In materials chemistry experiments, various physical properties are measured for synthesized materials and commercially available materials, including thermal properties, mechanical properties, electrical properties, optical properties, water absorption, film thickness, density, and viscosity.
However, physical-property measurement data often contain many numerical values, making it difficult to decide how to organize the results in a report and how to connect them to the discussion.
In the discussion of a materials chemistry experiment, it is not sufficient simply to write that “measurement values were obtained,” “a graph was created,” or “the values differed from literature values.”
It is necessary to organize what property of the material the measurement values represent, how the structure and composition are related to the physical properties, what causes the errors and variations, and which results are important in relation to the purpose of the experiment.
This article clearly explains how to organize physical-property measurement data obtained in materials chemistry experiments into a report, including how to organize results, create tables and graphs, compare with literature values, identify sources of error, structure the discussion, and use appropriate expressions in reports.
Note:
This article is a reference intended to assist with discussions of physical-property measurement data obtained in materials chemistry experiments, polymer chemistry experiments, and physical chemistry experiments at universities and similar institutions.
For the actual measurement methods, analytical equations, instrument conditions, units, literature values, and evaluation criteria, always follow the instructions in your university’s laboratory manual and those given by your instructor or TA.
- What Is Evaluated in a Materials Chemistry Experiment?
- Main Items to Include in the Results
- How to Organize Physical-Property Measurement Data in a Table
- How to Think About Graphing the Data
- How to Write About Average Values and Variation
- Handling Significant Figures and Units
- Comparison With Literature and Theoretical Values
- Discussing the Relationship Between Structure and Physical Properties
- Discussing the Relationship Between Preparation Conditions and Physical Properties
- How to Organize Data on Thermal Properties
- How to Organize Data on Mechanical Properties
- How to Organize Data on Electrical Properties
- How to Organize Data on Optical Properties
- How to Organize Data on Water Absorption and Swelling
- How to Organize Data on Film Thickness and Surface Condition
- Discussion of Approximation Lines and Correlation Coefficients
- How to Handle Outliers
- Basic Approach to Considering Sources of Error
- Sample-Derived Sources of Error
- Sources of Error From Measurement Conditions
- Instrument-Derived Sources of Error
- Sources of Error in Data Analysis
- Order for Writing the Discussion
- Difference Between a Superficial Discussion and a Good Discussion
- Examples of Discussion Expressions That Can Be Used in Reports
- How to Write Points for Improvement
- Points to Check in a Materials Chemistry Experiment Report
- Summary
What Is Evaluated in a Materials Chemistry Experiment?
In materials chemistry experiments, the relationship between material structure and physical properties is investigated through material synthesis, processing, film formation, heat treatment, and measurement.
Physical properties refer to the characteristics exhibited by a material, including hardness, ease of deformation, thermal stability, electrical conductivity, light absorption, and water absorption.
A characteristic of materials chemistry is that it considers not only how to make a substance, but also “what properties are exhibited when it is prepared under particular conditions.”
Therefore, in a report, it is important not merely to list measurement values but to discuss them by relating the preparation conditions, material structure, and measurement results.
Example Discussion:
In materials chemistry experiments, the physical properties of materials are measured and evaluated in relation to the material structure and preparation conditions.
The physical-property values obtained in this experiment are considered to have been affected by factors such as molecular structure, crystallinity, film thickness, water content, additives, and thermal history within the material.
Therefore, the measurement values must not be treated independently but should be discussed in relation to the state of the material.
Main Items to Include in the Results
In the results section of a materials chemistry experiment, organize the sample name, preparation conditions, measurement conditions, measured values, average values, variation, graphs, and comparison with literature values.
In physical-property measurements, even the same material often gives different values depending on the measurement conditions, so it is important to clearly state conditions such as temperature, humidity, sample dimensions, measurement speed, measurement wavelength, and distance between electrodes.
