Temperature Coefficient Research Articles

A Two-Stage Sub-Threshold Voltage Reference Generator Using Body Bias Curvature Compensation for Improved Temperature Coefficient

Leakage diodes cause deviations in the thermal drift of ultra-low-power two-transistor (2T) reference circuits, resulting in either convex or concave output voltages against temperature, depending on the reference transistor types (n-type/p-type). This paper investigates the combined application of the convexity and concavity properties exhibited by the output voltage of complementary 2T references, one n-type and one p-type. By exploiting the body bias effect, this approach mitigates variations in the output reference voltage caused by temperature fluctuations. Software optimization is also used to obtain the required aspect ratios after formulating the required criteria for drain-induced barrier lowering (DIBL) elimination in the first stage. The performance of the proposed reference is evaluated by post-layout Monte Carlo simulations. In the range of 0 °C to 100 °C, the output reference voltage has an average temperature coefficient (TC) of 26.7 ppm/°C without any temperature trim. The output reference voltage is 195.5 mV with a standard deviation of 13.6 mV. The line sensitivity (LS) is 17.1 ppm/V in the supply voltage range of 0.5 V to 2.1 V at 25 °C. At 25 °C and 0.5 V, the power consumption is 28.8 pW, increasing to a maximum of 1.3 nW at 100 °C and 2.1 V.

Experimental and data-driven chemical kinetic modeling study of alcohol-to-jet (ATJ) synthetic biofuel for sustainable aviation fuels

This work assesses the chemical ignition delay behavior of an isoparaffinic alcohol-to-jet (ATJ) fuel, one of the certified sustainable aviation fuels (SAFs). Chemical ignition delay measurements of ATJ were performed at a compressed pressure of PC = 2 MPa and three equivalence ratios (phi = 0.5, 1.0, & 1.3) in synthetic dry air, between 667 K and 1250 K. The unique chemical structures of isoalkanes result in high thermal decomposition rate, but low chemical oxidation reactivity. The new lumped mechanism (ARLMech-HC-ATJ) is developed using a genetic algorithm based on empirical ignition delays. The mechanism shows good performance over the temperature range from 667 K to 1250 K and varied equivalence ratios. Using the suggested mechanism, this study presents sensitivity analysis for the temperature range to understand chemical kinetics of ATJ fuel. The results show the impact of using ATJ modeling to design and optimize propulsion systems operating in the negative temperature coefficient (NTC) or low temperature chemistry (LTC) regime in the future and a methodology that can be adapted to other novel fuels.

Recovery of Ni-Co-Mn Oxides from End-of-Life Lithium-Ion Batteries for the Application of a Negative Temperature Coefficient Sensor

This study demonstrates the current advancements in battery management systems (BMSs), emphasizing the need for precise temperature monitoring within battery packs to enhance safety and performance through efficient thermal management. The increased demand for lithium-ion batteries (LIBs) has driven the development of temperature sensors with improved accuracy and stability. In particular, Ni-Co-Mn-based spinel oxides are commonly used due to their stable negative temperature coefficient (NTC) behavior. However, challenges arise in manufacturing due to the high cost and uncertain supply of critical cathode components (e.g., Co, Ni, and Mn) for LIBs. This research focuses on developing spinel-type (Ni0.6Co0.4Mn2)O4 using recycled Ni-Co-Mn oxides obtained from end-of-life (EOL) LIBs, demonstrating temperature resistance behavior suitable for temperature sensing. The oxides are prepared through hydrometallurgy, oxalate synthesis, and post-heat treatment. Successful integration into spinel-type NTC thermistors suggests broader applications in various industrial fields. A systematic investigation into the synthesis and characterization of recovered Ni-Co-Mn oxides from EOL LIB cathode materials (Li(Ni0.33Co0.33Mn0.33)O2) is presented for NTC thermistor application. Thermogravimetric analysis-derivative thermogravimetry (TGA-DTG) identifies the optimal post-heat treatment temperature. The X-ray diffraction (XRD) patterns confirm a cubic spinel structure of the Ni-Co-Mn oxides, supported by scanning electron microscope (SEM) images showing a uniform microstructure. Also, energy dispersive X-ray spectroscopy (EDS) mapping confirms homogeneous element distribution. Recovered oxide pellets from the sintering process exhibit a single spinel structure, with X-ray photoelectron spectroscopy (XPS) analysis revealing changes in the valence states for Ni and Mn. Resistivity measurements demonstrate semiconductive behavior, which shows a B value (3376.92 K) suitable for NTC thermistor applications. This study contributes valuable insights to black powder recycling from EOL LIBs and its potential in temperature-sensitive electronic devices.

