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DOE OSTI2025

Tropical High Cloud Feedback Relationships to Climate Sensitivity

Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Furthermore, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks.

atmosphere↗

DOE OSTI2025

Surface Trap Dynamics and Gamma‐Ray Detection Enhancement in Passivated FAPbBr 3 Perovskite Crystals

Perovskite‐based direct radiation detectors offer a compelling platform for room‐temperature gamma spectroscopy due to their high sensitivity, tunable optoelectronic properties, and compatibility with solution processing. While prior studies on formamidinium lead tribromide (FAPbBr 3 ) have shown that surface passivation mitigates deep trap state impact on the charge collection efficiency (CCE), the influence of surface‐based shallow traps on time‐resolved detector response remains largely unexplored. In this article, a digital signal processing (DSP) method is applied to analyze waveform rising edge dynamics in FAPbBr 3 single‐crystal detectors, identifying prompt and delayed charge collection components. Using the second derivative of the collected charge signal, the onset of shallow trap reemission is isolated, occurring 1.1 µs after carrier generation. Surface passivation suppressed deep trap states, shifting carrier occupancy toward shallower traps and extending the temporal window of delayed charge collection. This delayed contribution correlates with measurable changes in the temporal and amplitude distributions of detector events. By leveraging time‐domain filtering informed by these dynamics, a selective enhancement in signal quality and gamma peak‐to‐Compton ratio (PCR) is achieved, while preserving over 90% of photoelectric events. An improvement in the PCR to 1.80, from the original 1.09, is enabled by focusing on high collection efficiency events corresponding to reemitted carriers in the 1.1 to 3 µs range after the generation event. These results demonstrate a pathway for leveraging shallow trap dynamics to enhance spectral fidelity in time‐resolved perovskite detectors.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO 2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and emissions reductions of 3–100 %, with strategic energy management achieving 3–5 % and renewable electricity paired with electrified heating achieving up to 100 %. Text mining revealed that energy, hardware, and process technologies account for 91 % of literature coverage. Water, building envelope, and CO 2 utilization remain underexplored, indicating priorities for future research. This integrative approach to technology assessment supports growers, developers, and policymakers in aligning CEA system design with local conditions, improving resource efficiency and addressing gaps in cross-domain technology coverage.

Controlled environment agriculture↗

DOE OSTI2026

Low-cost calculation and analysis of 2D IR spectra of model diiron trinitrosyl complexes in the NO stretch region with vibrational perturbation theory

Two-dimensional infrared spectroscopy offers unique capabilities for probing vibrational coupling in complex metal–ligand systems. In this paper, we combine two-dimensional infrared spectroscopy with vibrational perturbation theory to investigate vibrational coupling in a diiron trinitrosyl complex across three stable redox states. Although these systems are challenging for electronic structure methods, we demonstrate that key features of experimental 2D IR spectra can be accurately reproduced using reduced-dimensional anharmonic calculations with a small harmonic frequency scaling. Analysis reveals that N–O stretching modes maintain high locality across all redox states, with coupling patterns that directly reflect variations in Fe–N bond strength. Using curvilinear coordinate analysis, we demonstrate these differences result from systematic changes in cubic anharmonic force constants rather than mode delocalization. Our results establish N–O stretches as sensitive probes of metal–ligand bonding strength, expanding the toolkit for studying biologically relevant nitrosyl complexes.

