Surface Temperature Measurements Research Articles

A Precision Livestock Farming Technique from Breeding to Slaughter: Infrared Thermography in Pig Farming

Infrared thermography is a contactless imaging technique, useful for measuring surface temperature at distance, which has been widely applied in animal production. The possible applications within the pig husbandry include sow heat detection, the reduction in the incidence of neonatal mortality, the recognition of the febrile state caused by pathogens, the study of metabolic efficiency, the evaluation of stress caused by heat, by constraints, or by aggressive interaction, and meat quality prediction. Even if this technique could be easily influenced by environmental factors, the continuous improvement in the procedures and the decrease in the cost of the equipment will allow for new and more applications in swine farming in the future.

Breast Cancer Screening Using Inverse Modeling of Surface Temperatures and Steady-State Thermal Imaging.

Cancer is characterized by increased metabolic activity and vascularity, leading to temperature changes in cancerous tissues compared to normal cells. This study focused on patients with abnormal mammogram findings or a clinical suspicion of breast cancer, exclusively those confirmed by biopsy. Utilizing an ultra-high sensitivity thermal camera and prone patient positioning, we measured surface temperatures integrated with an inverse modeling technique based on heat transfer principles to predict malignant breast lesions. Involving 25 breast tumors, our technique accurately predicted all tumors, with maximum errors below 5 mm in size and less than 1 cm in tumor location. Predictive efficacy was unaffected by tumor size, location, or breast density, with no aberrant predictions in the contralateral normal breast. Infrared temperature profiles and inverse modeling using both techniques successfully predicted breast cancer, highlighting its potential in breast cancer screening.

Highly stable lead-free perovskite glass for real-time 3D surface temperature measurement across the wide temperature range

3D Optical temperature sensors are highly valuable in various fields such as industry, medicine, and aerospace, as they allow for real-time detection of temperature distribution on surfaces. However, existing temperature sensor materials face challenges in achieving accurate detection across a wide range of temperatures from low to high. To overcome these issues, Cs2Zn1-xEuxBr4 perovskite B2O3–BaF2-Ga2O3 (BBG) borate glass was prepared for non-contact 3D optical temperature sensing. Cs2Zn1-xEuxBr4 perovskite B2O3–BaF2-Ga2O3 (BBG) borate glass improves the stability, thus expanding the temperature measurement range. Utilizing the fluorescence intensity ratio (FIR) method, based on the 613 nm (Eu3+: 5D0→7F2) and 592 nm (Eu3+: 5D0→7F1) emission bands, a FIR benchmark database was constructed for the entire temperature range from 10 K to 640 K. Temperature calculation equations related to FIR were derived, with a maximal relative sensitivity of 0.08 % K−1 at 180 K. The method for measuring the surface temperature of 3D curved aircraft is based on the rare earth perovskite borate glass. The temperature measured with this method is close to the thermal imaging temperature and has a good temperature measuring effect. The temperature measurement range is wider and more advantageous than previously reported ranges. These results indicate that Cs2Zn1-xEuxBr4-BBG perovskite borate glass temperature sensors have broad application prospects in many applications.

Study of Temporal Dynamics of Urban Heat Island Surface in Padang West Sumatra, Indonesia

Padang as the capital of the province, is a strategic area and also the center of the economy. Annual population growth affects changes in land use from vegetated land to built-up areas. An increase in barren land will trigger an increase in temperature. SUHI is a temperature phenomenon that occurs on the surface resulting from the increase in temperature. SUHI can be observed through surface temperature data or Land Surface Temperature. This study aims to identify changes in land surface temperature that are affected by changes in land use in the form of building density conditions. In analyzing this using Landsat 7 ETM+ imagery in 2001, 2006, 2011, 2016, and 2020. The building density measurement method LST transformations to measure surface temperature and helps the Surface Urban Heat Island phenomenon. The results of the analysis showed that there was an increase in the building density of the city of Padang over a period of 20 years. This phenomenon affects the surface temperature, indicating that the surface temperature has increased by around 0.47°C. The highest temperature from 2001-2020 occurred in 2016, with the highest temperature of 36°C.