Energy and exergy-based degree-hours in estimation of heat requirements for heating and cooling purposes

This study presents an innovative exergy-based methodology to revolutionize the assessment of heating and cooling energy utilization, transcending the limitations of traditional heating and cooling degree-hours (HDH and CDH) analyses. The study’s distinctiveness stems from its investigation into variations in HDH and CDH concerning critical parameters such as ambient temperature, solar-air temperature, solar absorptivity, surface emissivity, and total heat transfer coefficient. This fosters a profound comprehension of the thermodynamic performance of building heating and cooling systems, empowering decision-makers with the insights needed to optimize energy utilization effectively. As demonstrated through a case study conducted in Antalya, Turkey, this study uncovers significant findings. A mere 1 °C increase in ambient temperature results in an average 14 % surge in heating demand and an average 17 % decline in cooling demand, leading to a substantial 1000°-h discrepancy between heating and cooling requirements. Furthermore, we underscore the sensitivity of energy demand to temperature fluctuations, the substantial impact of design temperature on energy consumption, the notable influence of solar effects on environmental conditions, and the potential for optimization in parameters such as solar absorptivity, surface emissivity, and total heat transfer coefficient. These insights underscore the significance of exergy-based systems, offering heightened energy efficiency, swift adaptability to temperature changes, integration of renewable energy sources, and intelligent control features that contribute to sustainability and energy savings.

Deep Learning‐Assisted Sensitive 3C‐SiC Sensor for Long‐Term Monitoring of Physical Respiration

AbstractIn human life, respiration serves as a crucial physiological signal. Continuous real‐time respiration monitoring can provide valuable insights for the early detection and management of several respiratory diseases. High‐sensitivity, noninvasive, comfortable, and long‐term stable respiration devices are highly desirable. In spite of this, existing respiration sensors cannot provide continuous long‐term monitoring due to the erosion from moisture, fluctuations in body temperature, and many other environmental factors. This research developed a wearable thermal‐based respiration sensor made of cubic silicon carbide (3C‐SiC) using a microfabrication process. The results showed that as a result of the Joule heating effect in the robustness 3C‐SiC material, the sensor offered high sensitivity with the negative temperature coefficient of resistance of approximately 5,200ppmK‐1, an excellent response to respiration and long‐term stability monitoring. Furthermore, by incorporating a deep learning model, this fabricated sensor can develop advanced capabilities to distinguish between the four distinct breath patterns: slow, normal, fast, and deep breathing, and provide an impressive classification accuracy rate of ≈ 99.7%. The results of this research represent a significant step in developing wearable respiration sensors for personal healthcare systems.

Spatially Resolved High Voltage Kelvin Probe Force Microscopy: A Novel Avenue for Examining Electrical Phenomena at Nanoscale

AbstractKelvin probe force microscopy (KPFM) is a well‐established scanning probe technique, used to measure surface potential accurately; it has found extensive use in the study of a range of materials phenomena. In its conventional form, KPFM frustratingly precludes imaging samples or scenarios where large surface potential or surface potential gradients exist outside the typical ±10 V window. If the potential regime measurable via KPFM can be expanded, to enable precise and reliable metrology, through a high voltage KPFM (HV‐KPFM) adaptation, it can open up pathways toward a range of novel experiments, where the detection limit of regular KPFM has so far prevented the use of the technique. In this work, HV‐KPFM is realized and shown to be capable of measuring large surface potential and potential gradients with accuracy and precision. The technique is employed to study a range of materials (positive temperature coefficient of resistivity ceramics, charge storage fluoropolymers, and pyroelectrics) where accurate, spatially resolved mapping of surface potential within high voltage regime facilitates novel physical insight. The results demonstrate that HV‐KPFM can be used as an effective tool to fill in existing gaps in surface potential measurements while also opening routes for novel studies in materials physics.

Real Gas Effects in High-Pressure Ignition of n-Dodecane/Air Mixtures.