Moran, Hayden A. [Texas A&M University, College St↗

DOE OSTI2024

Performance assessment of near-fault buildings subjected to physics-based simulated earthquake ground motions with fling step

The effects of the co-seismic static offset (known as fling step) and associated velocity pulses on civil structures have been difficult to study because the static offset is typically removed during the processing of earthquake ground motion records. Simulated ground motions contain fling features and require no processing; therefore, they create new opportunities for representing fling features in seismic hazard analysis and assessing their influence on the seismic demands on near-fault structures. We use physics-based fault rupture simulations to study the characteristics of ground motions with fling step and the sensitivity of the near-fault structural demands to strong fling features. We uncover that simulated ground motions with a large fling step tend to have higher spectral intensity than those without a fling step at the same rupture distance, especially at periods longer than 2 s. As a result, the structural demands on flexible buildings tend to be the most sensitive to the fling features. Statistical analysis suggests that the ground motion spectral shape (represented by spectral accelerations at multiple periods) is—in most cases—a sufficient predictor of the structural demands on near-fault low-rise and mid-rise buildings at locations that are susceptible to strong fling effects. Finally, ground motion record selection experiments reveal that representing the spectral shape features at periods that are most relevant to a given structure may be an effective strategy to reduce the bias in the estimated demands on near-fault long-period structures when the available database of records is considered deficient in fling features.

Fling step↗

DOE OSTI2026

Regression Convolutional Neural Network for Energy Estimation in NOvA

Regression Convolutional Neural Network for Energy Estimation in NOvA" Abstract: "NOvA (NuMI Off-Axis $\nu_e$ Appearance) is a long baseline neutrino experiment designed to measure neutrino oscillations over a distance of 810 km. NOvA employs a near and far detector to observe $\nu_\mu$ disappearance and $\nu_e$ appearance of neutrinos produced by the NuMI beam at Fermilab. Energy reconstruction is critical for precise measurements of neutrino oscillation parameters and cross sections, which are functions of neutrino energy. Energy estimation remains difficult due to the complexity of detector response and final state particle kinematics. We present a regression-based convolutional neural network (CNN) method that reconstructs neutrino and lepton energies based on raw pixel inputs for NOvA. The trained model is able to reconstruct event energy for different interaction modes and complex final states containing leptons and hadrons. Studies of regression CNN networks show improved energy resolution and reduced sensitivity to calibration scale uncertainties relative to traditional kinematics-based energy reconstruction techniques. The results demonstrate the potential of the regression CNN method for neutrino physics analyses by improving on standard kinematics-based reconstruction.

Zhao, Larry [UC, Irvine (main)]↗

DOE OSTI2026

New opportunities for rare charm from $Z\rightarrow c\bar{c}$ decays

We analyze the potential of rare charm decays as probes of new physics at a high-luminosity flavor facility operating at the Z pole, such as the FCC-ee or CEPC. In particular, we identify clean null-test observables in $D^0 → π^+ π^- v\bar{v}$ and in polarized $Λ^+_c → p ℓ^+ ℓ^-$ decays with $ℓ = e, μ$. Complementarity with the LHC and HL-LHC flavor programs arises from the characteristic features of a Tera-Z environment: the capability to study missing-energy modes and charm production with significant polarization. We improve the theoretical description of $D^0 → π^+ π^- v\bar{v}$ decays and work out the phenomenology of polarization-induced null-test observables in $Λ^+_c → p ℓ^+ ℓ^-$ decays. In regions of dilepton mass near the φ resonance, polarization asymmetries can reach $O$(5%) for muons and $O$(14%) for electrons times the $Λ^+_c$ polarization. We also point out synergies between the dineutrino and the dilepton modes using the SMEFT framework of heavy new physics. Using the IDEA detector concept at FCC-ee, we find in simulation studies that dineutrino branching fractions as low as ~ 2 x 10 -7 can be probed, which reaches well into the parameter space of new physics, and also allows for discrimination of lepton flavor structures. Furthermore, the measurement of asymmetries in $Λ^+_c → p ℓ^+ ℓ^-$ at $O$(1%) will be possible. Similar sensitivities are expected for dielectron final states, although robust predictions will require further dedicated studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

58 GEOSCIENCES↗

DOE OSTI2026

Enhanced sensitivity to trace 238 U impurity of sapphire via coincidence neutron activation analysis

