Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used to measure the vapor pressure and heat of vaporization of organic compounds. TGA was able to estimate the vapor pressure of naphthalene and anthracene to within 21% and 30% of literature values, respectively. DSC trials in non-sealed pans measured heats of sublimation within 5% of literature, while sealed pan trials did not reduce boiling points below literature values due to pressurization. Further development is needed to apply these methods to organic materials.
Duncan Gordon et al., Physica B, 385-386, (2006), 511 - 513.Duncan Gordon
This study used time-resolved small-angle neutron scattering (SANS) to examine the crystallization process of a blend of deuterated and hydrogenated poly(ethylene terephthalate) (PET) over a temperature range of 220–230°C. SANS was able to track the growth of crystallites over time by following the increase in intensity of a scattering peak at 0.04 Å−1. Crystallization half-lives measured by SANS were similar to those obtained using differential scanning calorimetry. Analysis using the Avrami model yielded mechanistic constants between 2-3, indicating spherulitic crystallite growth.
1. Dendrimer-encapsulated gold nanoparticles were used to catalyze the reduction of 4-nitrophenol to 4-aminophenol at 40°C.
2. Five reaction conditions were tested with varying concentrations of 4-nitrophenol. Rate constants for the reactions were calculated and it was expected that the rate would decrease with increasing 4-nitrophenol concentration.
3. However, the results showed that the rate constants actually increased as the 4-nitrophenol concentration increased, with the highest rate seen at the highest concentration tested of 4M 4-nitrophenol. This trend was unexpected and suggests possible errors in the experiment.
This document describes an experiment using bomb calorimetry to measure the enthalpy of combustion of 1,2-diphenylethane. Bomb calorimetry works by igniting a substance in an insulated chamber and measuring the temperature change, from which the energy released can be calculated. The experiment used benzoic acid to first calibrate the bomb calorimeter and verify its functioning. Then, 1,2-diphenylethane was ignited in the bomb calorimeter in multiple trials. The results were used to calculate the enthalpy of combustion and enthalpy of formation of 1,2-diphenylethane.
Lauded as the fastest commercially available chip calorimeter, Flash DSC is ideal for studying rapid crystallization and reorganization processes, and is able to operate in temperatures from -95 to 1000 °C. These ultra-high cooling and heating rates have considerably progressed the study of thermally induced chemical processes and physical transitions, allowing the study of the crystallization and reorganization of a range of materials including metals and polymers like never before.
1) This document details an experiment to determine the melting points of organic compounds using a melting point apparatus. Students first calibrated their thermometers using known pure compounds.
2) They then determined the melting point of an unknown sample (#3), which was identified as 2-nitrobenzoic acid based on its melting point range matching the literature value.
3) Finally, students determined the melting point of a mixture of cinnamic acid and a second unknown (#2), which was identified as urea based on its physical properties and lower melting point of the mixture.
Differential scanning calorimetry (DSC) is a thermal analysis technique that measures the heat flow into or out of a sample as it is heated, cooled, or held at constant temperature. DSC directly measures the energy required to establish a zero temperature difference between a sample and an inert reference material as both are subjected to an identical temperature program. This allows the determination of transition temperatures such as melting points and glass transition temperatures. DSC is commonly used in pharmaceutical analysis to characterize materials such as purity determination, polymorphism detection, and stability studies. The basic components of a DSC instrument include sample and reference pans, a furnace to heat the pans at a controlled rate, and sensors to measure the heat flow difference between
Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used to measure the vapor pressure and heat of vaporization of organic compounds. TGA was able to estimate the vapor pressure of naphthalene and anthracene to within 21% and 30% of literature values, respectively. DSC trials in non-sealed pans measured heats of sublimation within 5% of literature, while sealed pan trials did not reduce boiling points below literature values due to pressurization. Further development is needed to apply these methods to organic materials.
Duncan Gordon et al., Physica B, 385-386, (2006), 511 - 513.Duncan Gordon
This study used time-resolved small-angle neutron scattering (SANS) to examine the crystallization process of a blend of deuterated and hydrogenated poly(ethylene terephthalate) (PET) over a temperature range of 220–230°C. SANS was able to track the growth of crystallites over time by following the increase in intensity of a scattering peak at 0.04 Å−1. Crystallization half-lives measured by SANS were similar to those obtained using differential scanning calorimetry. Analysis using the Avrami model yielded mechanistic constants between 2-3, indicating spherulitic crystallite growth.
1. Dendrimer-encapsulated gold nanoparticles were used to catalyze the reduction of 4-nitrophenol to 4-aminophenol at 40°C.
2. Five reaction conditions were tested with varying concentrations of 4-nitrophenol. Rate constants for the reactions were calculated and it was expected that the rate would decrease with increasing 4-nitrophenol concentration.
3. However, the results showed that the rate constants actually increased as the 4-nitrophenol concentration increased, with the highest rate seen at the highest concentration tested of 4M 4-nitrophenol. This trend was unexpected and suggests possible errors in the experiment.
This document describes an experiment using bomb calorimetry to measure the enthalpy of combustion of 1,2-diphenylethane. Bomb calorimetry works by igniting a substance in an insulated chamber and measuring the temperature change, from which the energy released can be calculated. The experiment used benzoic acid to first calibrate the bomb calorimeter and verify its functioning. Then, 1,2-diphenylethane was ignited in the bomb calorimeter in multiple trials. The results were used to calculate the enthalpy of combustion and enthalpy of formation of 1,2-diphenylethane.
Lauded as the fastest commercially available chip calorimeter, Flash DSC is ideal for studying rapid crystallization and reorganization processes, and is able to operate in temperatures from -95 to 1000 °C. These ultra-high cooling and heating rates have considerably progressed the study of thermally induced chemical processes and physical transitions, allowing the study of the crystallization and reorganization of a range of materials including metals and polymers like never before.