This work studies the real gas effects on the autoignition of hydrocarbon fuels under high pressures, using normal dodecane (n-dodecane) as the representative fuel and the Redlich-Kwong equation of state (EoS) as the real gas description. It is demonstrated that the real gas description yields a shorter ignition delay time (IDT) compared with the ideal gas description, especially in low-temperature regimes which could encompass the negative temperature coefficient (NTC) phenomena and has a stronger dependence on the molecular volume than the attractive potential. The study further shows that high pressure facilitates low-temperature reaction pathways, where the compressibility factors of key reactants contribute to real gas effects. Moreover, the results suggest that accounting for real gas behavior leads to an increase in the formation of polycyclic aromatic hydrocarbons (PAHs), which, in turn, promotes soot generation.

Effects and mechanism of thermal insulation materials on thermal runaway propagation in large-format pouch lithium-ion batteries

The large heat transfer area of large-format lithium-ion batteries primarily facilitates conduction heat, which is responsible for triggering the thermal runaway of adjacent cells. Therefore, the primary consideration is to utilize thermal insulation materials between cells in order to slow down or prevent the process of thermal runaway propagation. In this study, three varieties of thermal insulation materials were employed to insulate individual cells within a module comprising three large-format pouch cells. These materials include pre-oxygenated wire aerogel (AG-ST-POF), polymer-coated pre-oxygenated wire aerogel (PC-AG-ST-POF), and silicone (SI). The study experimentally examined the thermal runaway propagation (TRP) behavior of the battery module under conditions without insulation materials and with various types of insulation materials. The impact of thermal insulation materials on the TRP among cells was analyzed. The study revealed that none of the three materials completely suppressed the propagation of thermal runaway, although they did impede its progress. The overall impact of AG-ST-POF surpassed that of SI and PC-AG-ST-POF. Furthermore, the mechanism by which thermal insulation materials influence TRP was explored. The results of the thermophysical properties testing suggest that evaluating the impact of materials on TRP solely through thermal conductivity is not a reliable approach. Alternatively, the maximum service temperature and thermal diffusion coefficient are critical parameters for the selection of thermal insulation materials. This study can provide a valuable reference for process engineering design and application in the context of lithium-ion batteries, with the aim of mitigating the risk of TRP.

Examining the effects of sintering temperature on double perovskite La2NiTiO6: Analysis of structural, optical, electrical properties, and leakage current characteristics

This study explores the influence of varying sintering temperatures on the structural, optical, electrical, and leakage current features of La2NiTiO6 (LNTO), a double perovskite material synthesized through the citrate auto-ignition method. The X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray (EDX) analysis were employed to investigate the structure, microstructure, and compositional distribution of the samples. The samples sintered at various temperatures showed the monoclinic structure with space group P21/n and were confirmed by Rietveld's refinement of the XRD patterns. The average grain size increased with higher sintering temperatures, which is consistent with the particle size estimated from the histogram plot of the FE-SEM data. The UV–visible (UV–Vis) spectroscopy showed that the energy band gap decreased as sintering temperatures increased. Impedance spectroscopy analysis revealed non-Debye type relaxation of charge carriers and confirmed the negative temperature coefficient of resistance (NTCR) behavior. Electrical analysis affirmed that the direct current (DC) conductivity is thermally activated, following the Arrhenius equation with an inverse temperature dependency. As the sintering temperature increases, the leakage current density decreases, and the leakage current conforms to the ohmic conduction mechanism.

Temperature coefficient of resistance and thermal boundary conductance determination of ruthenium thin films by micro four-point probe

Accurate characterization of the temperature coefficient of resistance (α TCR) of electrically conductive materials is pertinent for reducing self-heating in electronic devices. In-situ non-destructive measurements of α TCR using the micro four-point probe (M4PP) technique have previously been demonstrated on platinum (Pt) thin films deposited on fused silica, assuming the thermal conductivity of the substrate as known. In this study, we expand the M4PP method to obtain the α TCR on industrially relevant stacks, comprising ruthenium (Ru) thin films (3.3 nm and 5.2 nm thick) deposited on bulk silicon (Si), separated by a 90 nm SiO2 spacer. The new M4PP methodology allows simultaneous determination of both α TCR and the total thermal boundary conductance (G TBC) between the metallic film and its substrate. We measured the α TCR and the G TBC to be 542 ± 18 ppm K−1 and 15.6 ± 1.3 MW m−2K−1 for 3.3 nm Ru, and 982 ± 46 ppm K−1 and 19.3 ± 2.3 MW m−2K−1 for 5.2 nm Ru. This is in good agreement with independent measurements of α TCR. Our methodology demonstrates the potential of M4PP to characterize thermal properties of metallic thin films used in semiconductor technology.