Main Items to Include in the Results
- Sample name
- Sample preparation conditions
- Sample pretreatment conditions
- Measurement method
- Instrument used
- Measurement temperature
- Measurement humidity
- Number of measurements
- Measured values
- Average value
- Standard deviation or variation
- Units
- Graphs
- Approximation line and correlation coefficient
- Literature values and theoretical values
- Difference between measured and literature values
- Sources of error
- Points for improvement
Example of How to Write the Results:
The physical properties of samples prepared under different conditions were measured, and the obtained values were summarized in a table.
For samples measured multiple times, the average value was calculated and the variation was also checked.
In addition, the relationship between the preparation conditions and the physical-property values was graphed, and trends associated with changes in the conditions were compared.
How to Organize Physical-Property Measurement Data in a Table
Physical-property measurement data become easier to discuss when first organized in a table.
The table should include the sample name, preparation conditions, measurement conditions, measured values, and units.
When measurements are performed multiple times, showing each measured value, the average value, and the standard deviation separately makes it possible to evaluate reproducibility and variation.
Units must always be clearly stated when creating a table.
For example, MPa is used for stress, S/m or S/cm for electrical conductivity, nm or µm for film thickness, dimensionless values for absorbance, and °C or K for temperature.
A table without units makes the meaning of the physical-property values unclear.
Example of Table Writing That Leads to Discussion:
Summarizing the physical-property values of each sample in a table makes it easier to compare differences caused by preparation conditions.
In particular, showing not only average values but also the variation in measured values makes it possible to confirm the degree of material inhomogeneity and measurement error.
When comparing physical-property values, it is important to standardize the units and measurement conditions.
How to Think About Graphing the Data
In materials chemistry experiments, graphing measured values makes trends easier to see.
As a basic rule, the changed condition is placed on the horizontal axis and the measured physical-property value on the vertical axis.
Examples include concentration versus absorbance, temperature versus viscosity, crosslinker concentration versus swelling ratio, film thickness versus transmittance, and doping time versus electrical conductivity.
Graphs should appropriately show axis labels, units, plotted points, approximation lines, and legends.
It is important not merely to include a graph, but to connect it to the discussion by considering “what trend is present,” “whether the relationship is linear,” “where the data deviate,” and “what caused the deviation.”
Example Discussion:
When the preparation conditions were plotted on the horizontal axis and the physical-property values on the vertical axis, the physical-property values changed with a certain trend as the conditions changed.
This suggests that the physical properties of the material depend on the preparation conditions.
On the other hand, possible reasons why some points deviated from the approximation line include sample inhomogeneity, measurement error, and differences in pretreatment conditions.
How to Write About Average Values and Variation
In physical-property measurements, it is important not to draw conclusions from only one measured value, but to perform multiple measurements and calculate an average value.
Material samples are often inhomogeneous, and even within the same sample, values may differ depending on the measurement position or measurement direction.
Therefore, showing both the average value and variation makes it possible to evaluate the reliability of the results.
Variation may be shown using standard deviation, maximum and minimum values, or error bars.
If the variation is large, not only measurement error but also inhomogeneity of the sample itself becomes a subject for discussion.
Example Discussion:
Because variation was observed in the measured values, the sample may not have been completely uniform.
In materials chemistry experiments, film thickness, surface condition, crystallinity, and water content may differ depending on the position, causing differences in measured values.
Therefore, it is necessary to evaluate the reproducibility of the results by showing not only the average value but also the standard deviation or measurement range.
Handling Significant Figures and Units
When summarizing physical-property measurement data in a report, attention must be paid to significant figures and units.
Writing values to more decimal places than the resolution of the measuring instrument makes the results appear more precise than they actually are.
Conversely, rounding too much may make differences among samples difficult to see.
Units must always be clearly stated in tables and on graph axes.
The same type of data should also use consistent units.
For example, comparing film thickness values when nm and µm are mixed may cause reading errors and calculation mistakes.
Example Discussion:
When comparing physical-property values, it is important to standardize significant figures and units.
Presenting values with more digits than the precision of the measuring instrument may overstate the reliability of the results.
In addition, if the units are not standardized, misunderstandings may occur when comparing samples or comparing the measured values with literature values.
Comparison With Literature and Theoretical Values
In materials chemistry experiments, measured values may be compared with literature or theoretical values.
