Thermometry Measurements Research Articles

Investigation of critical heat flux enhancement on nanoengineered surfaces in pressurized subcooled flow boiling using infrared thermometry

Enhancing the flow boiling critical heat flux (CHF) is beneficial to the economics and safety margins of many industrial applications cooled by boiling heat transfer. While many studies have shown that surfaces with hydrophilic nanoscale and micro-scale features can enhance CHF in pool boiling, it is still not clear how these engineered surfaces affect the CHF in subcooled flow boiling at ambient pressure, let alone high-pressure conditions. Here, two nano-engineered surfaces, i.e., a surface coated with a porous layer of hydrophilic silica nanoparticles and a surface coated with zinc oxide nanowires, were tested. Flow boiling tests with a 10 K subcooling and a mass flux of 1000 kg/(m2·s) were conducted at 1 bar and 4 bars using infrared thermometry diagnostics. At 1 bar, the CHF enhancement is around 15% for both coatings. At 4 bars, the CHF enhancement is around 17% for the nanowire surface, and around 25% for the nano-porous surface. Infrared thermometry measurements reveal that the CHF enhancement comes from an increase of both two-phase heat transfer and single-phase heat transfer mechanisms, which is due to a change of bubble dynamics on the nanoengineered surfaces. It is also shown that the boiling crisis can be predicted using a percolation model based on Monte Carlo (MC) simulations.

Flame structure and broadening in turbulent premixed jet flames

High-resolution and high signal-to-noise (SNR) planar Rayleigh scattering thermometry measurements are performed to investigate preheat and reaction zone broadening, turbulent transport of high-temperature gases, and the internal flame structure in a series of highly turbulent, lean (ϕ = 0.75), premixed methane-air turbulent jet flames. These flames are characterized by turbulence intensities ranging from u′/SL of 35 to 150 and turbulent Reynolds numbers approaching 104, as determined from separate particle image velocimetry (PIV) measurements. Average flame profiles obtained using a gradient-based flame reconstruction method and probability density functions (PDFs) of the preheat, reaction, and thermal layer thicknesses show substantial broadening of the preheat and thermal layers. Instantaneous preheat zones are broadened by as much as a factor of 30 compared to laminar flames, with an average broadening approaching a factor of 14 for the most turbulent case. Moderate broadening of the reaction layer is observed with up to a factor of eight times that of a laminar premixed flame for instantaneous realizations and an average broadening of four times that of a laminar flame for the most turbulent case. Conditional statistics of temperature obtained at isodistance contours within and upstream of the preheat zone show large shifts towards significantly higher temperatures compared to laminar flame values. In addition, broad temperature distributions and reduced thermal gradients at each position provide strong evidence of persistent turbulent transport of high-temperature gases ahead of the preheat zone. Finally, a detailed analysis of scalar dissipation rate statistics and dissipation layer topology was conducted. The conditional mean scalar dissipation rates for the turbulent flames show significant reductions compared to calculated laminar flame values and a shift towards higher values of the reaction progress variable (CT) for increasing turbulence levels. PDFs show a transition from near-Gaussian to highly negatively skewed with increasing turbulence levels, where the most probable values of the scalar dissipation rate shift towards higher values of CT, indicating that the primary reaction zone and flame front are subjected to increased strain. In terms of structure, no significant broadening of the small-scale dissipation layers was observed with increasing turbulence intensity. However, as turbulence intensity increases, there is a transition from a sparse number of continuous layers to a large number of shorter, ”broken”, nearly straight segments. The reduction of individual layer lengths (i.e., ”breaking”) is favored over increases in dissipation layer wrinkling, where the sharp decreases in the local dissipation rate values are highly correlated with regions of high curvature. A final notable outcome of this work is that there were negligible differences in all statistical and topological results when moving between the two highest turbulent cases, even though the turbulence intensity, turbulent Reynolds number, and the turbulence Karlovitz number increased substantially (70 - 120%). This implies that there may be an asymptotic limit in which turbulence affects flame behavior for the current configuration.