Determining energy, exergy and enviroeconomic analysis of stand-alone photovoltaic panel under harsh environment condition: Antarctica Horseshoe-Island cases

It is considered that some of the energy needs of the Turkish Science Base, which will be established on the Antarctic Horseshoe Island, will be supplied from solar energy. In this study, the performance of the PV panel was experimentally tested on the Antarctic Horseshoe Island. Energy, exergy and enviroeconomic analysis of the PV panel were performed. In the experiments carried out for three days, the energy efficiency was determined as 5.40%, 7.39% and 11.35%, respectively. The exergy efficiencies were calculated as 4.53%, 6.58% and 10.25%, respectively. At the end of three experiments, the amount of CO2 blocked to the atmosphere was determined as 3.06 kg on average. The study used meteorological parameters (solar radiation, wind speed, humidity, and ambient air temperature) and other data (current-voltage, panel surface temperature, convection and radiation heat transfer coefficients, sky temperature, total heat transfer coefficient, total heat loss and exergy destruction) that can only be calculated using these variables to estimate the electrical efficiency of the PV module. This was achieved using the multilayer perceptron and decision tree method. The process of approximating the values estimated by statistical evaluations to the values calculated experimentally for energy efficiency was found to have error rates of 5.6% and 12.5%, respectively.

Dielectric Analysis of Amine Modified Nano-graphite: Effects of Thickness, Temperature and Frequency

Amine modified nano-graphite (NH2-NG) has been produced from nanographite (NG) powder via liquor ammonia (NH3) aqueous solution by microwave, ultrasonic methods. The surface modified NG have been characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR) techniques which clearly demonstrate that synthesis of NH2-NG was successful. The crystalline characteristics of amine modified nanographite powder have been studied through XRD technique. The morphology structure of synthesized surface modified nanoparticles has been determined by SEM analysis. FTIR spectra confirmed the existence of amine groups on the surface of produced nano-graphite powder. NH2-NG pellet was prepared to analyse its dielectric properties as a function of thickness (1, 2, 3, 5 and 7 mm), frequency (range 10−2-105 Hz) and temperature (25, 50, 75 and 100 °C). As a function of frequency, the dielectric loss tangent and permittivity each exhibit a distinct relaxation peak that grows up to a thickness of 5 mm then decreasing. Because nanoparticles are capacitive, the capacitance values of NG and NH2-NG increase with thicknesses up to 5 mm and drop with frequency. The drop in dielectric permittivity of NG and NH2-NG pellets after 5 mm may be caused by an increase in resistivity. Positive temperature coefficient (PTC) of increased conductance is confirmed by the continuous increase in electrical conductivity of NG and NH2-NG with temperature. The degree of temperature has a significant impact on the dielectric loss tangent, dielectric permittivity, and electrical conductivity of NG, and NH2-NG.

SiO2 and Fe cation synergistically modify the LaMnO3 NTC thermistors with high stability

SiO2 insulator and Fe2O3 dopant was simultaneously used to modify the crystalline phase, morphology and electric properties of LaMnO3 ceramics. Results show that there are several merits after modification. On the one hand, the addition of SiO2 is demonstrated to have multifunction to the LaMn1-xFexO3 (0 ≤ x ≤ 0.5) (LMFO) ceramics. After adding SiO2, the surface of LMFO ceramics tend to be flat, the degree of densification increases, the porosity decreases, and the pores almost disappear. Meanwhile, the resistance drift rate of LaMnO3 with SiO2 is reduced and the aging stability is improved. In addition, the crystalline structure of LMFO ceramics transform from hexagonal perovskite phase (x ≤ 0.2) to cubic perovskite phase (x ≥ 0.25) along with the Fe-doping contents increase. Moreover, the grain size decreases and the grain boundaries increase with the increase of Fe content. X-ray photoelectron spectroscopy (XPS) spectra show that both the Mn4+/Mn3+ ratio and the oxygen vacancy concentration decrease with increasing Fe content. Resistivity ρ25°C raised from 2.84 Ω cm to 65.38 Ω cm, and material constant B25/50 increased from 139.36 K to 1751.78 K. Fe doping significantly improves the stability of LMFO ceramics, and the minimum value of resistance drift rate is 0.168 % after aging at 125 °C for 500 h. The above results confirm that the SiO2 modified LMFO ceramic is a high stability negative temperature coefficient (NTC) thermistor.

