Thermogravimetric AnalysisTGA is widely used in the fields of material thermal stability, decomposition kinetics, and composition analysis by measuring the changes in sample mass with temperature or time. However, improper operation during the experimental process can easily lead to data bias (such as baseline drift, peak distortion, or poor repeatability). The following key techniques for improving data accuracy are shared from three dimensions: temperature control, sample processing, and instrument calibration.
1、 Precise control of heating rate: avoiding thermal hysteresis effect
Background of the problem:
A too fast heating rate can cause an increase in the internal temperature gradient of the sample, with thermal conduction lagging behind the programmed heating, resulting in the actual decomposition temperature being higher than the instrument display value, causing a peak temperature shift in the TG curve (such as a polymer decomposition peak temperature error of 10-20 ℃).
Optimization strategy:
Segmented setting of heating program:
Low temperature range (<300 ℃): Use a slower rate (5-10 ℃/min) to ensure uniform heating of the sample and reduce sudden release of moisture or volatile components.
High temperature range (>300 ℃): Adjust the rate according to the degree of reaction intensity (such as 10-20 ℃/min) to balance experimental efficiency and data accuracy.
Example: When analyzing the positive electrode material of lithium-ion batteries (such as LiCoO ₂), the low temperature range (50-300 ℃) is heated at 5 ℃/min, and the high temperature range (300-800 ℃) is heated at 15 ℃/min, which can clearly distinguish the stages of structural water removal and oxygen release.
Using thin layer samples:
Spread the sample into a uniform thin layer (thickness ≤ 0.5mm) to reduce thermal conductivity resistance and synchronize the sample temperature with the furnace temperature.
Avoid stacking particles to prevent local overheating or retention of reactive gases.
Compare blank experiments:
Run an empty crucible experiment under the same conditions, deduct the mass change caused by the instrument's own heat capacity (such as crucible oxidation weight gain), and correct the baseline drift.
2、 Optimize sample processing: reduce mass and heat transfer interference
Background of the problem:
Excessive sample size, uneven particle size, or improper loading method can hinder the diffusion of reaction gases or cause uneven heating, leading to TG curve distortion (such as broadening of peak shape and appearance of shoulder peaks).
Optimization strategy:
Control sample size:
Routine experiment: The sample quality is controlled at 5-20mg, ensuring that the quality change signal (Δ m) is higher than the instrument noise level (usually ≥ 0.1 μ g).
Microanalysis: Use a micro crucible (such as 50 μ L volume) to reduce the sample size to 1-2mg, suitable for valuable samples or highly active substances (such as nanocatalysts).
Example: When analyzing the thermal stability of metal organic framework materials (MOFs), a 10mg sample can clearly show two stages of adsorption water removal (100-200 ℃) and ligand decomposition (300-500 ℃), while a 50mg sample exhibits a peak temperature lag of 15 ℃ due to limited mass transfer.
Unified particle size distribution:
Concentrate the sample particle size between 50-200 mesh (75-300 μ m) through grinding or sieving to avoid incomplete internal reactions of large particles or agglomeration of small particles.
For porous materials such as activated carbon, they need to be pre dried to eliminate the interference of adsorbed gases in the pores.
Standardized loading method:
Use specialized tools (such as spoons or brushes) to evenly spread the sample at the bottom of the crucible, avoiding accumulation at the edges or center.
Lightly tap the crucible to compact the sample, but do not over compact it to prevent hindering gas diffusion.
3、 Strict instrument calibration and maintenance: ensuring baseline stability
Background of the problem:
Uncalibrated balance, temperature sensor deviation, or air path contamination can cause baseline drift and distorted mass readings, directly affecting the accuracy of the starting and ending points of the TG curve.
Optimization strategy:
Daily calibration of balance:
Use standard weights (such as 10mg, 50mg) for two-point calibration to ensure a mass measurement error of ≤± 0.1%.
Regularly clean the balance sensor (such as wiping with a dust-free cloth) to avoid dust accumulation affecting sensitivity.
Regularly calibrate temperature sensors:
Compare the furnace temperature with the displayed value using a standard thermometer (such as a platinum resistance thermometer), and recalibrate if the deviation exceeds ± 1 ℃.
For high-temperature experiments (>800 ℃), it is necessary to check whether the thermocouple protective sleeve is oxidized or cracked to prevent temperature measurement distortion.
Maintain the pneumatic system:
Gas purity: Use high-purity inert gases (such as N ₂ ≥ 99.999%) or reactive gases (such as O ₂ ≥ 99.5%) to avoid impurities from participating in the reaction or adsorbing on the sample.
Gas path cleaning: Regularly replace gas filters (such as molecular sieves adsorbing moisture), clean gas path pipelines (such as using ethanol ultrasonic treatment), and prevent blockage or contamination.
Flow control: Use a mass flow meter (MFC) to accurately adjust the gas flow rate (such as 20-100mL/min) to ensure a stable reaction atmosphere.
Clean the sample compartment:
After the experiment, clean the residue in the sample chamber with a soft bristled brush to avoid cross contamination.
For corrosive samples (such as sulfur-containing compounds), it is necessary to wipe the cabin with alcohol swabs, ventilate and dry it before conducting the next experiment.
Summary: Closed loop management for improving data accuracy
Through precise temperature control (reducing thermal hysteresis), sample optimization (reducing mass transfer interference), and strict calibration (ensuring baseline stability), the repeatability and reliability of TGA experiments can be significantly improved. In practical applications, it is recommended to combine blank experiments, standard substance comparisons (such as calibrating the decomposition temperature of polystyrene), and multi person reviews to form a closed-loop quality control system, providing reliable data support for material research and quality control.