averaging in determining a representative relative permeability and indicated that the temporal and spatial scales covered in a typical micro‐CT flow experiment were sufficient to obtain a representative saturation value for sandstone rock under intermittent flow conditions.

Environmental Sciences & Ecology↗

Efficiency-optimized relativistic plasma harmonics for extreme fields

Bright harmonic radiation from relativistically oscillating laser plasmas offers a direct route for generating extreme electromagnetic fields. Theory predicts that under optimized conditions, the plasma medium can support strong spatiotemporal compression of laser energy in a coherent harmonic focus (CHF), delivering intensity boosts many orders of magnitude greater than the incident driving laser pulse. Although diffraction-limited performance (spatial compression) and attosecond phase locking (temporal compression) have been demonstrated experimentally, efficient coupling of relativistically intense laser pulse energy into the emitted harmonic cone has not been realized so far. Here we demonstrate that this highly nonlinear interaction can be tailored to deliver the maximum conversion efficiencies predicted from simulations. By fine-tuning the temporal profile of the driving laser on sub-picosecond (<10 −12 s) timescales, energies >9 mJ between the 12th and 47th harmonics are observed. These results are in agreement with the theoretically expected efficiency dependence on harmonic order, verifying that optimal conditions have been achieved in the generation process. This is the important final element required to achieve the expected intensity boosts from a CHF in experiments. Although obtaining spatiotemporal compression and optimal efficiency simultaneously remains challenging, the path to realizing extreme optical field strengths approaching the critical field of quantum electrodynamics (the Schwinger limit at >10 16 V cm −1 or >10 29 W cm −2 ) is now open, permitting all-optical studies of the quantum vacuum and new frontiers for intense attosecond science.

High-harmonic generation↗

Mapping brucellosis risk in Kenya and its implications for control strategies in sub-Saharan Africa

In Sub-Saharan Africa (SSA), effective brucellosis control is limited, in part, by the lack of long-term commitments by governments to control the disease and the absence of reliable national human and livestock population-based data to inform policies. Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. We randomly generated 268 geolocations and distributed them across Kenya, proportionate to the area of each of the five agroecological zones and the associated cattle population. Cattle herds closest to each selected geolocation were identified for sampling. Up to 25 cattle were sampled per geolocation and a semi-structured questionnaire was administered to their owners. We tested 6,593 cattle samples for Brucella immunoglobulin G (IgG) antibodies using an Enzyme-linked immunosorbent assay (ELISA). We assessed potential risk factors and performed spatial analyses and prevalence mapping using approximate Bayesian inference implemented via the integrated nested Laplace approximation (INLA) method. The national Brucella spp. prevalence was 6.8% (95% CI: 6.2–7.4%). Exposure levels varied significantly between agro-ecological zones, with a high of 8.5% in the very arid zone with the lowest agricultural potential relative to a low of 0.0% in the agro-alpine zone with the highest agricultural potential. Additionally, seroprevalence increased with herd size, and the odds of seropositivity were significantly higher for females and adult animals than for males or calves. Similarly, animals with a history of abortion, or with multiple reproductive syndromes had higher seropositivity than those without. At the herd level, the risk of Brucella spp. transmission was higher in larger herds, and herds with a history of reproductive problems such as abortion, giving birth to weak calves, or having swollen testes. Geographic localities with high Brucella seroprevalence occurred in northern, eastern, and southern regions of Kenya all primarily characterized by semi-arid or arid agro-ecological zones dominated by livestock pastoralism interspersed with vast areas with mixed livestock-wildlife systems. The large spatial extent of our survey provides compelling evidence for the widespread geographical distribution of brucellosis risk across Kenya in a manner easily understandable for policymakers. Our findings can provide a basis for risk-stratified pilot studies aiming to investigate the cost-effectiveness and efficacy of singular and combined preventive intervention strategies that seek to inform Kenya’s Brucellosis Control Policy.