Temperature and Frequency Dependence of Conductivity, Density of States, and Dielectric Permittivity of Ternary Metal Chalcogenide PbSnSe2 flake

The mechanically cleaved flake of ternary metal chalcogenide PbSnSe2 was transferred onto the interdigitated electrodes to form electrical contacts. The temperature dependent (180 K – 250 K) electrical properties were then analyzed employing complex impedance spectroscopy from 2 kHz - 2MHz. A detailed analysis of Nyquist plots proposed the space charge dependent behavior and negative temperature coefficient of PbSnSe2 flake. The AC conductivity followed Jonscher’s power law with -parameter value being less than unity. The values of -parameter increased with rise in temperature suggesting the presence of non-overlapping small polaron tunneling (NSPT) in the PbSnSe2 flake. From this NSPT model, tunneling distance, hopping energy, and density of states (DOS) were estimated at temperatures from 180 K – 250 K. The dielectric permittivity showed dispersion at lower frequencies and the tangent loss was also found to be directly related to temperature. A single semicircular arc in complex modulus analysis showed the dominance of bulk effect in the material.

The study of BMN cubic pyrochlores based multi-layer capacitors

The multi-layer ceramic capacitor (MLCC) is prepared with Bi1.5MgNb1.5O7 (BMN) pyrochlores, which has medium dielectric constant, large dielectric tunability, and especially the very small dielectric loss. The multilayer ceramic capacitors with Bi1.5MgNb1.5O7 as the dielectric material are prepared by a tape-casting method. The dielectric constant of the BMN thick film was observed to be superior to that of the bulk material, indicating its potential application in electronic devices. The increase in dielectric constant during the preparation of multilayer ceramic capacitors was explained by investigating the interdiffusion between the ceramic thick films and the electrodes. The BMN thick films and Ag0.7/Pd0.3 electrodes showed a dense microstructure and serial interfaces when sintering at 1050 °C for 1.5 h. The capacitor exhibited good temperature stability with a dielectric constant temperature coefficient of −249.94 ppm/°C, a relative dielectric constant of 216, and a dielectric loss of 0.00036. Provides insights for the development and optimization of high-performance dielectric tunable electronic device.

Tuning εr and τf by the combined effects of rattling RE3+ and compressed Ca2+ at the A-site in microwave dielectric ceramics CaREAlO4 (RE = Eu, Ho, Er, Yb)

The well-densified CaREAlO4 (RE = Eu, Ho, Er, Yb) microwave dielectric ceramics with the K2NiF4 structure are fabricated at 1360 - 1500 °C. Crystal structures were investigated via XRD and HRTEM, and no phase transition occurred. The ceramics exhibit low εr of 17.9 - 19.3 and relatively high Q×f values of 25,110 - 48,310 GHz, and tunable τf values ranging from -1.1 ppm/°C to +18.4 ppm/°C and then to -20.4 ppm/°C. The variations in εr and τf were ascribed to the mutual effects of rattling RE3+ and compressed Ca2+ characterized by bond valence theory and temperature coefficient of ion polarizability (ταm). The Q×f values of CaREAlO4 ceramics positively correlate with structure stability and lattice energy, the main intrinsic factors affecting Q×f.