1) This document details an experiment to determine the melting points of organic compounds using a melting point apparatus. Students first calibrated their thermometers using known pure compounds.
2) They then determined the melting point of an unknown sample (#3), which was identified as 2-nitrobenzoic acid based on its melting point range matching the literature value.
3) Finally, students determined the melting point of a mixture of cinnamic acid and a second unknown (#2), which was identified as urea based on its physical properties and lower melting point of the mixture.
Differential scanning calorimetry (DSC) is a thermal analysis technique that measures the heat flow into or out of a sample as it is heated, cooled, or held at constant temperature. DSC directly measures the energy required to establish a zero temperature difference between a sample and an inert reference material as both are subjected to an identical temperature program. This allows the determination of transition temperatures such as melting points and glass transition temperatures. DSC is commonly used in pharmaceutical analysis to characterize materials such as purity determination, polymorphism detection, and stability studies. The basic components of a DSC instrument include sample and reference pans, a furnace to heat the pans at a controlled rate, and sensors to measure the heat flow difference between
This document outlines the procedures for four experiments to determine heat of reaction: heat of precipitation by mixing silver nitrate and sodium chloride solutions; heat of displacement by adding zinc to copper nitrate; heat of neutralization by mixing hydrochloric acid and sodium hydroxide; and heat of combustion by burning butanol to heat water. It records the initial and highest temperatures of the reactions and solutions, as well as the mass of butanol used.
This document provides guidance on writing an eighth grade science lab report on how temperature affects the rate of a chemical reaction. It recommends writing a focused research question that specifies the independent variable (temperature from 40 to 80 degrees Celsius) and dependent variable (mass of reaction mixture in grams). The hypothesis should state that as temperature increases, the mass will decrease due to one of the products escaping as a gas. The method section describes the controlled variables and step-by-step process for conducting trials at different temperatures, recording data, and presenting it in a table.
This document summarizes a seminar presentation on preformulation studies using thermal analysis, X-ray diffraction, and FT-IR spectroscopy. The presentation introduces various thermal analysis techniques including thermogravimetry, differential thermal analysis, and differential scanning calorimetry. Applications of thermal analysis in preformulation are discussed such as characterization of hydrates and solvates, study of polymers, detection of impurities, drug-excipient compatibility studies, polymorphism, prediction of drug stability, and degree of crystallinity. The document provides an overview of the techniques and their uses in preformulation studies.
This document discusses the use of differential scanning calorimetry (DSC) to analyze various materials including ice melting points, specific heat capacity measurements of materials, starch gelatinization and retrogradation, protein denaturation, oil and fat crystallization, gel formation and melting, glass transition temperatures, and microbial growth measurements. DSC can be used to characterize many phase transitions and thermal properties of foods, polymers, and other materials.
Here are the effects on the rate of reaction of changing each condition:
- If the concentration of acid is increased, the rate of reaction will increase. This is because there will be more reactant particles per unit volume, resulting in more frequent collisions between reactants.
- If calcium carbonate powder is used instead of small pieces, the rate of reaction will increase. This is because powder has a larger surface area, allowing for more reactant particles at the interface where the reaction occurs.
- If the volume of acid is increased, the rate of reaction will initially increase but then level off. This is because there will be more reactant particles initially, but the reaction will use them up over time.
- If the
Factors affecting rate of reaction (recovered)Siti Alias
The document discusses how several factors affect the rate of chemical reactions according to collision theory:
1. Increasing the surface area of reactants by decreasing their size increases the rate of reaction by increasing collision frequency.
2. Higher concentrations increase collision frequency by providing more particles in a given volume, likewise increasing the reaction rate.
3. Higher temperatures cause reactants to move faster and collide more frequently, also increasing the reaction rate.
4. Catalysts can lower the activation energy for a reaction, increasing the frequency of effective collisions and thereby accelerating the reaction.
5. For gas reactions, higher pressures compress the gas, providing more particles per volume and thus more collisions and a faster reaction.
The document discusses rate of reaction and factors that affect it. It defines rate of reaction as the change in amount of reactants or products per unit time. Rate of reaction is affected by several factors including surface area, concentration, temperature, catalysts and pressure (for gas reactions). The collision theory is also explained, stating that reactions only occur during effective collisions where particles attain sufficient kinetic energy to overcome the activation energy barrier. Examples of how scientific understanding of rate of reaction enhances quality of life through applications like food storage, cooking and petroleum processing are provided.
This chapter discusses rates of reactions. It defines rate of reaction as how fast or slow a reaction is taking place. There are three main ways to measure rate of reaction: measuring time taken for reaction to complete, measuring amount of product formed per unit time, and measuring amount of reactant used up or remaining per unit time. The rate of reaction is affected by several factors like temperature, concentration, particle size, catalyst, and pressure. Temperature has the greatest effect as increasing temperature increases the kinetic energy of particles, leading to more successful collisions. Catalysts are substances that increase reaction rate without being used up in the reaction. They provide alternative reaction pathways or increase surface area for contact between reactants.
Thermo catalytic decomposition of methane over Pd/AC and Pd/CB catalysts for ...IJERA Editor
Hydrogen production studies have been carried using Thermo Catalytic Decomposition (TCD) Unit. Thermo catalytic decomposition of methane is an attractive route for COx free production of hydrogen required in fuel cells. Although metal based catalysts produce hydrogen at low temperatures, carbon formed during methane decomposition reaction rapidly deactivates the catalyst. The present work compares the results of 10 wt% Pd supported on commercially available activated carbon and carbon black catalysts (samples coded as Pd10/AC and Pd10/CB respectively) for methane decomposition reaction. Hydrogen has been produced by thermo catalytic decomposition of methane at 1123K and Volume Hourly Space Velocity (VHSV) of 1.62 L/h g on the activity of both the catalysts has been studied. XRD of the above catalysts revealed, moderately crystalline peaks of Pd which may be responsible for the increase in catalytic life and formation of carbon fibers. Also during life studies (850°C and 54 sccm of methane) it has been observed that the activity of carbon black is sustainable for a longer time compared to that of activated carbon.