Sapphire has mechanical and electrical properties that are advantageous for the construction of internal components of radiation detectors such as time projection chambers and bolometers. However, it has proved difficult to assess its 232 Th and 238 U content down to the picogram per gram level. Here, this work reports an experimental verification of a computational study that demonstrates 𝛾⁢𝛾 coincidence counting, coupled with neutron activation analysis (NAA), can reach ppt sensitivities. Combining results from 𝛾⁢𝛾 coincidence counting with those of earlier single-𝛾 counting based NAA shows that a sample of Saint Gobain sapphire has 232 Th and 238 U concentrations of <0.26 ppt and <2.3 ppt, respectively; the best constraints on the radiopurity of sapphire.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

How do drought and heat affect the response of soybean seed yield to elevated O 3 ? An analysis of 15 seasons of free–air O 3 concentration enrichment studies

The coincidence of rising ozone concentrations ([O 3 ]), increasing global temperatures, and drought episodes is expected to become more intense and frequent in the future. A better understanding of the responses of crop yield to elevated [O 3 ] under different levels of drought and high temperature stress is, therefore, critical for projecting future food production potential. Using a 15-year open-air field experiment in central Illinois, we assessed the impacts of elevated [O 3 ] coupled with variation in growing season temperature and water availability on soybean seed yield. Thirteen soybean cultivars were exposed to a wide range of season-long elevated [O 3 ] in the field using free-air O 3 concentration enrichment. Elevated [O3] treatments reduced soybean seed yield from as little as 5.3% in 2005 to 35.2% in 2010. Although cultivars differed in yield response to elevated [O 3 ] (R), ranging from 17.5% to –76.4%, there was a significant negative correlation between R and O 3 dosage. Soybean cultivars showed greater seed yield losses to elevated [O 3 ] when grown at drier or hotter conditions compared to wetter or cooler years, because the hotter and drier conditions were associated with greater O 3 treatment. However, year-to-year variation in weather conditions did not influence the sensitivity of soybean seed yield to a given increase in [O 3 ]. Collectively, this study quantitatively demonstrates that, although drought conditions or warmer temperatures led to greater O 3 treatment concentrations and O 3 -induced seed yield reduction, drought and temperature stress did not alter soybean's sensitivity to O 3 . Our results have important implications for modeling the effects of rising O 3 pollution on crops and suggest that altering irrigation practices to mitigate O 3 stress may not be effective in reducing crop sensitivity to O 3 .

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

DOE OSTI2025

Optical imaging of flavor order in flat band graphene

Abstract Spin- and valley flavor polarization plays a central role in the many-body physics of flat band graphene, with Fermi surface reconstruction — often accompanied by quantized anomalous Hall and superconducting state — observed in a variety of experimental systems. Here we describe an optical technique that sensitively and selectively detects flavor textures via the exciton response of a proximal transition metal dichalcogenide layer. Through a systematic study of rhombohedral and rotationally faulted graphene bilayers and trilayers, we show that when the semiconducting dichalcogenide is in direct contact with the graphene, the exciton response is most sensitive to the large momentum rearrangement of the Fermi surface, providing information that is distinct from and complementary to electrical compressibility measurements. The wide-field imaging capability of optical probes allows us to obtain spatial maps of flavor order with high throughput, and with broad temperature and device compatibility. Our work helps pave the way for optical probing and imaging of flavor orders in flat band graphene systems.