Analysis of the LatticeNet neural network framework’s performance using prediction-calculated temperature coefficients in PWR assemblies

Various Machine Learning (ML) techniques have seen recent and growing interest in the creation of surrogate neutronics models as a potential way to avoid the computational expenses associated with conventional high-fidelity modeling. Artificial Neural Networks (ANNs) have been shown to be particularly useful for single-assembly predictions involving pin-wise power distributions and multiplication factors. In this paper, the LatticeNet neural network framework is investigated as a method to predict Doppler and moderator temperature coefficients for Pressurized Water Reactor (PWR) fuel assemblies, as well as differential boron worth. This approach uses the built-in tools developed alongside LatticeNet to construct two fully-connected network architectures capable of predicting k-eigenvalues from two inputs such as fuel enrichment and temperature when trained with data generated with CASMO-4E. A single network taking in all study parameters as inputs was then used to predict k-eigenvalues for fuel temperature, moderator temperature, and boron perturbation cases. The calculated temperature coefficients and differential boron worth values were compared with a bank of reference values to validate the efficacy of this method. Overall, differences in k-eigenvalues were within 0.017% in the worst case. The temperature coefficients saw mean errors of 1.85% and 1.69% for the two-parameter networks, respectively. The all-parameter network was then shown to predict 1100 points in 236 ms compared to the 4.95 min CASMO-4E took to generate them. Additionally, the differential boron worth achieved the lowest mean error of 0.30%; each of these values were within our acceptance criteria.

Analysis of metal and zinc oxide semiconductor interface resistance using transmission line method

The transmission line method (TLM) is modified to analyze the contact resistance between the metal and zinc oxide semiconductor considering interface resistance. TCAD is used to simulate an ideal defect-less state and compare it with experimental result. It is found that the current transfer length can be overestimated in conventional TLM measurement. The importance of interface resistance is shown through interface trap and Schottky contact effect analysis: Resistance comparison between different metal used device, and the activation energy shift measurement after O2 pre-annealing. Based on these, the conventional resistance equation for TLM is corrected by separating channel resistance and non-ideal contact resistance. The mobility and temperature coefficient of resistance (TCR) of ZnO channel are extracted using the suggested method. This shows the importance of metal/semiconductor interface resistance in devices using semiconductor channel.

Flame soot absorption coefficient and temperature reconstruction through line-of-sight attenuation and light field imaging

The accuracy and efficiency of 3-D flame temperature field reconstruction using the light field imaging technique heavily depend on soot radiation characteristics. In this study, we employ the line-of-sight attenuation method to reconstruct the soot absorption coefficient distribution in a pure absorbing flame. Utilizing these soot absorption coefficients, the radiative transfer equation is effectively transformed within the framework of the light field imaging technique into a linear inverse problem and also outlines the flame boundary. This proposed strategy reduces the unwanted detection rays significantly, thus eliminating the extensive computational processing. Consequently, the proposed approach substantially enhances the accuracy and efficiency of flame temperature reconstruction. Numerical simulations were carried out on a bimodal asymmetric flame to validate the noise tolerance capabilities, investigate the effects of varying voxel numbers on flame division and carry out a comparative study. Experimental studies were also conducted to reconstruct flame temperature and soot absorption coefficient distributions under different combustion operating conditions. Thermocouple measurements were performed and compared with the reconstructed temperatures. Outcomes achieved from both numerical simulations and experimental studies demonstrate the feasibility, accuracy and robustness of the proposed method.

The Role of Climatic, Environmental and Socioeconomic Factors in the Natural Movement of Urban Populations in Kazakhstan, 2012-2020: An Analysis from a Middle-Income Country in Central Asia.

This study addresses the importance of identifying key characteristics influencing demographic indicators for urban populations, emphasizing the need to consider regional climatic features and ecological factors. The research utilized data from ten main regional cities across the Republic of Kazakhstan. This study involved a retrospective analysis based on secondary data from official sources spanning 2012-2020. We employed correlation analysis and multidimensional regression models. Noteworthy predictors for crude birth rate included the influence of effective temperature (β = 0.842, p < 0.0001), marriage rate (β = 0.780, p < 0.0001), Gini coefficient (β = -27.342, p = 0.020) and divorce rate (β = -2.060, p < 0.0001), with overall strong model performance (R2 = 0.940). The degree of atmospheric pollution (β = -0.949, p = 0.044), effective temperature (β = -0.294, p < 0.0001) and Gini coefficient (β = 19.923, p = 0.015) were the predictors for crude mortality rate, with a high model fit (R2 = 0.796). The study unveils significant relationships between demographic indicators (crude birth rate, mortality rate) and variables like effective temperature, marriage rate, divorce rate, Gini coefficient, physician density and others. This analysis of climatic, environmental, and socioeconomic factors influencing demographic indicators may help in promoting specific measures to address public health issues in Kazakhstan.