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At least 973 records · Page 54

Optimization of Orifice Geometry for Cross-Flow Mixing in a Cylindrical Duct

Mixing of gaseous jets in a cross-flow has significant applications in engineering, one example of which is the dilution zone of a gas turbine combustor. Despite years of study, the design of the jet injection in combustors is largely based on practical experience. The emergence of NO(x) regulations for stationary gas turbines and the anticipation of aero-engine regulations requires an improved understanding of jet mixing as new combustor concepts are introduced. For example, the success of the staged combustor to reduce the emission of NO(x) is almost entirely dependent upon the rapid and complete dilution of the rich zone products within the mixing section. It is these mixing challenges to which the present study is directed. A series of experiments was undertaken to delineate the optimal mixer orifice geometry. A cross-flow to core-flow momentum-flux ratio of 40 and a mass flow ratio of 2.5 were selected as representative of a conventional design. An experimental test matrix was designed around three variables: the number of orifices, the orifice length-to- width ratio, and the orifice angle. A regression analysis was performed on the data to arrive at an interpolating equation that predicted the mixing performance of orifice geometry combinations within the range of the test matrix parameters. Results indicate that the best mixing orifice geometry tested involves eight orifices with a long-to-short side aspect ratio of 3.5 at a twenty-three degree inclination from the center-line of the mixing section.

Kroll, J. T.↗

Tropospheric Ozone during the TRACE-P Mission: Comparison between TOMS Satellite Retrievals and Aircraft Lidar Data, March 2001

Over the past several years, we have developed two new tropospheric ozone retrievals from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument that are of sufficient resolution to follow pollution episodes. The modified-residual technique uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMS-direct method ('TDOT' = TOMS Direct Ozone in the Troposphere) represents a new algorithm that uses TOMS radiances directly to extract tropospheric ozone in regions of constant stratospheric ozone. It is not geographically restricted, using meteorological regimes as the basis for classifying TOMS radiances and for selecting appropriate comparison data. TDOT is useful where tropospheric ozone displays high mixing ratios and variability characteristic of pollution. Some of these episodes were observed downwind of Asian biomass burning during the TRACE-P (Transport and Atmospheric Chemical Evolution-Pacific) field experiment in March 2001. This paper features comparisons among TDOT tropospheric ozone column depth, integrated uv-DIAL measurements made from NASA's DC-8, and ozonesonde data.

Frolov, A. D.↗

"One-Stop Shopping" for Ocean Remote-Sensing and Model Data

OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the simulation period, and the output variables and submit the model to run on a backend parallel computer. When the run is complete, the output will be added to the LAS server for

Li, P. Peggy↗

NASA Tech Briefs, July 2005

Thin-Film Resistance Heat-Flux Sensors Circuit Indicates that Voice-Recording Disks are Nearly Full Optical Sensing of Combustion Instabilities in Gas Turbines Topics include: Crane-Load Contact Sensor; Hexagonal and Pentagonal Fractal Multiband Antennas; Multifunctional Logic Gate Controlled by Temperature; Multifunctional Logic Gate Controlled by Supply Voltage; Power Divider for Waveforms Rich in Harmonics; SCB Quantum Computers Using iSWAP and 1-Qubit Rotations; CSAM Metrology Software Tool; Update on Rover Sequencing and Visualization Program; Selecting Data from a Star Catalog; Rotating Desk for Collaboration by Two Computer Programmers; Variable-Pressure Washer; Magnetically Attached Multifunction Maintenance Rover; Improvements in Fabrication of Sand/Binder Cores for Casting; Solid Freeform Fabrication of Composite-Material Objects; Efficient Computational Model of Hysteresis; Gauges for Highly Precise Metrology of a Compound Mirror; Improved Electrolytic Hydrogen Peroxide Generator; High-Power Fiber Lasers Using Photonic Band Gap Materials; Ontology-Driven Information Integration; Quantifying Traversability of Terrain for a Mobile Robot; More About Arc-Welding Process for Making Carbon Nanotubes; Controlling Laser Spot Size in Outer Space; or Software-Reconfigurable Processors for Spacecraft.