Paleoclimate Changes in the Pacific Northwest Over the Past 36,000 Years From Clumped Isotope Measurements and Model Analysis

AbstractSince the last glacial period, North America has experienced dramatic changes in regional climate, including the collapse of ice sheets and changes in precipitation. We use clumped isotope (∆47) thermometry and carbonate δ18O measurements of glacial and deglacial pedogenic carbonates from the Palouse Loess to provide constraints on hydroclimate changes in the Pacific Northwest. We also employ analysis of climate model simulations to help us further provide constraints on the hydroclimate changes in the Pacific Northwest. The coldest clumped isotope soil temperatures T(47) (13.5 ± 1.9°C to 17.1 ± 1.7°C) occurred ∼34,000–23,000 years ago. Using a soil‐to‐air temperature transfer function, we estimate Last Glacial Maximum (LGM) mean annual air temperatures of ∼−5.5°C and warmest average monthly temperatures (i.e., mean summer air temperatures) of ∼4.4°C. These data indicate a regional warming of 16.4 ± 2.6°C from the LGM to the modern temperatures of 10.9°C, which was about 2.5–3 times the global average. Proxy data provide locality constraints on the boundary of the cooler anticyclone induced by LGM ice sheets, and the warmer cyclone in the Eastern Pacific Ocean. Climate model analysis suggests regional amplification of temperature anomalies is due to the proximal location of the study area to the Laurentide Ice Sheet margin and the impact of the glacial anticyclone on the region, as well as local albedo. Isotope‐enabled model experiments indicate variations in water δ18O largely reflect atmospheric circulation changes and enhanced rainout upstream that brings more depleted vapor to the region during the LGM.

Mn5+ Lifetime‐Based Thermal Imaging in the Optical Transparency Windows Through Skin‐Mimicking Tissue Phantom

AbstractLifetime‐based luminescence thermometry has been shown to enable accurate deep‐tissue monitoring of temperature changes – even at the in vivo level – in a minimally invasive way. However, major limiting factors to the performance of this approach are short lifetimes and poor brightness. These are characteristics, respectively, of semiconductor nanocrystals and lanthanide‐doped nanoparticles, of which most luminescent nanothermometers are made. To address these limitations, the composition of luminescent nanothermometers co‐doped with transition metal (Mn5+) and Er3+ ions are designed and optimized. The salient features of these nanothermometers are strong, near‐infrared emission and long, temperature‐dependent photoluminescence lifetime. The potential of these luminescent nanophosphors for thermal sensing is then showcased by monitoring a thermal gradient using a one‐of‐a‐kind piece of equipment designed for lifetime‐based luminescence thermometry measurements. The combination of the newly developed nanothermometers and the custom‐made instrument allows for obtaining 2D thermal maps both in the absence and presence of tissue phantoms mimicking the optical properties of the skin. The results presented in this study thus provide credible foundations for the deployment of lifetime‐based thermometry for accurate deep‐tissue thermal mapping at the preclinical level.

Characterization of Fluorescence Tracers for Thermometry and Film Thickness Measurements in Liquid Coolants Relevant for Thermal Management of Electric and Electronic Components.