Science & Technology - Other Topics↗

DOE OSTI2025

Mitigating humidity interference in chemiresistive hydrogen sensors through hydrophobic surface functionalization

Chemiresistive gas sensors based on semiconductor metal oxides, such as tin dioxide (SnO₂), are indispensable for detecting and monitoring toxic gases and pollutants, making them critical components in industrial and environmental applications. To enhance their performance, the metal oxides are loaded with noble metals such as palladium (Pd). However, ambient humidity poses a significant challenge to their performance. The presence of adsorbed water molecules on the oxide surface can considerably impair sensor sensitivity and overall performance. To address this issue, in this paper, we report on the application of an ultrathin, hydrophobic layer of hexamethyldisilazane to the surface of a Pd/SnO 2 sensor. This study investigates the influence of hydrophobic surface modifications on the metal oxide interface, focusing on their impact on sensor sensitivity and selectivity. The resulting sensor exhibits superior hydrogen sensing capabilities, operating effectively at low temperatures even in high humidity environments. Furthermore, the hydrophobic modification reduces the sensor’s susceptibility to interfering gases, thus enhancing its selectivity. The combined enhancements in moisture resistance and selectivity achieved through HMDS surface modification, along with the superior sensitivity of Pd/SnO₂ sensors, facilitate the development of gas sensors with enhanced humidity tolerance and broader applications.

Chemiresistive gas sensors↗

DOE OSTI2024

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 µL of human plasma in 15 min. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals who underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

An effective cosmological collider

Effective field theories (EFTs) of heavy particles coupled to the inflaton are rife with operator redundancies, frequently obscured by sensitivity to both boundary terms and field redefinitions. We initiate a systematic study of these redundancies by establishing a minimal operator basis for an archetypal example, the abelian gauge-Higgs-inflaton EFT. Working up to dimension 9, we show that certain low-dimensional operators are entirely redundant and identify new non-redundant operators with potentially interesting cosmological collider signals. Our methods generalize straightforwardly to other EFTs of heavy particles coupled to the inflaton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

A chemical kinetic analysis of knock propensity of methanol-to-gasoline fuel

Production of low carbon gasoline-like fuels such as methanol-to-gasoline (MTG) is a promising approach to achieve rapid greenhouse gas emission reduction of the transportation sector. Despite the fact that gasoline that meets the ASTM D4814 standard for automotive spark-ignition engine fuel can be readily produced from these processes, it is unclear how the composition of MTG may affect engine performance and emissions. Here, in this paper, a surrogate for an MTG is used to numerically study the effects of gasoline composition on knock propensity and on the sensitivity of knock to thermal and fuel stratification, to oxygen dilution and to nitric oxide from exhaust gas recirculation of residual gases. Simulations were performed in ANSYS CHEMKIN-PRO using a comprehensive chemical kinetic mechanism for gasoline surrogates, and results of the MTG surrogate were compared against those of a petroleum-based regular E10 gasoline, termed PACE-20. A premium-grade MTG fuel was also formulated by adding ethanol to the MTG surrogate, and results were compared against those of four premium-grade, gasoline-like fuels representative of future alternative gasoline formulations. Surrogates and mechanism were evaluated by comparison against experimental engine data, and the model showed high accuracy at stoichiometric conditions (mean absolute error of ignition timing equal to 1.46 crank angle degrees) but larger deviations at lean conditions (mean absolute error of ignition timing equal to 5.52 crank angle degrees). Despite the fact that the MTG surrogate has a RON 1.1 units higher than that of PACE-20, it may show higher knock propensity at medium temperature conditions due to a less intense NTC behavior. MTG autoignition was more temperature- and equivalence ratio-sensitive than that of PACE20, suggesting that MTG can benefit more from naturally-occurring thermal stratification or from induced fuel stratification of the end gas to mitigate knock intensity. The sensitivity of autoignition reactivity to oxygen dilution and to NO concentration was higher for MTG than for regular gasoline at medium loads, but the opposite trend was observed at high loads due to the effect of pressure on the low-temperature chemistry of regular gasoline. Approximately 14 % vol ethanol content was required to upgrade the octane rating of MTG from regular grade to premium grade. Adding 13.6 % vol ethanol made the fuel autoignition less sensitive to both oxygen dilution and NO content (ignition time varies approx. 17 % and 50 % less with oxygen dilution and NO addition, respectively, when adding ethanol at high engine loads).

02 PETROLEUM↗