Analysis of scuffing through temperature measurement experiment and numerical simulation for spiral bevel gears

Tooth surface scuffing failure, as one of the primary failure modes of gears, frequently occurs during the operation of gear mechanisms. Scuffing properties of spiral bevel gears were investigated through a numerical analysis and experimental study. A novel temperature model for a single tooth was proposed to predict scuffing temperatures on the tooth surface. The model allows the analysis of variations in tooth surface temperature, considering both operating conditions and tooth contact scenarios. Experiments were carried out to explore tooth surface adhesion of spiral bevel gears under precisely defined operating conditions. Measurement of tooth surface temperatures was conducted by combining non-contact infrared temperature sensors and temperature-measuring cameras. This experiment verifies temperature changes on the tooth surface adhesion of spiral bevel gears. The combination of two temperature measurement methods ensures accurate temperature measurements, with errors below 8%, and facilitates the swift opening of the end cover. Experimental validation of the scuffing prediction model yields a maximum temperature difference of 5.93%. The method establishes a theoretical foundation for evaluating tooth surface adhesion of spiral bevel gears.

Internal temperature estimation for lithium-ion batteries through distributed equivalent circuit network model

Lithium-ion cells experience significant internal thermal gradients during operation, with a direct impact on their safety, performance, cost and lifetime. The estimation of the internal temperature of cells is therefore particularly important. In this work, a 3D distributed electro-thermal model for internal temperature estimation is developed for a cylindrical cell (LG M50T, NMC811). The model is parameterized and comprehensively validated against experimental data for 21700 cells, including direct core temperature measurements. Multiple types of electrical load are considered, including constant current discharge, pulse discharge, drive cycle and instant discharge/charge switching. The developed model is used to estimate core temperature based on surface temperature measurement. The predictions are shown to have good accuracy at relatively low computational cost. We show that the widely adopted two-node lumped thermal estimation model is increasingly inaccurate for more aggressive discharges, when thermal gradients become higher. Compared to the standard two-node model, the distributed equivalent circuit network model predicts the effects of detailed internal cell structure (electrode, current collector, metal can and tab) and distributed internal heat generation. The results are of immediate interest to cell manufacturers and battery pack designers, while the modelling and parameterization framework is a useful tool for energy storage systems design.

Graphics‐Processing‐Unit‐Accelerated 3D Online Heat Transfer and Solidification Model for Continuously Cast Slab

A graphics‐processing‐unit (GPU)‐accelerated 3D heat‐transfer and solidification model is proposed to predict the temperature field and solidification field for continuously cast slab. The fully 3D model is developed based on the finite difference method and implemented on the compute unified device architecture (CUDA)/C++ platform. The model is verified by solving the 1D Stefan problem and validated by surface temperature measurements. The model is proven to be 18.91 times faster for the coarsest mesh of 35 million nodes and 22.92 times faster for the finest mesh of 50 million nodes than a central‐processing‐unit (CPU)‐based parallel version with 28 threads. The corresponding relative calculational times are 0.19 and 0.32, which indicate that the model has great computation efficiency. The model is proven to be robust enough for the dynamic continuous casting (CC) process via a test of dynamic casting speed. Further analysis of the nonuniform heat transfer and solidification shows that the model is able to predict the nonuniform heat transfer efficiently. In the studied cases, a higher casting speed will lead to a remarkable enhancement of the unevenness of heat transfer and solidification in general.

Characterization and Validation of ECOSTRESS Sea Surface Temperature Measurements at 70 m Spatial Scale

The ECOSTRESS push-whisk thermal radiometer on the International Space Station provides the highest spatial resolution temperature retrievals over the ocean that are currently available. It is a precursor to the future TRISHNA (CNES/ISRO), SBG (NASA), and LSTM (ESA) 50 to 70 m scale missions. Radiance transfer simulations and triple collocations with in situ ocean observations and NOAA L2P geostationary satellite ocean temperature retrievals were used to characterize brightness temperature biases and their sources in ECOSTRESS Collection 1 (software Build 6) data for the period 12 January 2019 to 31 October 2022. Radiometric noise, non-uniformities in the focal plane array, and black body temperature dynamics were characterized in ocean scenes using L1A raw instrument data, L1B calibrated radiances, and L2 skin temperatures. The mean brightness temperature biases were −1.74, −1.45, and −1.77 K relative to radiance transfer simulations in the 8.78, 10.49, and 12.09 µm wavelength bands, respectively, and skin temperatures had a −1.07 K bias relative to in situ observations. Cross-track noise levels range from 60 to 600 mK and vary systematically along the focal plane array and as a function of wavelength band and scene temperature. Overall, radiometric uncertainty is most strongly influenced by cross-track noise levels and focal plane non-uniformity. Production of an ECOSTRESS sea surface temperature product that meets the requirements of the SST community will require calibration methods that reduce the biases, noise levels, and focal plane non-uniformities.