Higher molecular weight hydroxypropylcellulose (HPC) polymers are less thermally stable and more prone to discoloration at lower temperatures than lower molecular weight HPCs. Thermal gravimetric analysis showed slight discoloration starting around 140°C for the lowest molecular weight grade and around 190°C for the highest grade. Rheological analysis found that all grades can be extruded below 200°C but lower molecular weight grades have melt viscosities under 100,000 Pa·s, making them better suited for hot melt extrusion without plasticization. Extruded samples of all grades still met compendial testing requirements.
1) Thermogravimetric analysis (TGA) measures the weight changes of a material as it is heated in different atmospheres. It can be used to analyze inorganic materials, metals, polymers, ceramics, and composites.
2) The document describes using TGA to analyze the thermal decomposition of calcium oxalate monohydrate. Calcium oxalate monohydrate decomposes in three steps as it is heated.
3) The measured mass losses at each step of decomposition closely matched the theoretical predictions, validating the predicted thermal decomposition reactions of calcium oxalate monohydrate.
This document summarizes a seminar presentation on preformulation studies using thermal analysis, X-ray diffraction, and FT-IR spectroscopy. The presentation discusses the role of these techniques in preformulation, including methods like thermogravimetry, differential thermal analysis, and differential scanning calorimetry. Applications described are polymorphism analysis, detection of impurities, drug-excipient compatibility testing, and prediction of drug stability from thermal degradation profiles. The document provides an overview of the principles and applications of various thermal analysis techniques in pharmaceutical preformulation studies.
Thermal analysis methods such as differential scanning calorimetry (DSC) can provide both qualitative and quantitative information about physical and chemical changes in materials as a function of temperature. DSC instruments work by measuring the heat flow into a sample as it is heated, cooled, or held isothermally. This allows the instrument to detect transitions like glass transitions, melting points, crystallization events, and chemical reactions. Key components of DSC instruments include the sample holder, furnace, temperature programmer, recording device, and atmosphere control. DSC has many applications in fields like pharmaceutical analysis, materials characterization, and reaction kinetics studies.
This document discusses differential scanning calorimetry (DSC), providing an overview of the technique in 3 paragraphs or less. It describes DSC as a technique that measures the difference in heat flow between a sample and reference material as they are heated. The document outlines some of the main components of a DSC including sample pans, purge gas, and cooling systems. It also briefly discusses sample preparation, the working principle of DSC, interpreting DSC curves, and some common applications and types of DSC instruments.
Basic Polymer identification and DSC and TGA analysisVatsal Kapadia
Vatsal K. Kapadia is interning at Larsen & Toubro in their Polymer Testing department. During the internship, he is analyzing various polymer materials to identify their composition and properties. Some of the techniques he is using include differential scanning calorimetry to determine melting points and glass transition temperatures, thermogravimetric analysis to measure composition and filler content, and conducting various tests such as burning samples to identify different polymer classes. The goal of his analysis is to help determine the appropriate materials for components and identify opportunities to improve products.
Ppp Dsc 1 Thermal Analysis Fundamentals Of Analysisguest824336
Thermal analysis techniques such as differential scanning calorimetry (DSC) are used to investigate polymer properties as a function of temperature. DSC provides information on glass transition temperatures, crystallization temperatures, melting points, and heat capacity by measuring the heat flow into or out of a small polymer sample as it is heated or cooled. Proper sample preparation and experimental parameters are important to obtain accurate and reproducible DSC results.
Thermal analysis characterization of polymers and plastics acs webinarKevin Menard, Ph.D. MBA
Thermal analysis is a collection of techniques that examines how polymer properties change with temperature. Common techniques include DSC, TGA, DMA, and TMA. DSC measures transitions like glass transition and melting points via changes in heat flow or temperature. TGA analyzes weight changes with rising temperature such as decomposition. DMA provides storage modulus and damping curves to identify transitions. Thermal analysis is useful for characterizing polymers, determining purity, and studying curing and degradation. Hyphenated techniques like TG-IR and TG-GCMS further identify materials and products evolved during thermal degradation.
Factors affecting rate of chemical reactionsAbigail Sapico
The document summarizes experiments that demonstrate factors affecting the rate of chemical reactions. The experiments show that increasing the concentration of reactants, surface area of reactants, temperature, or adding a catalyst can increase the reaction rate. The nature of reactants also influences the reaction rate, as some combinations react faster than others.
The investigation of thermodynamic properties and reactivity yields interesting insights into the chemistry of newly synthesized substances. With thermal analysis extensive information can be gained from small samples (often only a few milligrams). In addition, the data obtained by thermal analysis can be used to plan and optimize a synthesis. Among the most important applications are identification and purity analysis, and the determination of characteristic temperatures and enthalpies of phase transitions (melting, vaporization), phase transformations, and reactions. Investigations into the kinetics of consecutive reactions and decomposition reactions are also possible. With the instruments available today such analyses can usually be performed quickly and easily. In this review the fundamentals of thermoanalytical methods are described and illustrated with selected examples of applications to low and high molecular weight compounds.
THERMAL ANALYSIS (DIFFERENTIAL THERMAL ANALYSIS AND DSC)Poonam Aher Patil
This document provides information on differential thermal analysis (DTA). It begins by defining DTA as a technique that measures the difference in temperature between a substance and reference material as they are subjected to a controlled temperature program. It describes various physical and chemical phenomena that can cause changes in temperature, such as adsorption, desorption, melting, and reactions. The document discusses factors that can affect DTA curves, including instrumental factors like furnace atmosphere and heating rate, and sample factors like particle size and amount. It also provides details on DTA instrumentation, theoretical aspects, applications, advantages, and references.