If the measured values are close to the literature values, the measurement and sample preparation can be considered generally appropriate.
On the other hand, if the values differ from literature values, differences in sample purity, preparation conditions, measurement conditions, instrument calibration, and sample state are considered.
For polymers and composite materials, complete agreement with literature values is not unusual.
This is because physical properties are affected by molecular weight, crystallinity, additives, water content, thermal history, film thickness, measurement temperature, and other factors.
When values differ from literature values, they should not immediately be judged “incorrect”; instead, differences in conditions should be organized and discussed.
Example Discussion:
Possible reasons the measured value differed from the literature value include differences in sample preparation and measurement conditions.
Because material properties are affected by molecular weight, crystallinity, additives, water content, thermal history, and other factors, even materials having the same name do not necessarily show exactly the same values.
Therefore, when comparing with literature values, it is necessary to check not only the difference in values but also the differences in conditions.
Discussing the Relationship Between Structure and Physical Properties
The most important point in the discussion of a materials chemistry experiment is to connect the material structure with its physical properties.
For example, highly crystalline materials may have greater strength or higher melting points, while gels with higher crosslink densities may have lower swelling ratios.
In conductive polymers, doping may increase the carrier concentration and raise electrical conductivity.
When explaining changes in physical-property values, explain “why the property changed” in terms of molecular structure, microstructure, composition, and preparation conditions.
This produces a discussion characteristic of materials chemistry rather than a simple listing of results.
Example Discussion:
One possible reason sample A had a higher elastic modulus than sample B is that sample A had greater crystallinity or stronger intermolecular interactions.
When molecular chains are regularly arranged or intermolecular interactions are strong, the material becomes more resistant to deformation under external force, resulting in a higher elastic modulus.
In this way, differences in physical-property values must be discussed in relation to the internal structure of the material.
Discussing the Relationship Between Preparation Conditions and Physical Properties
Material properties are greatly affected by preparation conditions.
Even for the same material, changes in drying temperature, heat-treatment time, solution concentration, cooling rate, crosslinker concentration, doping time, film thickness, and other conditions may change the physical properties.
Therefore, the discussion should clearly identify “which conditions affected the physical properties.”
The relationship between preparation conditions and physical-property values can be shown clearly by comparing the values in tables or graphs for each condition.
If a trend is observed, that trend should be connected to changes in the material structure.
Example Discussion:
Because the physical-property values changed as the heat-treatment temperature increased, the internal structure of the material is considered to have changed as a result of heat treatment.
For example, if crystallization proceeds during heat treatment, thermal and mechanical properties related to elastic modulus and melting point may change.
Therefore, differences in preparation conditions are considered to have affected the physical properties through changes in the microstructure of the material.
How to Organize Data on Thermal Properties
Thermal properties include melting point, glass-transition temperature, crystallization temperature, thermal-decomposition temperature, heat of fusion, and degree of crystallinity.
For data obtained by DSC and TGA, peak temperature, onset temperature, peak area, mass-loss percentage, and similar values are organized.
In thermal analysis, the thermal history of the sample and the heating rate affect the results, so the measurement conditions must always be stated.
In the discussion, Tg is related to molecular-chain motion in the amorphous region, Tm to melting of crystalline regions, and TGA mass loss to evaporation of water or solvent and thermal decomposition.
Peak size and shape can also provide clues for considering crystallinity and sample uniformity.
Example Discussion:
Because an endothermic peak was observed in the DSC measurement, the crystalline regions in the sample are considered to have melted.
In addition, the step in the baseline is considered to correspond to the glass transition of the amorphous region.
Possible reasons the measured values differed from literature values include the thermal history of the sample, heating rate, degree of crystallinity, and presence or absence of additives.
How to Organize Data on Mechanical Properties
Mechanical properties include tensile strength, elastic modulus, elongation at break, hardness, and toughness.
In tensile testing, a stress-strain curve is created from load and elongation, and the elastic modulus is determined from the initial slope, tensile strength from the maximum stress, and elongation at break from the strain at failure.
Mechanical properties are affected by film thickness, specimen shape, cutting direction, molecular orientation, crystallinity, plasticizers, water content, and tensile speed.