Spatiotemporal Drought Assessment in Ningxia Autonomous Region: A Machine Learning and Remote Sensing Approach

Drought represents a significant disaster that directly impacts the economic and ecological welfare of any nation it afflicts. This study focused on the climatic anomalies of drought over the Ningxia Hui autonomous region in northwest China over the last two decades. The study employed an in-depth machine learning model, which incorporated drought indices, thus leading to a data-informed analysis of Ningxia drought patterns. The study accomplished this by using MODIS satellite data products available for vegetation and moisture monitoring. The MOD09GA, MOD11A2, and MCD43A4 data streams were loaded into Google Earth Engine as factors to develop a time-series dataset of vegetation indices. Indices are Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Temperature (LST) measurements are taken into account. Data on temperature, precipitation, and evapotranspiration was compiled for the period from 2003 to 2023 and calculated standardized indices on pixel level for the whole Ningxia region to develop the Standardized Precipitation Index (SPI), Keetch-Byram Drought Index (KBDI), and Standardized Precipitation-Evapotranspiration Index ( The study results indicated that SPI fell significantly from the year 2003 to 2023, from 0.7 to -0.3. The SPEI plummeted from 0.5 to -0.2 during the observed time frame. KBDI also went up, through 581.33 in 2003 and 681.091 in 2023, showing deterioration of aridity and drying of the soil. The conclusion of this study focuses on the deterioration of drought conditions in the Ningxia region in the last 20 years.

Thermographic assessment of skin temperature after lumbar spine surgery: Useful method for detection of wound complications? A pilot study.

Wound complications after lumbar spine surgery may result in prolonged hospitalization and increased morbidity. Early identification can trigger appropriate management. The aim of this study was to investigate the efficacy of infrared-based wound assessment (FLIR) after lumbar spine surgery in the context of identifying wound healing disorders. 62 individuals who underwent lumbar spine surgery were included. The immediate postoperative course was studied, and the patient's sex, age, body mass index (BMI), heart rate, blood pressure, body temperature, numeric rating scale for pain (NRS), C-reactive protein (CRP), leukocyte, and hemoglobin levels were noted and compared to thermographic measurement of local surface temperature in the wound area. Measurement of local surface temperature in the wound area showed a consistent temperature distribution while it was uneven in case of wound healing disorder. In this instance, the region of the wound where the wound healing disorder occured had a lower temperature than the surrounding tissue (p> 0.05). This study demonstrates the ongoing importance of clinical wound assessment for early detection of complications. While laboratory parameter measurement is crucial, FLIR may serve as a cost-effective supplemental tool in clinical wound evaluation. Patient safety risks appear minimal since local ST is measured without touch.

Land Surface Temperature Retrieval From GF5-01A Based on Split- Window Algorithm

Abstract. Land Surface temperature (LST) is a core parameter in the energy exchange between the surface and the atmosphere, and the use of thermal infrared remote sensing can realize the wide-range, fast, and accurate acquisition of surface temperature. GF5-01A is an important part and the final satellite of the major special project on high-resolution Earth observation system which is equipped with a wide-area thermal infrared imager with a resolution of 100 meters and a width of 1,500 kilometers. In this paper, based on the GF5-01A WTI spectral response function, combined with the TIGR2000 atmospheric profiles data and the ASTER spectral library, the data simulation was carried out by using the atmospheric radiative transfer model MODTRAN 5.2, and then constructed the split-window algorithm. Then, the method proposed in this paper was validated and evaluated using Landsat 8/9 temperature products and measured surface temperature data from SURFRAD sites acquired on the same day. The results show that the RMSE between the GF5-01A retrieved LST and the Landsat8/9 retrieved LST is between 1.27–2.24K, and the Bias is between −2.08–1.12K. The RMSE is between 0.68–2.64K and the bias is between −0.68–1.49K compared to the measured surface temperature. The split-window algorithm of GF5-01A proposed in this paper can meet the requirements of thermal infrared remote sensing monitoring and has enormous potential and value.