This document summarizes a student group's chemistry experiment on the effect of temperature on the solubility of potassium nitrate. The group used a Stella dynamic model to predict that solubility would increase exponentially with temperature. They conducted trials dissolving potassium nitrate in water at 0°C, 25°C and 60°C, collecting data from 15 total trials at each temperature. Their results showed solubility increased as temperature increased, supporting their hypothesis. However, their 60°C data was lower than predicted, possibly due to cooling from room temperature. Overall, their precise data matched other research, though other large data sets showed more variability.
This document outlines the procedures for four experiments to determine heat of reaction: heat of precipitation by mixing silver nitrate and sodium chloride solutions; heat of displacement by adding zinc to copper nitrate; heat of neutralization by mixing hydrochloric acid and sodium hydroxide; and heat of combustion by burning butanol to heat water. It records the initial and highest temperatures of the reactions and solutions, as well as the mass of butanol used.
This document provides guidance on writing an eighth grade science lab report on how temperature affects the rate of a chemical reaction. It recommends writing a focused research question that specifies the independent variable (temperature from 40 to 80 degrees Celsius) and dependent variable (mass of reaction mixture in grams). The hypothesis should state that as temperature increases, the mass will decrease due to one of the products escaping as a gas. The method section describes the controlled variables and step-by-step process for conducting trials at different temperatures, recording data, and presenting it in a table.
This document summarizes a seminar presentation on preformulation studies using thermal analysis, X-ray diffraction, and FT-IR spectroscopy. The presentation introduces various thermal analysis techniques including thermogravimetry, differential thermal analysis, and differential scanning calorimetry. Applications of thermal analysis in preformulation are discussed such as characterization of hydrates and solvates, study of polymers, detection of impurities, drug-excipient compatibility studies, polymorphism, prediction of drug stability, and degree of crystallinity. The document provides an overview of the techniques and their uses in preformulation studies.
This document discusses the use of differential scanning calorimetry (DSC) to analyze various materials including ice melting points, specific heat capacity measurements of materials, starch gelatinization and retrogradation, protein denaturation, oil and fat crystallization, gel formation and melting, glass transition temperatures, and microbial growth measurements. DSC can be used to characterize many phase transitions and thermal properties of foods, polymers, and other materials.
Here are the effects on the rate of reaction of changing each condition:
- If the concentration of acid is increased, the rate of reaction will increase. This is because there will be more reactant particles per unit volume, resulting in more frequent collisions between reactants.
- If calcium carbonate powder is used instead of small pieces, the rate of reaction will increase. This is because powder has a larger surface area, allowing for more reactant particles at the interface where the reaction occurs.
- If the volume of acid is increased, the rate of reaction will initially increase but then level off. This is because there will be more reactant particles initially, but the reaction will use them up over time.
- If the
Factors affecting rate of reaction (recovered)Siti Alias
The document discusses how several factors affect the rate of chemical reactions according to collision theory:
1. Increasing the surface area of reactants by decreasing their size increases the rate of reaction by increasing collision frequency.
2. Higher concentrations increase collision frequency by providing more particles in a given volume, likewise increasing the reaction rate.
3. Higher temperatures cause reactants to move faster and collide more frequently, also increasing the reaction rate.
4. Catalysts can lower the activation energy for a reaction, increasing the frequency of effective collisions and thereby accelerating the reaction.
5. For gas reactions, higher pressures compress the gas, providing more particles per volume and thus more collisions and a faster reaction.
The document discusses rate of reaction and factors that affect it. It defines rate of reaction as the change in amount of reactants or products per unit time. Rate of reaction is affected by several factors including surface area, concentration, temperature, catalysts and pressure (for gas reactions). The collision theory is also explained, stating that reactions only occur during effective collisions where particles attain sufficient kinetic energy to overcome the activation energy barrier. Examples of how scientific understanding of rate of reaction enhances quality of life through applications like food storage, cooking and petroleum processing are provided.
This chapter discusses rates of reactions. It defines rate of reaction as how fast or slow a reaction is taking place. There are three main ways to measure rate of reaction: measuring time taken for reaction to complete, measuring amount of product formed per unit time, and measuring amount of reactant used up or remaining per unit time. The rate of reaction is affected by several factors like temperature, concentration, particle size, catalyst, and pressure. Temperature has the greatest effect as increasing temperature increases the kinetic energy of particles, leading to more successful collisions. Catalysts are substances that increase reaction rate without being used up in the reaction. They provide alternative reaction pathways or increase surface area for contact between reactants.
Thermo catalytic decomposition of methane over Pd/AC and Pd/CB catalysts for ...IJERA Editor
Hydrogen production studies have been carried using Thermo Catalytic Decomposition (TCD) Unit. Thermo catalytic decomposition of methane is an attractive route for COx free production of hydrogen required in fuel cells. Although metal based catalysts produce hydrogen at low temperatures, carbon formed during methane decomposition reaction rapidly deactivates the catalyst. The present work compares the results of 10 wt% Pd supported on commercially available activated carbon and carbon black catalysts (samples coded as Pd10/AC and Pd10/CB respectively) for methane decomposition reaction. Hydrogen has been produced by thermo catalytic decomposition of methane at 1123K and Volume Hourly Space Velocity (VHSV) of 1.62 L/h g on the activity of both the catalysts has been studied. XRD of the above catalysts revealed, moderately crystalline peaks of Pd which may be responsible for the increase in catalytic life and formation of carbon fibers. Also during life studies (850°C and 54 sccm of methane) it has been observed that the activity of carbon black is sustainable for a longer time compared to that of activated carbon.