60 APPLIED LIFE SCIENCES↗

Influence of ambient gas on self-reversal in Li transitions relevant to isotopic analysis

Laser induced breakdown spectroscopy is a promising, rapid analysis method for the detection and quantification of Li and its isotopes needed in geochemical, nuclear, and energy storage applications. However, spectral broadening in laser produced plasmas, presence of fine and hyperfine structures, and self-reversal effects make Li isotopic analysis via laser induced breakdown spectroscopy challenging. The present study explores the influence of Ar, N 2 , and He ambient gases over the pressure range of 0.05 - 100 Torr on line broadening and self-reversal of the Li I transition with the greatest isotopic shift in the VIS spectral region (i.e., ≈670.8 nm, ≈15.8 pm isotopic shift). We perform spatially and temporally resolved optical emission spectroscopy of plasmas produced via laser ablation of LiAlO 2 substrates. Our results show that the self-reversal and linewidth is reduced at lower pressures for all gases, and using optimized plasma conditions with chemometric methods, the 6 Li/ 7 Li isotopic ratios can be predicted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Opportunities for Recovering Resources from Municipal Wastewater

Municipal wastewater contains valuable resources including water, energy, and nutrients that often enter and leave wastewater treatment plants (WWTPs) without being captured. Currently, plants are increasingly seeking to recover resources and reuse them in a sustainable way. Therefore, the purpose of this project was to assess the potential for recovery and reuse of water and products from municipal wastewater treatment plants across the United States and to examine how this potential varies by region. To accomplish this, three main tasks were set: first, to characterize wastewater treatment plants; second, to characterize technologies and pathways used to recover energy, nutrients, and water from treatment plants; third, to assess the demand for reclaimed resources and products at a regional level by performing spatial analysis. These three tasks were then synthesized to present key findings in this report and a geospatial dataset with the hope of guiding the increased use of resource recovery technologies in the U.S.

54 ENVIRONMENTAL SCIENCES↗

Experimental Measurements of Soot and Soot Precursors of Sustainable Aviation Fuels

Sustainable Aviation Fuels (SAFs) are promising for decarbonizing the challenging-to-electrify aerospace sector and reducing yearly greenhouse gas emissions by thousands of tons. Developing predictive detailed chemical kinetic models for SAF (and traditional) fuel mixtures necessitates a robust experimental database to elucidate the intricate pyrolysis and oxidation chemistry of SAF fuel blend components. Two critical components of SAF surrogate mixtures are iso-dodecane isomers and trans-decalin. This report characterizes the structure of three slightly sooting, laminar, non-premixed, nitrogen-diluted Planar Mixing Layer Flames (PMLFs) fueled by either pure ethylene, ethylene doped with 1500ppm of either 2,2,4,6,6-pentamethyl-heptane or trans-decalin. The flames have the same stoichiometric mixture fraction and total mole fraction of fuels in the fuel stream (X F,F = X C2H4,F + X Dopant,F = 0.26), resulting in approximately the same maximum temperature (T max ≈ 1800 K) to highlight the effect of doping on soot and its gaseous precursors. The PMLF is unconfined and established between adjacent planar jets of the fuel and oxidizer streams surrounded by annular shielding nitrogen. The flow is stabilized by exhausting the hot buoyant flame products through a slot in a downstream plate onto which the cold flow impinges. Importantly, any horizontal cross-section of the PMLF has a self-similar thermochemical structure of a reactive boundary layer that grows at increasing Height Above the Burner (HAB). Therefore, the horizontal cross-sections of a PMLF can be modeled as a One-Dimensional Counterflow Flame (1D-CF) with very low strain rates which are unachievable in traditional CFs and yield a structure that is several millimeters thick. In brief, the PMLF is ideal for performing spatially resolved measurements with minimal effects of the sampling-induced perturbations, to develop and validate detailed chemical kinetic models on time scales of a few tens of milliseconds that are relevant in aviation applications. The horizontal profiles of C0-C18 gaseous species at HAB = 50 mm and soot volume fraction at 25 and 50 mm are measured using capillary sampling followed by GC-MS analyses and Laser Induced Emission Spectroscopy (LIES), respectively. Additionally, the Elastic Laser Light Scattering (E-LLS) coefficient is measured at HAB = 50 mm and 25 mm to determine the strain rates of the 1D-CFs equivalent to the characterized PMLF horizontal cross sections and the profile of the E-LLS equivalent diameter of soot. The comparison of the results in the base PMLF fueled only by ethylene with those in either doped PMLF in which 1500 ppm of ethylene are replaced with 2,2,4,6,6-pentamethyl-heptane or trans-decalin, reveals that the doping increases the mole fraction of several Polycyclic Aromatic Hydrocarbons (PAHs) at both HABs by a factor of approximately 2.5, and the soot volume fraction at both HABs by factors of ~1.5 for 2,2,4,6,6-pentamethyl-heptane and ~1.25 for trans-decalin doping, respectively. Conversely, doping causes a near doubling of the soot equivalent diameter only at HAB = 50 mm, without significant effects at 25 mm. The experimental results partially validate the tested state-of-the-art detailed chemical kinetic model and also point toward the further improvement of its predictive capabilities.

10 SYNTHETIC FUELS↗