In a report, not only numerical values but also fracture position, fracture surface, whitening, and the presence or absence of necking can be used in the discussion.
Example Discussion:
A sample with a high elastic modulus in the tensile test requires a large stress for initial deformation and is therefore considered to be a hard material.
On the other hand, a sample with a large elongation at break may have been able to undergo large deformation while the molecular chains oriented in the tensile direction.
Possible reasons for variation in the measured values include uneven film thickness, scratches at the edges of the test specimen, and differences in fracture position.
How to Organize Data on Electrical Properties
Electrical properties include resistance, resistivity, electrical conductivity, sheet resistance, and dielectric constant.
When determining electrical conductivity, not only the resistance value but also the sample length, cross-sectional area, film thickness, and distance between electrodes are taken into account.
In thin films and conductive polymers, contact resistance with the electrodes and film uniformity greatly affect the results.
In the discussion, changes in electrical conductivity are related to carrier concentration, doping state, film continuity, contact between particles, water content, and temperature.
Because the two-terminal method includes contact resistance, the measured value may be shifted toward a higher resistance than the actual value.
Example Discussion:
The increase in electrical conductivity after doping is considered to have resulted from an increase in the concentration of charge carriers within the material.
However, the measured resistance value may also include the effects of electrode contact resistance and uneven film thickness.
Therefore, when evaluating electrical conductivity, it is necessary to consider not only the electronic state of the material but also the sample geometry and measurement method.
How to Organize Data on Optical Properties
Optical properties include absorbance, transmittance, reflectance, emission intensity, wavelength, and band gap.
In UV-Vis measurements, the positions of absorption peaks, the magnitude of absorbance, and changes in transmittance are organized.
For thin-film samples, film thickness, surface roughness, cloudiness, and scattering affect the optical data.
In the discussion, changes in absorption peaks are related to electronic states, conjugation length, concentration, complex formation, particle size, and similar factors.
If the transmittance is low, not only material absorption but also the effects of film thickness and scattering must be considered.
Example Discussion:
Possible reasons for the decrease in sample transmittance include an increase in film thickness and light scattering caused by surface roughness.
In addition, if the position of the absorption peak changed, the electronic state or intermolecular interactions of the material may have changed.
When discussing optical properties, it is necessary to distinguish the intrinsic absorption of the material from the effects of film thickness, scattering, and cloudiness.
How to Organize Data on Water Absorption and Swelling
In experiments on water absorption and swelling, dry mass, mass after water absorption, amount of absorbed water, swelling ratio, and water content are organized.
In gels and water-absorbing polymers, crosslink density, hydrophilic functional groups, pH, salt concentration, water-absorption time, and drying conditions affect the results.
In the discussion, a large amount of water absorption is related to hydrophilic functional groups and network structure.
In addition, because the method used to remove surface water after water absorption and the drying state affect the measured values, operational errors are also considered.
Example Discussion:
In the sample with a high swelling ratio, hydrophilic functional groups are considered to have interacted with water molecules, allowing a large amount of water to be retained inside the gel.
On the other hand, in samples with a high crosslink density, the network structure is less able to expand and the swelling ratio may decrease.
In addition, if the method used to remove surface water after water absorption is not consistent, an error occurs in the mass after water absorption.
How to Organize Data on Film Thickness and Surface Condition
For thin-film materials, organize film thickness, variation in film thickness, surface roughness, transparency, pinholes, cracks, peeling, and other features.
Film thickness affects the optical, electrical, and mechanical properties of a material and is therefore important as a prerequisite for physical-property measurements.
If the film thickness is nonuniform, the measured values may differ depending on the location.
For example, electrical conductivity, transmittance, absorbance, and tensile strength are affected by film thickness and surface condition.
It is desirable to measure film thickness at multiple locations and show the average value and variation.
Example Discussion:
Because variation was observed in the film thickness, the thin film was considered not to be completely uniform.
If the film thickness is uneven, optical transmittance, electrical resistance, and mechanical strength may vary depending on the measurement location.
Therefore, when comparing the physical properties of thin-film samples, film thickness and surface condition must be evaluated at the same time.