Study on Temperature Cascade ELM Inversion Method for 110 kV Single-Core Cable Intermediate Joints

The accurate calculation of the hotspot temperature of the cable intermediate joint can effectively guarantee the safe operation of the transmission and distribution network. This paper addresses the limitations of the current method of estimating hotspot temperature solely from surface temperature measurements. Specifically, we focus on a 110 kV single-core cable as our subject of study. We started by establishing a simulation model for the temperature field at the intermediate joint to generate data samples. Subsequently, the NCA (neighborhood component analysis) algorithm was employed to select the optimal measurement points on the cable’s surface. This allowed determination of the quantity and location of characteristic points. Finally, we developed a cascading inversion model, which consists of a radial inversion model and an axial inversion model, based on the extreme learning machine algorithm. The example results show that the mean squared error of hotspot temperature obtained by cascade inversion and direct inversion is 6.95 and 24.71, respectively, indicating that cascade inversion can effectively improve the inversion accuracy.

Theoretical and numerical investigation of introduced errors in surface temperature measurements of pistons applied in internal combustion engine

DMP (Differences in Material Properties) often exists between temperature sensors and combustion chamber components of ICE (Internal Combustion Engine), resulting in IEs (Introduced Errors) in the temperature measuring process. In this paper, we present a comprehensive theoretical analysis of the correlation between introduced errors on chamber components and the DMP. The analysis process considers the characteristics of the chamber's heat transfer BC (Boundary Condition). Then, simulations are used to investigate the introduced error of hardness plug and thermocouple sensors on the top surface of an ICE aluminum alloy piston. The theoretical analysis results indicate that heat transfer BC can be segmented into the time-averaged and fluctuation parts, and IEs are linearly superimposed under these two parts of BCs. The heat conductivity impacts the time-averaged error and the product of heat conductivity, density, and heat capacity impacts the fluctuation error. The experimental and simulation results indicate that the max time-average error of the hardness plug on piston is 2.4 °C, with a fluctuation introduced error of 3.6 °C and a total introduced error of 6 °C; and the time-average introduced error of thermocouple sensor is 9.4 °C, with a fluctuation error of 5.8 °C and a total introduced error of 15.2 °C. Finally, a fluctuation error correction method is proposed to reduce error. After correction, the error is reduced by 71 % and 66 % for hardness plug and thermocouple, respectively.

Abstract PO1-07-12: Inverse modeling with surface temperature accurately detects the presence of breast cancer

Abstract Breast cancer affects over 250,000 women in the United States every year. Patient outcomes including overall survival significantly decline with large sized tumors and nodal involvement on initial presentation. The introduction of mammogram screening has been instrumental in the early detection of cancer. However, it has lower sensitivity in dense breast tissue and limited specificity which leads to unnecessary additional invasive testing. Several methods such as magnetic resonance imaging (MRI), computed tomography (CT) and ultrasound imaging are used as adjunctive methods. However, there is still a need for cost-effective techniques without additional radiation exposure for breast cancer screening for use with mammography. We propose an adjunctive screening method using surface temperature measurements and inverse breast modeling for early detection of breath cancer. Methods: We enrolled patients who presented with mammogram detected breast tumors that were confirmed to be cancerous lesions by biopsy. We used prone position steady state infrared imaging of bilateral breasts to measure surface temperatures and multi-view MRI images to create patient specific 3D breast models. The inverse technique applies Levenberg-Marquard algorithms (LMA) and utilizes commercial software for thermal transport modeling. The inverse technique predicts a heat generation map normalized for baseline surface temperatures to localize the presence of an underlying tumor. Results: A total of 25 breast tumors (diameter range from 5 to 27 mm) from 24 patients were included in the analysis with a median patient age of 67 years. One patient had bilateral breast tumors. Mammogram data showed inclusion of mixed breast tissue composition including dense and extremely dense breast tissue. LMA accurately detected the tumor in all 25 patients with maximum absolute errors of 7 mm in location of the tumor in the breast and 1.78 mm in diameter. The accuracy of detection was not affected by tumor histology which included invasive ductal and lobular carcinomas, ductal and lobular carcinoma in-situ and atypical ductal hyperplasia. No heat sensitive tumors were detected in the 23 contralateral breasts which acted as internal negative controls. Conclusion: Infrared temperature profiles and inverse modeling successfully detected malignant breast tumors with no missed tumors or false positive results and could be used as adjunctive screening along with mammography, especially in patients with dense breast tissue. Citation Format: Nithya Sritharan, Carlos Gutierrez, Isaac Perez-Raya, Jose-Luis Gonzalez-Hernandez, Alyssa Owens, Donnette Dabydeen, Lori Medeiros, Satish Kandlikar, Pradyumna Phatak. Inverse modeling with surface temperature accurately detects the presence of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-12.