This study investigated a novel two-color LIF (laser-induced fluorescence) technique for thermometry in coolants relevant for electric components. In principle, this diagnostic enables thermometry in liquid flows but also a simultaneous determination of film thickness and film temperature, which is relevant, e.g., for jet impingement cooled electric components. Temperature measurements are based on a temperature-sensitive intensity ratio of special tracers realized by suitable band pass filters within the respective emission spectra. For this purpose, the heat transfer fluids Fragoltherm F12, Marlotherm LH, and a water-glycol mixture WG20 (80 vol.% water, 20 vol.% glycol) and its individual components were doped with suitable tracers. The tracer Eosin-Y was utilized for polar coolants (water, WG20, and glycol) and Nile red was utilized for non-polar solvents (Fragoltherm F12 and Marlotherm LH). The spectral LIF intensities were recorded for a wide range of temperatures (253-393 K), which are relevant for cooling of electric motors, batteries, and power electronics. Furthermore, absorption spectra were analyzed as well. The temperature-dependent fluorescence measurements revealed different behavior for the polar and non-polar solvents. A temperature increase in the polar solvents (water, WG20, glycol) led to a spectral shift of the emission peaks of Eosin-Y towards longer wavelengths (red-shifted), while the peaks of Nile red in the non-polar solvents (Fragoltherm F12 and Marlotherm LH) showed an opposite behavior and were blue-shifted. The highest average temperature sensitivity was achieved for Marlotherm LH (4.22%/K), followed by glycol (1.99%/K), WG20 (1.80%/K), water (1.62%/K), and Fragoltherm F12 (1.12%/K). These sensitivities are similar to or even much higher than the literature data of other LIF tracers, which were, however, not determined in those coolants. Consequently, the two novel proposed dyes for the studied heat transfer liquids enable a reliable temperature determination.

Water vapor in hydrogen flames measured by time-resolved collisional dephasing of the pure-rotational N2 CARS signal

We present a novel diagnostic technique to probe water vapor (H2O) concentration in hydrogen (H2) combustion environments via the time-resolved measurement of the collisional dephasing of the pure-rotational coherent anti-Stokes Raman scattering (CARS) signal of nitrogen (N2). The rotational Raman coherence of the N2 molecules, induced by the interaction with the pump and Stokes laser fields, dephases on a timescale of hundreds of picoseconds (ps), mostly due to inelastic collisions with other molecules in atmospheric flames. In the spatial region of H2 flames where H2O is present in appreciable amount, it introduces a faster dephasing of the N2 coherence than the other major combustion species do: we use time-resolved femtosecond/picosecond (fs/ps) CARS to deduce the H2O mole fraction from the dephasing effect of its inelastic collisions with N2. The proof-of-principle is demonstrated in a laminar H2/air diffusion flame, performing sequential measurements of the collisional dephasing of the N2 CARS signal up to 360 ps. We measure the temperature and the relative O2/N2 and H2/N2 concentrations at a short probe delay, and input the results in the time-domain model to extract the H2O mole fraction from the signal decay, thus measuring the whole scalar flow fields across the flame front. We furthermore present single-shot simultaneous thermometry and absolute concentration measurements in the turbulent TU Darmstadt/DLR Stuttgart canonical ‘H3 flame’ performed by dual-probe CARS measurements obtained with a polarization separation approach. This allows us to probe the molecular coherence simultaneously at ∼20 and ∼250 ps on the basis of a single-laser-shot, and record the resulting signals in two distinct detection channels of our unique polarization-sensitive coherent imaging spectrometer. The proposed technique allows for measuring the absolute concentrations of all the major species of H2 flames, thus providing a full characterization of the flow composition, as well as of the temperature field.

Thermocouple-based thermometry for laminar sooting flames: Implementation of a fast and simple methodology

This work reports the implementation and the validation of the extrapolation method for thermocouple temperature measurements corrected from the radiation losses in sooting flames. This simple method relies on the use of thermocouples having different size diameters and enables a fast and direct determination of the flame temperature by extrapolation to zero diameter. We propose here a detailed study of the possibilities and limitations offered by this method based on experimental measurements and comparison with well-established methods carried out in a laminar diffusion sooting flame. In details, a specific fast insertion setup using four different sized thermocouples has been implemented to record temperature values at different heights in the flame. From these data, we highlight that a linear calibration curve correlates the raw measured temperatures to the flame temperatures corrected of the radiation losses can be easily and rapidly obtained. The impact of soot deposition on the thermocouple on the temperature measurement is also discussed. To assess the reported thermocouple methodology, a direct comparison is made between the temperature profile determined along the vertical central axis of the flame by the extrapolation method with OH and NO LIF thermometry measurements as well as numerical simulation. Finally, we also report the comparison of experimental and simulated radial temperature profiles highlighting the adequate dynamic of the method for temperature profile determination in high temperature gradient conditions (500 K/mm). This work demonstrates that the extrapolation method is an efficient and fast method to determine accurate temperature profiles in flames, even in presence of soot particles up to a few hundred ppb, which can be useful for the development of fast and cheap sensors for either laboratory or larger-scale applications.