Discussion of Approximation Lines and Correlation Coefficients
When physical-property measurement data are graphed, a linear relationship may be expected.
Examples include calibration curves, concentration versus absorbance, time versus mass change, and reciprocal temperature versus logarithmic values.
When drawing an approximation line, showing the slope, intercept, and correlation coefficient makes it easier to explain the trend in the data.
If the correlation coefficient is high, the measured values are considered to follow a linear relationship well.
On the other hand, if the correlation coefficient is low or some points deviate from the line, possible explanations include measurement error, inconsistent conditions, sample inhomogeneity, or an inappropriate linear model.
Example Discussion:
Because the measured values generally followed the approximation line, a linear relationship is considered to exist between the physical-property value and the variable within the range of experimental conditions.
On the other hand, possible reasons some points deviated from the line include errors in sample preparation, changes in temperature during measurement, and sample inhomogeneity.
If the correlation coefficient is low, it is also necessary to consider whether a linear approximation is appropriate.
How to Handle Outliers
Some measured data may contain values that differ greatly from the others.
When an outlier appears, its cause should first be considered rather than immediately deleting it.
Possible causes include defects in the sample, differences in measurement location, instrument reading errors, bubbles, contamination, insufficient drying, and poor electrical contact.
If an outlier is excluded, the reason for excluding it must be clearly stated.
It should not be removed simply because it is inconvenient, but only when a clear abnormality in the experimental procedure has been confirmed.
Comparing results with and without the outlier is also one possible approach.
Example Discussion:
Possible reasons one measured value differed greatly from the others include a defect on the sample surface or a difference in measurement location.
When handling an outlier, it should not be excluded simply because it differs from the average value; abnormalities during measurement and the state of the sample must first be checked.
If a clear operational error can be confirmed, it is desirable to exclude the value from the analysis after stating the reason.
Basic Approach to Considering Sources of Error
Sources of error in materials chemistry experiments can broadly be divided into sample-derived errors, measurement-operation errors, instrument-derived errors, and analytical errors.
Sample-derived errors include uneven film thickness, nonuniform composition, insufficient drying, defects, impurities, and differences in thermal history.
Measurement-operation errors include dimensional measurements, temperature control, time measurements, electrode contact, and sample fixing.
When writing about sources of error, do not simply write “human error occurred,” but specifically state which operation affected which value and in what way.
For example, explaining the direction of the error, such as “overestimating the film thickness causes the calculated stress to become smaller,” leads to a better discussion.
Example Discussion:
Uneven film thickness is one possible source of error in the measured values.
If the film thickness is not uniform, the physical-property values vary depending on the measurement location, increasing the variation in the average value.
In addition, if the film thickness is overestimated, calculations of stress and electrical conductivity using the cross-sectional area are affected, potentially causing the physical-property values to be underestimated or overestimated.
Sample-Derived Sources of Error
Even if material samples appear identical, their internal structure and surface condition may not be uniform.
Uneven film thickness, bubbles, cracks, pinholes, particle aggregation, differences in crystallinity, differences in water content, and uneven distribution of additives may affect physical-property measurements.
In thin films, gels, powders, and composite materials in particular, sample inhomogeneity can be a major source of error.
If the variation in the measured results is large, not only the measurement procedure but also the sample-preparation conditions must be reviewed.
Example Discussion:
The large variation in the physical-property values may have been caused by inhomogeneity within the sample.
If uneven film thickness or pinholes are present in a thin film, the optical and electrical properties vary depending on the measurement location.
In addition, in gels and composite materials, local differences in composition and water content may cause differences in physical properties even within the same sample.
Sources of Error From Measurement Conditions
In physical-property measurements, measurement conditions such as temperature, humidity, measurement speed, measurement time, optical path length, electrode spacing, and load conditions affect the results.
Polymers and gels in particular readily change their properties with temperature and humidity, so it is important to standardize the measurement environment.
If the measurement conditions are not consistent, it becomes difficult to determine whether differences in physical properties are caused by differences among samples or differences in the measurement conditions.