Source record↗

A Generic Nonlinear Aerodynamic Model for Aircraft

A generic model of the aerodynamic coefficients was developed using wind tunnel databases for eight different aircraft and multivariate orthogonal functions. For each database and each coefficient, models were determined using polynomials expanded about the state and control variables, and an othgonalization procedure. A predicted squared-error criterion was used to automatically select the model terms. Modeling terms picked in at least half of the analyses, which totalled 45 terms, were retained to form the generic nonlinear aerodynamic (GNA) model. Least squares was then used to estimate the model parameters and associated uncertainty that best fit the GNA model to each database. Nonlinear flight simulations were used to demonstrate that the GNA model produces accurate trim solutions, local behavior (modal frequencies and damping ratios), and global dynamic behavior (91% accurate state histories and 80% accurate aerodynamic coefficient histories) under large-amplitude excitation. This compact aerodynamics model can be used to decrease on-board memory storage requirements, quickly change conceptual aircraft models, provide smooth analytical functions for control and optimization applications, and facilitate real-time parametric system identification.

Grauer, Jared A.↗

A Machine-Learning Decision-Support Tool for Travel-Demand Modeling

Utility maximization(UM) models are the lifeblood of virtually all travel demand models (TDM) in practice. Be it the traditional travel demand models or more advanced activity-based models, utility maximization models are used extensively to model and predict myriad travel choices such as location choice, mode choice, route choice etc. More recently machine learning (ML) models are being applied in a variety of contexts to predict choice patterns (product suggestions on Amazon, restaurant suggestions on Yelp etc.,). In the TDM arena, there has been interest in incorporating ML models where they can enhance prediction accuracy. Though there have been sporadic efforts at comparing specific utility maximization models to machine learning models, there is a need for a standard comparison tool which can evaluate ML models against UM models for a given choice context. Addressing this need, we present a tool for applying an array of models including logit, nested logit, neural network, Naive Bayes and decision tree classifiers. The tool is specifically tailored to aid in the deciding the best model for a given choice context and can be used to choose an appropriate model family or to construct a model ensemble to improve upon current modeling standards in travel demand modeling. We test our proposed system on household vehicle count and work schedule targets from the 2017 National Household Travel Survey. Results demonstrate that for some variables, logit are not the most effective models, and the proposed system can aid in selecting a better model.

33 ADVANCED PROPULSION SYSTEMS↗

The brown dwarf population in the star-forming region NGC 2264

ABSTRACT The brown dwarf population in the canonical star-forming region NGC 2264 is so far poorly explored. We present a deep, multiwavelength, multiepoch survey of the star-forming cluster NGC 2264, aimed to identify young brown dwarf candidates in this region. Using criteria including optical/near-infrared (IR) colours, variability, Spitzer mid-IR colour excess, extinction, and Gaia parallax and proper motion (in order of relevance), we select 902 faint red sources with indicators of youth. Within this sample, we identify 429 brown dwarf candidates based on their IR colours. The brown dwarf candidates are estimated to span a mass range from 0.01 to 0.08 M⊙. We find rotation periods for 44 sources, 15 of which are brown dwarf candidates, ranging from 3.6 h to 6.5 d. A subset of 38 brown dwarf candidates show high-level irregular variability indicative of ongoing disc accretion, similar to the behaviour of young stars.