Spatial and spectral filtering strategies for surface phosphor thermometry measurements

Intensity-ratio based phosphor thermometry is a well-established technique to obtain surface temperature measurements, which however suffers from important pixel-to-pixel noise, mainly due to the signal-dependent photon shot noise. In order to enhance signal-to-noise ratio levels, spatial filtering is recognized as a common post-processing routine, with the implication of strongly alleviating the spatial resolution (SR) of measurements. In this study, a dataset of phosphorescence images using Mg4FGeO6:Mn4+ thermographic particles and an ICCD camera is constituted. Various spatial filtering strategies are applied to these images, such as software pixel binning, moving average and Gaussian filters, in order to estimate their relative performances in terms of SR and temperature uncertainty. In addition, a Fourier space low-pass Butterworth filter is benchmarked against these common filters. Results show that the pixel binning strategy provides a limited improvement in the temperature uncertainty when compared to the loss in SR. Conversely, the Gaussian and moving average filters are found to effectively enhance the temperature uncertainty, though the 5th-order Butterworth filter is more selective, by providing an excellent mitigation of high-frequency noise with a minor attenuation of low-frequency information. Eventually, a joint spatial-spectral filtering strategy is investigated, which however does not present significant advantages compared to a sole filtering strategy.

POD-Kalman filtering for improving noninvasive 3D temperature monitoring in MR-guided hyperthermia.

BackgroundDuring resonance frequency (RF) hyperthermia treatment, the temperature of the tumor tissue is elevated to the range of 39–44°C. Accurate temperature monitoring is essential to guide treatments and ensure precise heat delivery and treatment quality. Magnetic resonance (MR) thermometry is currently the only clinical method to measure temperature noninvasively in a volume during treatment. However, several studies have shown that this approach is not always sufficiently accurate for thermal dosimetry in areas with motion, such as the pelvic region. Model‐based temperature estimation is a promising approach to correct and supplement 3D online temperature estimation in regions where MR thermometry is unreliable or cannot be measured. However, complete 3D temperature modeling of the pelvic region is too complex for online usage.PurposeThis study aimed to evaluate the use of proper orthogonal decomposition (POD) model reduction combined with Kalman filtering to improve temperature estimation using MR thermometry. Furthermore, we assessed the benefit of this method using data from hyperthermia treatment where there were limited and unreliable MR thermometry measurements.MethodsThe performance of POD–Kalman filtering was evaluated in several heating experiments and for data from patients treated for locally advanced cervical cancer. For each method, we evaluated the mean absolute error (MAE) concerning the temperature measurements acquired by the thermal probes, and we assessed the reproducibility and consistency using the standard deviation of error (SDE). Furthermore, three patient groups were defined according to susceptibility artifacts caused by the level of intestinal gas motion to assess if the POD–Kalman filtering could compensate for missing and unreliable MR thermometry measurements.ResultsFirst, we showed that this method is beneficial and reproducible in phantom experiments. Second, we demonstrated that the combined method improved the match between temperature prediction and temperature acquired by intraluminal thermometry for patients treated for locally advanced cervical cancer. Considering all patients, the POD–Kalman filter improved MAE by 43% (filtered MR thermometry = 1.29°C, POD–Kalman filtered temperature = 0.74°C). Moreover, the SDE was improved by 47% (filtered MR thermometry = 1.16°C, POD–Kalman filtered temperature = 0.61°C). Specifically, the POD–Kalman filter reduced the MAE by approximately 60% in patients whose MR thermometry was unreliable because of the great amount of susceptibilities caused by the high level of intestinal gas motion.ConclusionsWe showed that the POD–Kalman filter significantly improved the accuracy of temperature monitoring compared to MR thermometry in heating experiments and hyperthermia treatments. The results demonstrated that POD–Kalman filtering can improve thermal dosimetry during RF hyperthermia treatment, especially when MR thermometry is inaccurate.