Higher molecular weight hydroxypropylcellulose (HPC) polymers are less thermally stable and more prone to discoloration at lower temperatures than lower molecular weight HPCs. Thermal gravimetric analysis showed slight discoloration starting around 140°C for the lowest molecular weight grade and around 190°C for the highest grade. Rheological analysis found that all grades can be extruded below 200°C but lower molecular weight grades have melt viscosities under 100,000 Pa·s, making them better suited for hot melt extrusion without plasticization. Extruded samples of all grades still met compendial testing requirements.
1) Thermogravimetric analysis (TGA) measures the weight changes of a material as it is heated in different atmospheres. It can be used to analyze inorganic materials, metals, polymers, ceramics, and composites.
2) The document describes using TGA to analyze the thermal decomposition of calcium oxalate monohydrate. Calcium oxalate monohydrate decomposes in three steps as it is heated.
3) The measured mass losses at each step of decomposition closely matched the theoretical predictions, validating the predicted thermal decomposition reactions of calcium oxalate monohydrate.
This document summarizes a seminar presentation on preformulation studies using thermal analysis, X-ray diffraction, and FT-IR spectroscopy. The presentation discusses the role of these techniques in preformulation, including methods like thermogravimetry, differential thermal analysis, and differential scanning calorimetry. Applications described are polymorphism analysis, detection of impurities, drug-excipient compatibility testing, and prediction of drug stability from thermal degradation profiles. The document provides an overview of the principles and applications of various thermal analysis techniques in pharmaceutical preformulation studies.
Thermal analysis methods such as differential scanning calorimetry (DSC) can provide both qualitative and quantitative information about physical and chemical changes in materials as a function of temperature. DSC instruments work by measuring the heat flow into a sample as it is heated, cooled, or held isothermally. This allows the instrument to detect transitions like glass transitions, melting points, crystallization events, and chemical reactions. Key components of DSC instruments include the sample holder, furnace, temperature programmer, recording device, and atmosphere control. DSC has many applications in fields like pharmaceutical analysis, materials characterization, and reaction kinetics studies.
This document discusses differential scanning calorimetry (DSC), providing an overview of the technique in 3 paragraphs or less. It describes DSC as a technique that measures the difference in heat flow between a sample and reference material as they are heated. The document outlines some of the main components of a DSC including sample pans, purge gas, and cooling systems. It also briefly discusses sample preparation, the working principle of DSC, interpreting DSC curves, and some common applications and types of DSC instruments.
Basic Polymer identification and DSC and TGA analysisVatsal Kapadia
Vatsal K. Kapadia is interning at Larsen & Toubro in their Polymer Testing department. During the internship, he is analyzing various polymer materials to identify their composition and properties. Some of the techniques he is using include differential scanning calorimetry to determine melting points and glass transition temperatures, thermogravimetric analysis to measure composition and filler content, and conducting various tests such as burning samples to identify different polymer classes. The goal of his analysis is to help determine the appropriate materials for components and identify opportunities to improve products.
Ppp Dsc 1 Thermal Analysis Fundamentals Of Analysisguest824336
Thermal analysis techniques such as differential scanning calorimetry (DSC) are used to investigate polymer properties as a function of temperature. DSC provides information on glass transition temperatures, crystallization temperatures, melting points, and heat capacity by measuring the heat flow into or out of a small polymer sample as it is heated or cooled. Proper sample preparation and experimental parameters are important to obtain accurate and reproducible DSC results.
Thermal analysis characterization of polymers and plastics acs webinarKevin Menard, Ph.D. MBA
Thermal analysis is a collection of techniques that examines how polymer properties change with temperature. Common techniques include DSC, TGA, DMA, and TMA. DSC measures transitions like glass transition and melting points via changes in heat flow or temperature. TGA analyzes weight changes with rising temperature such as decomposition. DMA provides storage modulus and damping curves to identify transitions. Thermal analysis is useful for characterizing polymers, determining purity, and studying curing and degradation. Hyphenated techniques like TG-IR and TG-GCMS further identify materials and products evolved during thermal degradation.
Factors affecting rate of chemical reactionsAbigail Sapico
The document summarizes experiments that demonstrate factors affecting the rate of chemical reactions. The experiments show that increasing the concentration of reactants, surface area of reactants, temperature, or adding a catalyst can increase the reaction rate. The nature of reactants also influences the reaction rate, as some combinations react faster than others.
The investigation of thermodynamic properties and reactivity yields interesting insights into the chemistry of newly synthesized substances. With thermal analysis extensive information can be gained from small samples (often only a few milligrams). In addition, the data obtained by thermal analysis can be used to plan and optimize a synthesis. Among the most important applications are identification and purity analysis, and the determination of characteristic temperatures and enthalpies of phase transitions (melting, vaporization), phase transformations, and reactions. Investigations into the kinetics of consecutive reactions and decomposition reactions are also possible. With the instruments available today such analyses can usually be performed quickly and easily. In this review the fundamentals of thermoanalytical methods are described and illustrated with selected examples of applications to low and high molecular weight compounds.
THERMAL ANALYSIS (DIFFERENTIAL THERMAL ANALYSIS AND DSC)Poonam Aher Patil
This document provides information on differential thermal analysis (DTA). It begins by defining DTA as a technique that measures the difference in temperature between a substance and reference material as they are subjected to a controlled temperature program. It describes various physical and chemical phenomena that can cause changes in temperature, such as adsorption, desorption, melting, and reactions. The document discusses factors that can affect DTA curves, including instrumental factors like furnace atmosphere and heating rate, and sample factors like particle size and amount. It also provides details on DTA instrumentation, theoretical aspects, applications, advantages, and references.