Research on Thermocouple Integration Method of Hollow Thin-Walled Turbine Rotor Blade Surface

The hollow thin-walled structure is increasingly used in advanced aero-engine turbine rotor blades, and the traditional surface temperature measurement method based on groove buried couple is no longer applicable. In this paper, a new thermocouple integration method is proposed. The laser additive manufacturing process is used to generate thermocouple embedding channels on the surface of turbine blades. After the thermocouple is embedded, it is pre-fixed, and the thermocouple protection is realized by supersonic flame spraying technology. The strength of the thermocouple integrated structure of the turbine blade is verified by finite element analysis. Based on CFD analysis, the influence of thermocouple integration on the efficiency, pressure ratio and temperature distribution of the turbine blade is studied. The high-speed rotation test shows that the thermocouple integrated structure has high strength and reliability and meets the measurement requirements. This method can provide technical support for the surface temperature measurement of hollow thin-walled turbine rotor blades.

Estimation of thermophysical properties of a pouch-type Li-ion battery using an inverse methodology

The growing popularity of electric vehicles highlights the crucial role of batteries. Effective battery thermal management is crucial for improving performance, reliability, and safety, especially in tropical areas where overheating is a key challenge. This necessitates a comprehensive understanding of the thermophysical properties of batteries. The present study concerns the estimation of the temperature-dependent orthotropic thermophysical properties (kx , ky , kz , cp ) of the active material in a pouch-type Li-ion battery using an inverse methodology. An experimental study is conducted on a commercial AMP20M1HD-A Li-ion battery to measure the surface temperature at various locations using thermocouples. The forward model consists of the three-dimensional unsteady conduction problem and is solved in COMSOL using experimental boundary conditions. The data generated is used to train an Artificial Neural Network, which acts as a replacement for the forward model. The Metropolis Hasting-Markov Chain Monte Carlo algorithm along with the Bayesian inference inverse model is used for analyzing the posterior distribution and the average estimates for thermophysical properties are obtained. The temperature dependence study shows a significant correlation between temperature and battery thermophysical properties. The accuracy of the employed inverse model is validated by obtaining the surface temperature using the estimated thermophysical properties and comparing it with the measured surface temperature.

Lunar North Polar Cold Traps Based on Diurnally and Seasonally Varying Temperatures

Lunar cold traps are defined by extremely low sublimation rates, such that water ice could have accumulated in them. Here time-averaged sublimation rates are calculated for the north polar region of the Moon based on over 14 years of Diviner surface temperature measurements. Data for each spatial pixel are binned according to subsolar (diurnal) and ecliptic (seasonal) longitude. The cold trap area poleward of 80°N is about 32% larger when defined by a time-average sublimation rate instead of by peak temperature. Apparently sunlit cold traps are identified, e.g., in Lenard Crater, where modeling of direct illumination reveals that the Sun briefly rises above the horizon each Draconic year. The true cold trap area is smaller than what can be determined from Diviner data. Also presented are north polar maps for the potential sublimation rate of relic buried ice and for subsurface cold trapping.

Review of the Capacity to Accurately Detect the Temperature of Human Skin Tissue Using the Microwave Radiation Method.