Intracellular Aβ42 Aggregation Leads to Cellular Thermogenesis.

The aggregation of Aβ42 is a hallmark of Alzheimer’s disease. It is still not known what the biochemical changes are inside a cell which will eventually lead to Aβ42 aggregation. Thermogenesis has been associated with cellular stress, the latter of which may promote aggregation. We perform intracellular thermometry measurements using fluorescent polymeric thermometers to show that Aβ42 aggregation in live cells leads to an increase in cell-averaged temperatures. This rise in temperature is mitigated upon treatment with an aggregation inhibitor of Aβ42 and is independent of mitochondrial damage that can otherwise lead to thermogenesis. With this, we present a diagnostic assay which could be used to screen small-molecule inhibitors to amyloid proteins in physiologically relevant settings. To interpret our experimental observations and motivate the development of future models, we perform classical molecular dynamics of model Aβ peptides to examine the factors that hinder thermal dissipation. We observe that this is controlled by the presence of ions in its surrounding environment, the morphology of the amyloid peptides, and the extent of its hydrogen-bonding interactions with water. We show that aggregation and heat retention by Aβ peptides are favored under intracellular-mimicking ionic conditions, which could potentially promote thermogenesis. The latter will, in turn, trigger further nucleation events that accelerate disease progression.

Data-driven prediction of next-layer melt pool temperatures in laser powder bed fusion based on co-axial high-resolution Planck thermometry measurements

Uncontrolled process variability, stemming from geometry, machine, or parameter variation, can lead to metallurgical defects such as keyhole porosity and lack of fusion as well as geometrical defects such as increased surface roughness or increased deformation in the produced parts. This lack of control is a pressing problem in laser powder bed fusion (L-PBF) processes. One way to reduce this variability is to use model-based predictive control. Process parameters such as laser power and scan speed can be adjusted during the process based on in-situ measurements of process conditions such as melt pool size or temperature. In this paper, a predictive model that is an essential element in a larger predictive control ecosystem for L-PBF is developed and tested. The proposed machine learning-based regression model is trained using high-resolution co-axial melt pool temperature measurements from the previous layers. The machine learning model can predict the melt pool temperatures along the toolpath for the next layer assuming processing parameters remain the same. The paper describes the development of the machine learning-based prediction model and presents the guidelines for the design and selection of the features in feature vector. The estimation of the prediction performance based on real physical data is presented followed by suggestions of future work. The main limitation of the current approach is the relatively high computational cost. Some guidelines for implementation and possible improvements are given in the discussion of results.

Characterization of femtosecond laser-induced grating scattering of a continuous-wave laser light in air.

Nanosecond laser-induced grating scattering/spectroscopy (LIGS) technique has been widely applied for measuring thermodynamic parameters such as temperature and pressure in gaseous and liquid media. Recently, femtosecond (fs) laser was demonstrated to induce the grating and develop the fs-LIGS technique for gas thermometry. In this work, we systematically investigated the fs-LIGS signal generation using 35 fs, 800 nm laser pulses at 1 kHz repetition rate in ambient air by varying the pump laser energies, the probe laser powers and the temporal delays between two pump laser pulses. The stability of single-shot fs-LIGS signal was studied, from which we observed that the signal intensity exhibits a significant fluctuation while the oscillation frequency shows a much better stability. A 4.5% precision of the oscillation frequency was achieved over 100 single-shot signals. By using a previously-developed empirical model, the fs-LIGS signals were fitted using nonlinear least-squares fitting method, by which crucial time constants characterizing the signal decay process were extracted and their dependences on the pump laser energy were studied. From the measured results and theoretical analysis, we found that the appropriate range of the overall pump laser energy for reliable fs-LIGS measurements is approximately located within 80 ∼ 300 μJ. The limitations on the accuracy and precision of the fs-LIGS measurements, the origin of destructive influence of plasma generation on the signal generation as well as the electrostriction contribution were also discussed. Our investigations could contribute to a better understanding of the fs-LIGS process and further applications of the technique in single-shot gas thermometry and pressure measurements in various harsh conditions.