This document summarizes a student group's chemistry experiment on the effect of temperature on the solubility of potassium nitrate. The group used a Stella dynamic model to predict that solubility would increase exponentially with temperature. They conducted trials dissolving potassium nitrate in water at 0°C, 25°C and 60°C, collecting data from 15 total trials at each temperature. Their results showed solubility increased as temperature increased, supporting their hypothesis. However, their 60°C data was lower than predicted, possibly due to cooling from room temperature. Overall, their precise data matched other research, though other large data sets showed more variability.
This document summarizes a thermochemistry lab experiment to determine the heat of combustion of paraffin wax. The purpose was to measure the amount of heat released when one mole of paraffin wax combusts. The procedure involved using a calorimeter to heat water as the wax combusted. Calculations were done to determine the heat released and the molar heat of combustion. The calculated value was 8,607.95 kJ/mol, which was lower than the actual value of 14,800 kJ/mol likely due to heat loss to the surroundings during the experiment.
Thermogravimetric analysis (TGA) is a technique that measures how the weight of a material changes as it is heated. TGA provides information about decomposition temperatures, thermal degradation properties, and quantitative weight losses. The key components of a TGA instrument are a furnace, balance, temperature controller, and recorder. Samples are heated and their weight changes are measured continuously as a function of increasing temperature. Weight loss curves can indicate decomposition reactions and be used to determine composition. TGA has applications in characterizing materials used in various industries.
NETZSCH Nevio Instrument Series for THERMAL ANALYSISValentyn Mohylyuk
This document discusses the use of thermal analysis techniques like differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) for investigating pharmaceuticals, foods, and cosmetics. It provides examples of how DSC and TGA can be used to characterize materials and determine properties like melting points, phase transitions, decomposition behavior, and composition. The document also describes the NETZSCH Nevio series of instruments, which are designed for thermal analysis in industries like chemicals, pharmaceuticals, cosmetics, and foods.
PCR was invented in 1983 by Kary Mullis and revolutionized molecular biology. It allows for the exponential amplification of specific DNA regions using thermal cycling and two primers. Key developments included the use of Taq polymerase, automation using thermal cyclers, and optimization of components and cycling conditions. Variations like nested PCR, hot start PCR, and RT-PCR expanded PCR applications. PCR provides a powerful and sensitive technique for detecting and analyzing DNA and RNA.
This document provides an overview of thermo-gravimetric analysis (TGA). TGA measures how a material's weight changes as it is heated or cooled over time in a controlled atmosphere. It works by heating a sample and measuring its weight loss, which reveals information about physical and chemical changes and decomposition temperatures. The key components of a TGA system include a furnace, thermobalance, temperature sensor and recorder. Sample preparation and experimental conditions like heating rate and atmosphere can affect results. TGA is used to analyze materials like ceramics and polymers and determine purity and thermal stability.
This document discusses differential thermal analysis (DTA), which measures the difference in temperature between a sample and a reference material as both are heated. It describes phenomena like physical changes (melting, vaporization) and chemical reactions that cause temperature changes detectable by DTA. Instrumentation for DTA is also outlined, including furnaces, temperature programmers, and amplifiers. Factors that can affect DTA curves like heating rate, atmosphere, sample mass, and particle size are examined. Differential scanning calorimetry (DSC) is also introduced as a related technique.
The document discusses various thermal characterization techniques used to analyze textile materials. It begins by outlining the session outcomes, which are to discuss principles, explain instrumentation methods, interpret results, and explore applications of thermal characterization techniques. These techniques include thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), differential thermal analysis (DTA), thermomechanical analysis (TMA), and dynamic mechanical analysis (DMA). The document then provides details on the basic principles, instrumentation, and applications of TGA, DSC, DTA, and TMA. TGA is used to measure weight changes as a function of temperature, DSC measures heat flows during transitions, DTA records temperature differences between
1) Isotactic and amorphous polypropylene samples were tested using differential scanning calorimetry. The isotactic sample crystallized at 151.36°C with an enthalpy of 87.04 J/g and entropy of 0.34 J/(g K).
2) The amorphous sample showed a glass transition at -11.02°C with an enthalpy of 15.38 J/g and entropy of 11.5 J/g K, indicating it was not fully amorphous.
3) The crystallinity of the isotactic and amorphous samples were determined to be 42% and 6.8% respectively based on their enthalpies of crystall
This document summarizes an experiment conducted using a Marcet boiler to determine the relationship between the pressure and temperature of saturated steam. The experiment measured pressure and temperature values over a range of approximately 0-14 bars. These measured values were then compared to theoretical values from steam tables. The results showed that pressure and temperature were directly proportional, though some measured values differed slightly from predicted values, possibly due to experimental errors. The document also lists the objectives, equipment used, calculations made, and discusses sources of error in the experiment.
Presentation given by Dr David Vega-Maza from University of Aberdeen on "Vapour-Liquid and Solid-Vapour-Liquid Equilibria of the System (CO2 + H2) at Temperatures Between (218 and 303) K and at Pressures up to 15 MPa" in the Effects of Impurities Technical Session at the UKCCSRC Biannual Meeting - CCS in the Bigger Picture - held in Cambridge on 2-3 April 2014
In DSC the heat flow is measured and plotted against temperature of furnace or time to get a thermo gram. This is the basis of Differential Scanning Calorimetry (DSC).
The deviation observed above the base (zero) line is called exothermic transition and below is called endothermic transition.
Thermal analysis techniques such as differential scanning calorimetry (DSC) measure physical and chemical changes that occur in a material when it is heated or cooled. DSC specifically works by heating a sample and reference simultaneously while measuring the heat flow into or out of the sample. This allows it to detect transitions like melting, crystallization, and glass transitions. DSC is commonly used in pharmaceuticals to determine purity, detect polymorphism, and study stability and compatibility. It provides information on thermal events and material properties through measurements of heat flow versus temperature.