Pearson, Samuel↗

Investigation of Coincidence Counting for Improving Minimal Detectable Activity of 110m Ag in Single Particle Gamma Analysis

Post-irradiation examination (PIE) of fuel particles from the fourth Advanced Gas Reactor Fuel Development and Qualification (AGR) Program irradiation (AGR-5/6/7) is being performed at Oak Ridge National Laboratory (ORNL). Tristructural isotropic (TRISO)-coated particles and associated compacts for the AGR-5/6/7 experiment fabricated by BWX Technologies Nuclear Operations Group were formed into a graphite matrix compact and irradiated at the Advanced Test Reactor at Idaho National Laboratory. At ORNL, particles are deconsolidated from the graphite matrix compact and individually scanned for emitted gamma rays with the Irradiated Microsphere Gamma Analyzer (IMGA). The IMGA system comprises a single high purity germanium (HPGe) detector, an automated particle handling vacuum system, and an ORTEC DSPEC-50 digital spectrometer for gamma ray analysis. IMGA quantifies gamma ray-emitting fission product inventories of individual TRISO particles, and these inventories can be compared with the measured average inventories per particle and radionuclide inventories predicted by AGR-5/6/7 physics calculations to determine if a particle experienced radionuclide release. Details on IMGA data collection methods can be found in the literature. The TRISO particle’s SiC layer provides structural support, as well as a barrier for fission product release during irradiation or subsequent safety testing. A weakened or compromised SiC layer can be identified by the release of radionuclides, such as 137 Cs, which is detected by IMGA. However, select radionuclides, such as 90 Sr, 110 mAg, and 154 Eu have been shown to migrate through an intact SiC layer. Measurement of the radionuclide 110 mAg is significant as its release has been shown to be particularly sensitive to in-reactor conditions (e.g., temperature) with broad variable particle to-particle release behaviors observed within a single compact. As such, 110 mAg activity is often used for particle selection for comprehensive PIE as bounding 110 mAg retention particles are hypothesized to represent limits in particle behaviors within a compact. As TRISO particle fuel PIE activities continue over time, IMGA measurements of the 110 mAg inventory are eventually hindered because of its relatively short half-life (~250 days). As the fuel ages from its end of irradiation (EOI) date, the measurement uncertainty and minimum detectable activity (MDA) of 110m Ag increase because the detector background continuum begins to dominate. For particles from the second AGR irradiation experiment (AGR-2), the 110m Ag MDA was above 20% of the calculated average particle inventory after approximately five half-lives, and 110m Ag activity was no longer measurable with IMGA after approximately seven half-lives. Therefore, coincidence counting approaches have been explored to determine feasibility of leveraging new approaches to overcome limitations associated with increasing MDA over time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High-Resolution Tropical Channel Model Simulations of Tropical Cyclone Climatology and Intraseasonal-to-Interannual Variability

We tailored a tropical channel configuration of the Weather Research and Forecasting (WRF) Model to study tropical cyclone (TC) activity and associated climate variabilities. This tropical channel model (TCM) covers from 30°S to 50°N at 27-km horizontal resolution, with physics parameterizations carefully selected to achieve more realistic simulations of TCs and large-scale climate mean states. In this work we performed 15-member ensembles of retrospective simulations from 1982 to 2016 hurricane seasons. A thorough comparison with observations demonstrates that the TCM yields significant skills in simulating TC activity climatology and variabilities in each basin, as well as TC physical structures. The correlation of the ensemble averaged accumulated cyclone energy (ACE) with observations in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NAT) is 0.80, 0.64, and 0.61, respectively, but is insignificant in the north Indian Ocean (NIO). Moreover, the TCM-simulated modulations of El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) on the large-scale environment and TC genesis also agree well with observations. To examine the TCM’s potential for seasonal TC prediction, the model is used to forecast the 2017 and 2018 hurricane seasons, using bias-corrected sea surface temperatures (SSTs) from the CFSv2 seasonal prediction results. The TCM accurately predicts the hyperactive 2017 NAT hurricane season and near-normal WNP and ENP hurricane seasons when initialized in May. In addition, the TCM accurately predicts TC activity in the NAT and WNP during the 2018 season, but underpredicts ENP TC activity, in association with a poor ENSO forecast.