In a report, the measurement conditions should be clearly stated, and the effects of differences in those conditions on the results should be discussed.
Example Discussion:
Possible reasons the measured values differed from literature values include differences in measurement temperature and humidity.
In polymer materials, an increase in temperature may increase molecular-chain mobility and change the elastic modulus or viscosity.
In addition, in hygroscopic materials, water content changes with humidity and may affect mechanical and electrical properties.
Instrument-Derived Sources of Error
Measuring instruments also have sources of error.
Insufficient calibration, zero-point shifts, unstable baselines, sensor resolution, noise, and poor contact between the sample and instrument can affect the measured values.
For example, baseline stability is important in DSC, load-cell calibration in tensile testing, and electrode contact in electrical-conductivity measurements.
Effective measures for reducing instrument-derived errors include calibration using a standard sample, blank measurements, checking the zero point of the instrument, and allowing sufficient stabilization time before measurement.
Example Discussion:
Possible causes of a systematic shift in the measured values include insufficient instrument calibration or a zero-point shift.
If the instrument reference is shifted, all measured values may be biased in the same direction.
Therefore, checking the state of the instrument using standard samples and blank measurements is important for reliable physical-property measurements.
Sources of Error in Data Analysis
Analytical errors include mistakes in reading graphs, selection of the approximation range, baseline correction, unit-conversion mistakes, handling of significant figures, and incorrect use of equations outside their valid range.
In materials chemistry experiments, physical-property values are often obtained through calculations or extrapolation rather than directly using measured values, so the analysis method has a large influence on the result.
For example, the elastic modulus changes depending on which range of the stress-strain curve is treated as the initial linear region.
Tg changes depending on where the baseline is read.
Intrinsic viscosity may change depending on the concentration range used for extrapolation.
Example Discussion:
One possible cause of error in the analyzed value is the selection of the approximation range.
For example, if the range used to determine the elastic modulus includes a region that deviates from the initial linear portion, the calculated slope will differ from the actual value.
In thermal analysis, Tg and peak area also change depending on the baseline-correction method, so the analysis conditions must be clearly defined.
Order for Writing the Discussion
A materials chemistry discussion becomes easier to understand when written in a fixed order.
First, explain the major trend in the obtained results.
Next, explain how that trend can be understood from the material structure or preparation conditions.
Then discuss differences from literature or theoretical values, sources of error, and points for improvement.
Basic Structure of the Discussion
- Describe the trend in the measurement results
- Relate it to the material structure and preparation conditions
- Compare it with literature and theoretical values
- Consider the causes of deviations and variation
- Write points for improvement
- Summarize what was learned in relation to the purpose of the experiment
Example Flow of a Discussion:
In this experiment, the physical-property value tended to increase as the treatment temperature increased.
This is considered to have resulted from changes in the internal structure of the material, such as crystallization or densification caused by heat treatment.
However, there was a difference from the literature value, and possible causes include the thermal history of the sample, measurement temperature, and uneven film thickness.
For more accurate evaluation, the sample-preparation conditions must be standardized and multiple measurements performed to confirm the average value and variation.
Difference Between a Superficial Discussion and a Good Discussion
In materials chemistry experiments, simply listing numerical values does not constitute a discussion.
In a good discussion, the meaning of the measured values, material structure, preparation conditions, and sources of error are connected.
Rather than ending with “it differed from the literature value,” explain why it differed based on the conditions and sample state.
| Superficial Discussion | Good Discussion |
|---|---|
| The physical-property value was high. | Possible reasons the physical-property value was high include greater crystallinity or stronger intermolecular interactions in the material, which may have made the structure more stable against external stimuli. |
| It differed from the literature value. | The difference from the literature value may have been caused by differences in sample preparation conditions, molecular weight, additives, water content, measurement temperature, and instrument conditions. |
| The graph was not linear. | Possible reasons for deviation from the straight line include the measurement range exceeding the applicable range of the equation, sample inhomogeneity, and variation in measurement conditions. |
| There was an error. | Possible sources of error include film-thickness measurement, temperature control, sample-drying state, electrode contact, and baseline correction, each of which may have affected the calculation of the physical-property values. |
Examples of Discussion Expressions That Can Be Used in Reports
The following expressions can be used in materials chemistry experiment reports.