Microwave radiometry (MWR) is instrumental in detecting thermal variations in skin tissue before anatomical changes occur, proving particularly beneficial in the early diagnosis of cancer and inflammation. This study concisely traces the evolution of microwave radiometers within the medical sector. By analyzing a plethora of pertinent studies and contrasting their strengths, weaknesses, and performance metrics, this research identifies the primary factors limiting temperature measurement accuracy. The review establishes the critical technologies necessary to overcome these limitations, examines the current state and prospective advancements of each technology, and proposes comprehensive implementation strategies. The discussion elucidates that the precise measurement of human surface and subcutaneous tissue temperatures using an MWR system is a complex challenge, necessitating an integration of antenna directionality for temperature measurement, radiometer error correction, hardware configuration, and the calibration and precision of a multilayer tissue forward and inversion method. This study delves into the pivotal technologies for non-invasive human tissue temperature monitoring in the microwave frequency range, offering an effective approach for the precise assessment of human epidermal and subcutaneous temperatures, and develops a non-contact microwave protocol for gauging subcutaneous tissue temperature distribution. It is anticipated that mass-produced measurement systems will deliver substantial economic and societal benefits.

Higher accuracy estimation of the weighted mean temperature (Tm) using GPT3 model with new grid coefficients over China

The weighted mean temperature (Tm) is an essential parameter in the field of Global Navigation Satellite System (GNSS) meteorology, as it enables the conversion of zenith wet delay to atmospheric precipitable water vapor (PWV). The existing Tm models, such as the GPT3 model, utilize the empirical annual and semi-annual amplitudes of Tm at grid points along with corresponding trigonometric functions to estimate Tm, making it difficult to provide a more detailed description of the daily variation of Tm. Therefore, the measured surface temperature and water vapor pressure were introduced to calculate the new series of grid coefficients using the least-square method, which enables the GPT3 model to estimate Tm with higher accuracy. In this process, the ERA5 reanalysis data derived from ECMWF from 2001 to 2010 was utilized to compute Tm values, and the new grid coefficient obtained by introducing only surface temperature was considered as scheme #1 and that achieved by introducing both surface temperature and surface water vapor pressure was regarded as scheme #2. The Tm data of 2023 calculated both by the radiosonde and ERA5 reanalysis data were utilized to assess the new grid coefficients for Tm estimation, and the results show that the grid coefficients based on these two surface parameters outperformed those only using the temperature. In the compassion using the ERA5 data, the bias/MAE/RMSE with the two types of new grid coefficients are −0.09/1.89/2.41 K and − 0.07/1.82/2.31 K, respectively, and the improvements reach to 50%/32.5%/34.2% and 61.1%/35%/36.9% compared with GPT3 model. In the comparison with radiosonde data, the scheme #1 and #2 performed a 0.55 K(13.8%) and 0.68 K(17.1%) improvement in the mean RMSE of stations compared with the GPT3 model. Note that the proposed two schemes can effectively improve the accuracy of estimating Tm in the comparison of regions, epochs and seasons with the Bevis and GPT3 model. Furthermore, the impact of Tm on PWV can be improved by the proposed two schemes, which was demonstrated using the theoretical RMSE and relative error of PWV.

Temperature imaging inside fluid devices using a ratiometric near infrared (NIR-II/III) fluorescent Y2O3: Nd3+, Yb3+, Er3+ nanothermometer

Luminescence thermometry is a non-contact method that can measure surface temperatures and the temperature of the area where the fluorescent probe is located, allowing temperature distribution visualizations with a camera. Ratiometric fluorescence thermometry, which uses the intensity ratio of fluorescence peaks at two wavelengths with different fluorescence intensity dependencies, is an excellent method for visualizing temperature distributions independent of the fluorophore spatial concentration, excitation light intensity and absolute fluorescence intensity. Herein, Nd3+/Yb3+/Er3+-doped Y2O3 nanomaterials with a diameter of 200 nm were prepared as phosphors for temperature distribution measurement of fluids at different temperatures. The advantages of this designed fluorescent material include non-aggregation in water and the fact that its near-infrared (NIR) fluorescence excitation (808 nm) is not absorbed by water, thereby minimizing sample heating upon irradiation. Under optical excitation at 808 nm, the ratio of the fluorescence intensities of Yb3+ (IYb; 975 nm) and Er3+ (IEr; 1550 nm), which exhibited different temperature responses, indicated the temperature distribution inside the fluid device. Thus, this technique using Nd3+/Yb3+/Er3+-doped Y2O3 is expected to be applied for temperature distribution mapping analysis inside fluidic devices as a ratiometric NIR fluorescence thermometer, which is unaffected by laser-induced heating.Graphical abstract