The optimized quantum dot mediated thermometry reveals isoform specific differences in efficiency of myosin extracted from muscle mini bundles

The biophysical function of myosin in vitro has been extensively investigated in different motility assays, but the study of myosin ATPase properties at the fiber level is insufficiently investigated. In this study, quantum dot (QD) mediated thermometry measurements were optimized to measure the efficiency of myosin extracted from muscle mini bundles. A reduction in fluorescent intensity of QD reflects an increase in temperature caused by the heat released during ATP hydrolysis and denotes the efficiency of the motor protein myosin. The procedure for extracting myosin was similar to the single fiber in vitro motility assay with some small modifications, and the concentration of myosin was represented by the extracted total protein since the ratio of extracted myosin to total protein was constant. Moreover, the efficiencies of myosin extracted from preparations containing different myosin heavy chain isoforms reveal lower efficiency of slow compared to fast myosin isoforms. Specifically, more heat was released in slow myosin enzymatic reaction, resulting in faster decay of QD fluorescence intensity. Hence, the optimized QD mediated thermometry provides a novel and sensitive approach to evaluate efficiency of myosin ATPase obtained from small muscle samples, representing a significant advantage in the clinical evaluation of neuromuscular disorders.

Structure and scalar correlation of ammonia/air turbulent premixed flames in the distributed reaction zone regime

Instantaneous structures of turbulent premixed ammonia/air flames on a piloted jet burner were investigated using simultaneous planar laser-induced fluorescence (PLIF) and Rayleigh thermometry measurements. Two-dimensional spatial distributions of temperature were simultaneously measured with those of the NH radical and the NO pollutant, respectively. Experiments were conducted for stoichiometric flames under five jet velocities. All flames are located in the distributed reaction zone regime of the Borghi-Peters diagram with the Karlovitz (Ka) number ranging from 274 to 4720. The NH PLIF images are used to characterize the fuel consumption layer of the reaction zones since the formation of NH is associated with the consumption of ammonia. The NH PLIF results show that under all flame conditions investigated, the NH layer remains thin in the proximity of the burner while it becomes progressively thickened and distorted by turbulence with increasing turbulent intensity and axial distance. For flames with Ka of 274, the NH layer essentially remains thin, while at Ka of 590 or higher, significant broadening of the NH layer is observed. Probability density functions (PDFs) of the NH layer thickness show that the NH layer can be broadened by 3 – 4 times as the flames are developed downstream. The broadening of the NH layer is considered to indicate that the flames are in the distributed reaction zone regime. The boundary between the thin-reaction zone regime and the distributed reaction zone regime occurs at a much larger Ka than that in methane/air flames. The broadening of the NH layer is due to the penetration of the turbulent eddies and the merging of flame branches. The latter occurs mainly near the flame tips. NO is shown to exist in a wide region in space, across the preheat zone, reaction zone, and postflame zone. NO formation occurs mainly in the reaction zone, however, it is transported by turbulence eddies to the preheat zone and by convection to the postflame zone. The temperature measurements indicate that the preheat zone is broadened in all flames investigated. The broadening of the preheat zone is moderately sensitive to the Ka number while it is more sensitive to the integral length scale of the flames.

Investigating photomultiplier tube nonlinearities in high-speed phosphor thermometry using light emitting diode simulated decay curves.