Adjust the necessary parts according to your own experimental results.
- The obtained physical-property values changed depending on the sample preparation conditions.
- This trend can be explained by structural changes within the material.
- The variation in measured values is considered to originate from sample inhomogeneity and errors in the measurement procedure.
- The difference from the literature value may have arisen from differences in measurement conditions or sample state.
- Measurement reproducibility can be evaluated by checking not only the average value but also the standard deviation.
- Points deviating from the approximation line may have been caused by errors in sample preparation or fluctuations in measurement conditions.
- Material properties are affected by molecular structure, crystallinity, orientation, water content, additives, and other factors.
- In thin-film samples, film thickness and surface condition greatly affect physical-property measurements.
- In polymer materials, temperature and humidity change molecular-chain mobility and therefore also change physical-property values.
- For more accurate evaluation, the measurement conditions must be standardized and reproducibility confirmed using multiple samples.
How to Write Points for Improvement
Points for improvement in materials chemistry experiments are easier to organize when divided into sample preparation, pretreatment, measurement, and analysis.
It is important that each improvement correspond to a specific source of error.
For example, if uneven film thickness is a source of error, possible improvements include measuring the film thickness at multiple locations, standardizing the preparation conditions, and keeping the substrate level.
Improvements to Sample Preparation
- Keep the sample preparation conditions constant
- Accurately standardize solution concentration and mixing conditions
- Standardize drying and heat-treatment conditions
- Make the film thickness and shape uniform
- Reduce bubbles, cracks, and pinholes
Improvements to Measurement
- Standardize the measurement temperature and humidity
- Check instrument calibration
- Standardize the measurement position and direction
- Perform multiple measurements and calculate the average value
- Check the sample condition before measurement
Improvements to Analysis
- Standardize units
- Handle significant figures appropriately
- Clearly define the approximation range
- Explain how outliers are handled
- When comparing with literature values, check differences in conditions
Example of How to Write Points for Improvement:
To improve the reliability of the measured values, the sample-preparation and measurement conditions must be standardized, and multiple measurements should be performed to confirm the average value and variation.
In addition, because uneven film thickness affects the physical-property values of thin-film samples, it is important to measure film thickness at multiple locations and record the measurement positions.
During analysis, units, significant figures, and approximation ranges should be clearly defined, and differences in measurement conditions should also be considered when comparing with literature values.
Points to Check in a Materials Chemistry Experiment Report
Checking the following points before writing the report makes the discussion easier to write.
- Are the sample name and preparation conditions clearly stated?
- Are the measurement method and measurement conditions stated?
- Are the units of the measured values standardized?
- Are the average value and variation shown?
- Are trends organized using tables and graphs?
- Is the meaning of the physical-property values explained?
- Are the physical properties related to the structure and preparation conditions?
- Are the results compared with literature or theoretical values?
- Are the causes of deviations and variation in the measured values described specifically?
- Do the sources of error correspond to the points for improvement?
- Is the handling of outliers explained?
- Is what was learned in relation to the purpose of the experiment summarized?
Summary
Materials chemistry experiments deal with various types of physical-property measurement data, including thermal properties, mechanical properties, electrical properties, optical properties, water absorption, and film thickness.
In a report, it is important to organize measured values in tables, graph them when necessary, and show average values, variation, and comparisons with literature values.
Clearly stating units, significant figures, and measurement conditions increases the reliability of the results.
In the discussion, the measured values should not simply be listed, but explained in relation to the material structure, preparation conditions, and measurement conditions.
Considering molecular structure, crystallinity, orientation, crosslinking, water content, additives, film thickness, thermal history, and similar factors as possible causes of changes in physical-property values produces a discussion characteristic of materials chemistry.
In addition, when measured values differ from literature values or show variation, sample inhomogeneity, measurement conditions, instrument calibration, and analytical methods should be considered separately.
In a materials chemistry experiment report, it is important to explain not only “what was measured,” but also “what the value means for the material” and “why that value was obtained.”