54 ENVIRONMENTAL SCIENCES↗

Synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions

Recent advances in metabolic engineering have enabled the production of chemicals via bio-conversion using microbes. However, downstream separation accounts for 60–80% of the total production cost in many cases. Previous work on microbial production of extracellular chemicals has been mainly restricted to microbiology, biochemistry, metabolomics, or techno-economic analysis for specific product examples such as succinic acid, xanthan gum, lycopene, etc. In these studies, microbial production and separation technologies were selected apriori without considering any competing alternatives. However, technology selection in downstream separation and purification processes can have a major impact on the overall costs, product recovery, and purity. To this end, we apply a superstructure optimization based framework that enables the identification of critical technologies and their associated parameters in the synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions. We divide extracellular chemicals into three categories based on their physical properties, such as water solubility, physical state, relative density, volatility, etc. We analyze three major extracellular product categories (insoluble light, insoluble heavy and soluble) in detail and provide suggestions for additional product categories through extension of our analysis framework. The proposed analysis and results provide significant insights for technology selection and enable streamlined decision making when faced with any microbial product that is released extracellularly. The parameter variability analysis for the product as well as the associated technologies and comparison with novel alternatives is a key feature which forms the basis for designing better bioseparation strategies that have potential for commercial scalability and can compete with traditional chemical production methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methods of making a component with variable magnetization and related components

A method of forming a component having a variation in saturation magnetization is presented. The method includes selectively diffusing nitrogen into a metallic component of a masked metallic component by exposing the masked metallic component to a nitrogen-rich atmosphere. The masked metallic component includes a patterned oxide layer formed on a surface of the metallic component, and the patterned oxide layer includes an oxide of a metal present in the metallic component. A related component is also presented.

36 MATERIALS SCIENCE↗

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed back-cone distance of the spiral bevel gear set for a specified speed ratio, shaft angle, input torque, and power. Significant parameters in the design are: the spiral angle, the pressure angle, the numbers of teeth on the pinion and gear, and the location and size of the four support bearings. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for gradient optimization. After finding the continuous optimum, a designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗

THE INFLUENCE OF CHANGES IN NUCLEAR COVARIANCE DATA ON THE CALCULATION OF Ck FOR HIGHLY ENRICHED URANIUM SOLUTION SYSTEMS

Since their initial development nearly 20 years ago, sensitivity/uncertainty (S/U) techniques have been increasingly applied to criticality safety validation. These techniques can generally be applied quickly and for a range of purposes after the initial investment of calculating sensitivities for a safety analysis model and a range of potential benchmark experiments. This paper discusses these applications and how they have been affected by changes in covariance data libraries.Critical experiment selection is the most prominent area in which S/U methods impact validation efforts. These methods allow for rigorous calculation of similarity between safety analysis models and potential benchmarks. The most widely used of these methods is the integral parameter ck, although other integral parameters such as E and some non-integral parameters have also been explored. The ck parameter calculates the fraction of nuclear data–induced uncertainty shared between an application and an experiment; this metric is predicated on the assessment that nuclear data errors are the most likely source of computational bias. Therefore, values of ck are inherently dependent on the nuclear covariance library used to calculate them and inevitably change when these data change.Past studies have shown how much the ck values can vary, especially in difficult validation cases like burnup credit. These significant changes are the result of differences in the relative uncertainties of nuclides with large sensitivities, and they imply differences in benchmark applicability to the safety analysis model. This paper demonstrates that more common criticality safety models involving single fissile species have significantly less variability of ck between covariance libraries, thus enhancing confidence in the application of S/U methods for experiment selection in these scenarios. This paper presents case studies examining the impact of these changes on some hypothetical safety analysis systems.