Photomultiplier tube (PMT) nonlinearities relevant for single shot high-speed lifetime phosphor thermometry were investigated by simulating decay curves with a light emitting diode (LED) at repetition rates between 1Hz and 10kHz. The PMT gain, LED decay time, and background radiant flux were also varied to investigate their impact on the measured decay time error. Errors in the measured decay time due to nonlinear PMT performance lead to temperature measurement errors; therefore, having the measured decay time sensitive to only phosphor temperature is highly valuable for more reliable temperature measurements. Photocathode bleaching had a significant impact on the signal level linearity for PMTs with excitation frequency in the kHz regime but had a smaller impact on the decay time error. Space charge effects were most noticeable at high radiant flux levels and high repetition rates. Strong background radiant flux may lead to decay time errors, and a gateable photocathode could be an effective method to reduce decay time errors. The best decay time measurement configuration to maximize precision without sacrificing accuracy is to use PMT gain in the recommended range and the highest radiant flux where the PMT response is still linear. The degree of nonlinearity in the PMT response is partly detector dependent; therefore, the results in this work may differ among detectors; however, the analysis presented in this work provides guidelines for improving the temperature accuracy of kHz lifetime phosphor thermometry measurements.

2-in-1 Dual-Fiber Probe Integrated With Nanodiamonds for Optical Thermometry Measurements

We here propose and demonstrate a novel “2-in-1” fiber consisting of two freely separated fiber ends and one fiber tip mounted with nanodiamonds (NDs) containing nitrogen vacancy (NV) centers. The fiber tip with ball lens is fabricated by fusing two parallel multimode fiber with arcing discharge. The excitation and collection of the integrated NV centers through the two fiber ends, can be optimized by manipulating the fabricated lens. We also demonstrate the feasibility of all-optical thermometry using this device. This endoscopy-like probe paves the way for developing fiber-based quantum device for flexible thermometry and magnetometry.

High-temperature rotational-vibrational O2[sbnd]CO2 coherent Raman spectroscopy with ultrabroadband femtosecond laser excitation generated in-situ

We present ultrabroadband two-beam femtosecond/picosecond coherent Raman spectroscopy on the ro-vibrational spectra of CO2 and O2, applied for multispecies thermometry and relative concentration measurements in a standard laminar premixed hydrocarbon flame. The experimental system employs fs-laser-induced filamentation to generate the compressed supercontinuum in-situ, resulting in a ∼24 fs full-width-at-half-maximum pump/Stokes pulse with sufficient bandwidth to excite all the ro-vibrational Raman transitions up to 1600 cm-1. We report the simultaneous recording of the ro-vibrational CO2 Q-branch and the ro-vibrational O2 O-, Q- and S-branch coherent Stokes Raman spectra (CSRS) on the basis of a single-laser-shot. The use of filamentation as the supercontinuum generation mechanism has the advantage of greatly simplifying the experimental setup, as it avoids the use of hollow-core fibres and chirped mirrors to deliver a near-transform-limited ultrabroadband pulse at the measurement location. Time-domain models for the ro-vibrational Q-branch spectrum of CO2 and the ro-vibrational O-, Q- and S-branch spectra of O2 were developed. The modelling of the CO2 Q-branch spectrum accounts for up to 180 vibrational bands and for their interaction in Fermi polyads, and is based on recently available, comprehensive calculations of the vibrational transition dipole moments of the CO2 molecule: the availability of spectroscopic data for these many vibrational bands is crucial to model the high-temperature spectra acquired in the flue gases of hydrocarbon flames, where the temperature can exceed 2000 K. The numerical code was employed to evaluate the CSRS spectra acquired in the products of a laminar premixed methane/air flame provided on a Bunsen burner, for varying equivalence ratio in the range 0.6–1.05. The performance of the CO2 spectral model is assessed by extracting temperatures from 40-laser-shots averaged spectra, resulting in thermometry accuracy and precision of ∼5% and ∼1%, respectively, at temperatures as high as 2220 K.