Thermal denaturation studies can yield a significant amount
of information about the secondary structure of DNA molecules. The double helix structure is held together by the hydrogen bonds in base pairs of adenine-thymine (A-T) and guanine-cytosine (G-C). Since G-C base pairs have three hydrogen bonds compared to the 2 in A-T base pairs, a DNA sample with larger G-C content will require more energy to separate, leading to a higher DNA melt temperature. UV/Visible Spectrophotometry can be used to monitor the thermal denaturation of DNA as the sample is heated allowing determination of the DNA melt temperature, tm, and ultimately the %G-C content of the molecule.
1. The student conducted a bomb calorimetry experiment to determine the calorie content of a Fruit Loop cereal by measuring the energy released during combustion.
2. The experiment yielded a measured energy value of 3.762 kJ for one piece of Fruit Loop, compared to the manufacturer's listed value of 3.424 kJ, a difference of 0.338 kJ.
3. The student was surprised to find their measured value was higher than the listed value, as they had expected the older cereal sample would contain less energy, but the small difference suggests the manufacturer's calorie listing is accurate.
Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) are thermal analytical techniques that measure changes in the mass and temperature of a sample as it is heated. TGA measures weight changes that occur as a sample is heated, providing information on physical and chemical phenomena like phase transitions and decomposition. DTA measures the difference in temperature between a sample and an inert reference as both are heated, revealing endothermic and exothermic reactions in the sample. Together, TGA and DTA can be used to characterize materials and determine their composition, purity, and thermal stability.
Differential thermal analysis and it's pharmaceutical applicationJp Prakash
Differential thermal analysis (DTA) is a thermal analysis technique that measures the temperature difference between a sample and an inert reference material as both are subjected to a controlled temperature program. DTA can detect physical and chemical changes that involve endothermic or exothermic processes, such as melting, crystallization, oxidation, and decomposition. DTA is widely used in pharmaceutical applications to characterize materials and determine phase transitions, decomposition temperatures, and thermal stability. The document provides examples of DTA studies on sulfur, benzoic acid, and the antihypertensive drug telmisartan to illustrate how DTA can identify physical and chemical changes that occur as temperature is varied.
This presentation summarizes differential scanning calorimetry (DSC), which measures the heat flow into or out of a sample during heating or cooling. DSC can determine phase transitions like glass transitions, melting points, and crystallization temperatures. It works by heating a sample and reference simultaneously while measuring any heat differential. Factors like heating rate, sample size, and instrumentation can affect results. DSC is useful for characterizing polymers and other materials.
Similar to Determination of Thermodynamic Properties of OLED Compounds (20)
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
Determination of Thermodynamic Properties of OLED Compounds
1. Determination of Thermodynamic
Properties of Organic Compounds
Team Serval: Logan Williamson, Owen Perlowski, Kristen Webster, Nick Kasper
CHE 255: Chemical Engineering Processes
December 13th, 2016
3. Current method:
Guess and Check = Time and Money
Problem
3
New
Material
Guess ideal
temp zones to
purify product
Train
sublimation
under vacuum
Successful
Separation?
(HPLC)
No Yes
4. Goals
Measure heat of vaporization
Run experiments under reduced pressure/temperature
Required accuracy: ballpark
Stay within budget/time constraints
4
6. Our Approach: Experiments
Thermogravimetric
Analysis
- Mass loss vs. temperature/time
- Clausius-Clapeyron equation
- No need to approach
degradation temperature
6
Differential Scanning
Calorimetry
- Differential heat flow vs.
temperature
- Lower pressure by sealing pans
under vacuum
Pressure reduction method
unsuccessful
Successful and promising
for application
7. Thermogravimetric Analysis (TGA): What is it?
http://www.tainstruments.com/tga-5500/ https://www.researchgate.net/figure/263958136_fig2_Figure-2-Schematic-of-the-TGA
7
8. TGA: Theory
8Source: Price, Duncan M. "Vapor Pressure Determination by Thermogravimetry."Thermochimica Acta 367-368 (2001): 253-62.
9. TGA: Experimental Outline
9
Determine Calibration
Constant (k)
Using k, Calculate Vapor
Pressures of Model
Compounds
Use Vapor Pressures to
Calculate Heat of
Vaporization of Model
Compounds
Compare Calculated
Values to Literature
Values
Use Method to Calculate
Vapor Pressures and
Heat of Vaporization of
Compound with No
Literature Data
11. TGA: Determining k for Each Compound
11
Anthracene
k = 887,652
Naphthalene
k = 1,503,009
12. TGA: Calculating Vapor Pressure Using
Optimized k
12
Using Least-Squares Regression:
Naphthalene
Temp (℃) Lit. p (Pa)
Avg.
Calculated p
(Pa)
Percent
Error
80 1000 828 17.2
93 1811 1672 7.7
98 2357 2036 13.6
103 2833 2418 14.7
115 4752 3754 21.0
Anthracene
Temp (℃) Lit. p (Pa)
Avg.
Calculated p
(Pa)
Percent
Error
227 7000 7898 12.8
237 9000 10,227 13.6
247 12000 12,051 0.4
257 16000 13,330 16.7
Optimal k = 1,183,875
Average % Error: 13%
13. TGA: Calculating Heats of Vaporization of Model Compounds
13
Naphthalene Anthracene
Calculated ΔHVap 49.3 kJ/mol
Literature ΔHVap 56.1 kJ/mol
Percent Error 12.1
Calculated ΔHVap 41.2 kJ/mol
Literature ΔHVap 59.2 kJ/mol
Percent Error 30.1
14. TGA: Heat of Vaporization is Independent of k
14
Naphthalene
kOpt = 1,183,875
ΔHVap = 49.3 kJ/mol
k = 1
ΔHVap = 49.3 kJ/mol
15. TGA: Calculating Heat of Vaporization of Unknown
Compound
15
Tri-p-tolylamine (TTA)
Temp (℃) Avg. Calculated p (Pa)
250 2692
280 5157
Calculated ΔHVap 52.2 kJ/mol
Molecular Weight: 287.4 g/mol
Using kOpt = 1,183,875
16. TGA: Summary
16
● Good for determining how long it will take to vaporize any compound at a
given temperature. This could help Molecular Glasses save time during
their purification of materials. TGA is versatile and can reach temperatures
> 1000℃.