Clarity, Justin↗

First Measurement of Differential Charged Current Quasielastic-like $\nu_\mu$–Argon Scattering Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

We report the first measurement of flux-integrated multi-differential cross sections for charged-current events with muon neutrinos scattering on argon with solely a muon and a single proton in the final state as a function of kinematic imbalance variables. The measurement was carried out using the Booster Neutrino Beam at Fermi National Accelerator Laboratory within the MicroBooNE Liquid Argon Time Projection Chamber detector with an exposure of 6.79 × 10 20 protons on target. Events were selected to enhance the contribution of charged-current mesonless interactions with one proton detected in the final state. The data discussed here are reported in terms of multidifferential cross sections in kinematic imbalance variables, which are generally sensitive to nuclear effects. The double-differential results in these variables can provide an excellent handle to disentagle specific nuclear aspects not easily isolated via single differential cross sections. Our results pave a path towards identifying regions of the phase-space where future interaction modeling development and Monte Carlo neutrino generator tuning efforts should concentrate. EVENT SELECTION Neutrino oscillation measurements aim to extract neutrino mixing angles, mass differences, the value of the chargeparity violating phase in the lepton sector, and to search for new physics beyond the Standard Model [1, 2]. For that to be achieved, an unprecedented understanding of neutrino-argon interactions is of utmost importance since a growing number of neutrino oscillation experiments employ Liquid Argon Time Projector Chamber (LArTPC) neutrino detectors [3–6]. The accuracy to which these experiments can extract neutrino oscillation parameters requires a good understanding of the neutrino energy. Experimentally, this energy is deduced from the measured kinetic energies of particles that are emitted following the neutrino interaction in the detector. The kinematic properties of such finalstate particles reflect complex dynamics due to nuclear and initial-state effects of the interaction [7]. However, certain categories of nuclear effects can be isolated by variables built specifically to characterize the degeneracy between such effects [8–10]. This note reports cross sections in kinematic variables sensitive to nuclear effects using events with one detected muon with momentum 0.1 < pµ < 1.2 GeV/c, and exactly one proton with 0.3 < pp < 1 GeV/c. This signal definition includes events with any number of protons below 300 MeV/c, neutrons at any momenta, and charged pions with momentum lower than 70 MeV/c. This choice is guided by the fact that their experimental signature of correlated muon-proton pairs is fairly straightforward to reconstruct [11–22]. Such events primarily originate from chargedcurrent (CC) neutrino-nucleon quasielastic (QE) scattering interactions where the neutrino removes a single intact nucleon from the nucleus without producing any additional particles. This definition can also include contributions from interactions that lead to the production of additional particles that are absent from the final state due to nuclear effects, such as pion absorption, or have momenta that are below the experimental detection threshold.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Guidelines and considerations for designing field experiments simulating precipitation extremes in forest ecosystems

1. Precipitation regimes are changing in response to climate change, yet understanding of how forest ecosystems respond to extreme droughts and pluvials remains incomplete. As future precipitation extremes will likely fall outside the range of historical variability, precipitation manipulation experiments (PMEs) are critical to advancing knowledge about potential ecosystem responses. However, few PMEs have been conducted in forests compared to short-statured ecosystems, and forest PMEs have unique design requirements and constraints. Moreover, past forest PMEs have lacked coordination, limiting cross-site comparisons. Here, we review and synthesize approaches, challenges, and opportunities for conducting PMEs in forests, with the goal of guiding design decisions, while maximizing the potential for coordination. 2. We reviewed 63 forest PMEs at 70 sites world-wide. Workshops, meetings, and communications with experimentalists were used to generate and build consensus around approaches for addressing the key challenges and enhancing coordination. 3. Past forest PMEs employed a variety of study designs related to treatment level, replication, plot and infrastructure characteristics, and measurement approaches.Important considerations for establishing new forest PMEs include: selecting appropriate treatment levels to reach ecological thresholds; balancing cost, logistical complexity, and effectiveness in infrastructure design; and preventing unintended water subsidies. Response variables in forest PMEs were organized into three broad tiers reflecting increasing complexity and resource intensiveness, with the first tier representing a recommended core set of common measurements. 4. Differences in site conditions combined with unique research questions of experimentalists necessitate careful adaptation of guidelines for forest PMEs to balance local objectives with coordination among experiments. We advocate adoption of a common framework for coordinating forest PME design to enhance cross-site comparability and advance fundamental knowledge about the response and sensitivity of diverse forest ecosystems to precipitation extremes.