Hydrothermal Synthesis of Yb3+: LuLiF4 Microcrystals and Laser Refrigeration of Yb3+: LuLiF4/Silicon‐Nitride Composite Nanostructures

AbstractThe hydrothermal synthesis and characterization of 10%Yb3+:LiLuF4 (LLF) microcrystals are reported. A combination of X‐ray diffraction (XRD) analysis, analytical transmission electron microscopy (TEM), scanning TEM (STEM), energy‐dispersive X‐ray (EDX) spectroscopy), temperature‐dependent Fourier‐transform infrared (FTIR) spectroscopy, and photoluminescence (PL) measurements confirm a scheelite (I41/a) phase and substitutional doping of Yb3+ within the microcrystals. Laser cooling to more than 20 K below room temperature in vacuum (10−3 torr) is demonstrated when irradiating individual microcrystals using a near‐infrared pumping wavelength (λ = 1020nm) at a laser power of 40 mW (irradiance of 0.85 MW cm−2). The use of these microcrystals is further demonstrated for solid‐state laser refrigeration of an electron‐transparent silicon‐nitride (Si3N4) TEM window. A combination of internal luminescence thermometry, heat‐transfer modeling, and control measurements on lithographically patterned Si3N4 optical cavities is used to demonstrate successful bulk laser cooling of Si3N4 TEM windows by ≈15 K below room temperature, opening new opportunities for contactless in situ TEM refrigeration.

A T1-based correction method for proton resonance frequency shift thermometry in breast tissue.

Develop and evaluate the effectiveness of a T1-based correction method for errors in proton resonant frequency shift thermometry due to non-local field effects caused by heating in fatty breast tissues. Computational models of human breast tissue were created by segmenting MRI data from a healthy human volunteer. MR-guided focused ultrasound (MRgFUS) heating and MR thermometry measurements were simulated in several locations in the heterogeneous segmented breast models. A T1-based correction method for PRF thermometry errors was applied and the maximum positive and negative errors and the root mean squared error (RMSE) in a region around each heating location was evaluated with and without correction. The method uses T1measurements to estimate the temperature change in fatty tissues and correct for their influence. Experimental data from a heating study in cadaver breast tissue were analyzed, and the expected PRFS error computed. The simulated MR thermometry had maximum single voxel errors ranging between 10% and 18% when no correction was applied. Applying the correction led to a considerable improvement, lowering the maximum error range to 2%-5%. The 5th to 95th percentile interval of the temperature error distribution was also lowered with correction, from approximately 3.5 to 1°C. This correction worked even when T1 times were uniformly raised or lowered by 5%-10%. The experimental data showed predicted errors of 15%. This simulation study demonstrates that the T1-based correction method reduces MR thermometry errors due to non-local effects from heating in fatty tissues, potentially improving the accuracy of thermometry measurements during MRgFUS treatments. The presented correction method is reliant on having a patient-specific 3D model of the breast, and may be limited by the accuracy of the fat temperatures which in turn may be limited by noise or bias present in the T1measurements.

Decrypting the boiling crisis through data-driven exploration of high-resolution infrared thermometry measurements

We develop a neural network model capable of predicting the margin to the boiling crisis (i.e., the departure from nucleate boiling ratio, DNBR) from high-resolution infrared measurements of the bubble dynamics on surfaces with different morphologies and wettability (or wickability). We use a feature ranking algorithm, i.e., minimum redundancy maximum relevance, to elucidate the importance of fundamental boiling parameters, i.e., nucleation site density, bubble departure frequency, growth time, and footprint radius, in predicting the boiling crisis. We conclude that these parameters are all necessary and equally important. This result has profound implications, as it undermines the general validity of many observations and mechanistic models that attempt to predict the critical heat flux (CHF) by describing how a single boiling parameter changes with the heat flux or from one surface to another. Notably, the neural network model can predict the DNBR on CHF-enhancing surfaces of different wickability without using any input information related to the surface properties. This result suggests that, at least on the considered surfaces, surface wickability enhances the CHF by modifying the bubble dynamics, i.e., the aforesaid boiling parameters, rather than acting as an additional heat removal mechanism.