Climate Extremes, drought, ecological thresholds, ↗

A Multi-Pixel Split-Window Approach to Sea Surface Temperature Retrieval from Thermal Imagers with Relatively High Radiometric Noise: Preliminary Studies

In the following decade(s), a set of satellite missions carrying thermal infrared (TIR) imagers with a relatively high noise equivalent differential temperature (NEdT) are expected, e.g., the high resolution TIR imagers flying on the future Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment (TRISHNA), Land Surface Temperature Monitoring (LSTM) and NASA-JPL/ASI Surface Biology and Geology Thermal (SBG) missions or the secondary payload on board the ESA Earth Explorer 10 Harmony. The instruments on board these missions are expected to be characterized by an NEdT of ⪆0.1 K. In order to reduce the impact of radiometric noise on the retrieved sea surface temperature (SST), this study investigates the possibility of applying a multi-pixel atmospheric correction based on the hypotheses that (i) the spatial variability scales of radiatively active atmospheric variables are, on average, larger than those of the SST and (ii) the effect of atmosphere is accounted for via the split window (SW) difference. Based on 32 Sentinel 3 SLSTR case studies selected in oceanic regions where SST features are mainly driven by meso to sub-mesoscale turbulence (e.g., corresponding to major western boundary currents), this study documents that the local spatial variability of the SW difference term on the scale of ≃3 × 3 km2 is comparable with the noise associated with the SW difference. Similarly, the power spectra of the SW term are shown to have, for small scales, the behavior of white noise spectra. On this basis, we suggest to average the SW term and to use it for the atmospheric correction procedure to reduce the impact of radiometric noise. In principle, this methodology can be applied on proper scales that can be dynamically defined for each pixel. The applicability of our findings to high-resolution TIR missions is discussed and an example of an application to ECOSTRESS data is reported.

sea surface temperature↗

Bioinspired oxidation of benzyl alcohol: The role of environment and nuclearity of the catalyst evaluated by multivariate analysis

Inspired by copper-containing enzymes such as galactose oxidase and catechol oxidase, in which distinct coordination environments and nuclearities lead to specific catalytic activities, we summarize here the catalytic properties of dinuclear and mononuclear copper species towards benzyl alcohol oxidation using a multivariate statistical approach. Here, the new dinuclear [Cu 2 (μ-L 1 )(μ-pz)] 2+ (1) is compared against the mononuclear [CuL 2 Cl] (2), where (L 1 ) - and (L 2 ) - are the respective deprotonated forms of 2,6-bis((bis(pyridin-2-ylmethyl)amino)methyl)-4-methylphenol, and 3-((bis(pyridin-2-ylmethyl)amino)methyl)-2-hydroxy-5-methylbenzaldehyde and (pz) - is a pyrazolato bridge. Copper(II) perchlorate (CP) is used as control. The catalytic oxidation of benzyl alcohol is pursued, aiming to assess the role of the ligand environment and nuclearity. The multivariate statistical approach allows for the search of optimal catalytic conditions, considering variables such as catalyst load, hydrogen peroxide load, and time. Species 1, 2 and CP promoted selective production of benzaldehyde at different yields, with only negligible amounts of benzoic acid. Under normalized conditions, 2 showed superior catalytic activity. This species is 3.5-fold more active than the monometallic control CP, and points out to the need for an efficient ligand framework. Species 2 is 6-fold more active than the dinuclear 1, and indicates the favored nuclearity for the conversion of alcohols into aldehydes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