● Vapor pressures can be estimated within ~20% error. One possible way to
reduce the error is to test more than 2 model compounds when regressing
for the calibration constant. Also test wider range of temperatures.
● Heats of Vaporization can be estimated using calculated vapor pressures.
Furthermore, these heats are independent of the calibration constant and
can therefore be calculated strictly from a TGA test and the Clausius-
Clapeyron equation.
19. Changes from Initial Build
Sealed areas that could
have allowed air leakage
with gorilla glue
Added cardboard blast
shield
19
20. Changes from Initial Build
Changed pressure gauge
after valve to a liquid filled
gauge to increase
readability
20
21. Vacuum Bagging Procedure
1. Cut bagging film into 3”x 8” sheets.
2. Place connector base and DSC pan with sample and lid on top on top of one
sheet.
3. Apply sealant tape around edges.
4. Place second sheet on top of the first and press down on tape to seal.
5. Connect connector to pump system and turn on pump.
6. Close valve 2 and allow pressure to build up within vessel.
7. Close valve 1 and open valve 2 to remove air from bag. 21
24. DSC
24www.pcbshop.prg
DSC Procedure was split into three
different sections, for the three different
pans we used:
1. Non-Hermetically Sealed Pans
2. Hermetically Sealed Pans under
vacuum
3. Hermetically Sealed pans not under
vacuum (1 atm)
The following slides will provide a simple
guide to each type of pan procedure
25. DSC - Procedure
(Non-Hermetic Pans Supplied by Mark Juba, Hermetically Sealed Pans provided
by Anthamatten Lab)
1. Place desired sample in pan. Weigh pan before and after.
a. If Hermetically sealed, use TA clamp to seal shut
2. Determine procedure in DSC program
a. Determine max temp/temp increase.
3. Input reference pan, along with pan with sample
4. Run sample
25
26. DSC: Results
Results for the DSC were in this form:
This graph shows us the Heat Flow (W/g) vs.
Temperature (C) .
As we know, the DSC records required heat for
phase change. This is expressed as a peak on
this graph.
By using manual integration present in the DSC
analysis software, we are able to find the precise
amount of heat required for this specific instance
of phase change. These values were compared
to literature for accuracy and error percentages
were analyzed calculated.
26
27. Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
24.966 47.241 72.206
%Error 16.222 20.201 26.244
Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
27.549 45.797 73.347
%Error 7.551 22.639 25.079
Anthracene Hermetic 1atm Trials
Anthracene Literature BP: 342C
Anthracene Literature MP: 218C
MP & BP Found at:
O'Neil, M.J. (ed.). The Merck Index - An Encyclopedia of Chemicals, Drugs, and Biologicals. Whitehouse
Station, NJ: Merck and Co., Inc., 2006., p. 111 27
Mass = 17.3mg
Mass = 9mg
28. Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
27.549 46.778 74.327
%Error 7.551 20.983 24.078
Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
25.251 47.793 73.044
%Error 15.265 19.268 25.389
Anthracene Hermetic Vacuum Trials
Anthracene Literature BP: 342C
Anthracene Literature MP: 218C
28
Mass = 14.8mg
Mass = 7.2mg
30. Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
- - 98.188
%Error - - 0.294
Mass(mg) Calc H Fusion
(kJ/mol)
Calc H Vap
(kJ/mol)
Calc H Sub
(kJ/mol)
25.7 - - 93.537
%Error - - 4.456
Anthracene Non-Hermetic Trials
Anthracene Literature BP: 342C
Anthracene Literature MP: 218C
30
Mass = 13.4mg
Mass = 25.7mg
32. DSC: Summary
Saw no improvement with using vacuum bagging system to reduce pressure
inside the pan.
Increase in boiling point for sealed pans may tell us there is a small amount of
pressure buildup in our pans, which is counterproductive.
We observed literature consistency with non-hermetically sealed pans, although
it appears impossible to determine only heat of vaporization or only heat of
fusion for these trials.
No difference when using different mass amounts. Data is consistent regardless
of mass.
Observed relatively accurate heats for our compounds. This could be incredibly
32
33. Conclusion
Our goal was to determine the heat of vaporization of solid compounds under
reduced pressure for application to OLED materials
2 methods:
Differential scanning calorimetry (DSC) w/ vacuum sealing
Thermogravimetric analysis (TGA)
TGA and non-hermetically sealed DSC gave results most consistent with the
literature
No improvement with using vacuum bagging system to reduce pressure inside
the pan due to a buildup of internal pressure in the pans 33
34. Acknowledgments
We would like to thank everyone in the chemical engineering
department for allowing us this opportunity with a special
thanks to Professor Kelley, Mark Juba, Dave Weiss, Larry
Kuntz, Professor Tenhaeff, Cindy Fitzgerald, Rachel
Monfredo, our TA Robbie Harding, and Dawei Chen from the
Anthamatten Lab.
34
37. Additional TGA Analysis
37
Error Analysis:
Hypothesis: Noise in the data increases as the temperature increases.
Naphthalene Anthracene
Temperature [℃]
dm/dt[g/min]
Temperature [℃]
dm/dt[g/min]
38. References
Melting Point and Boiling Point of Anthracene:
O'Neil, M.J. (ed.). The Merck Index - An Encyclopedia of Chemicals, Drugs, and Biologicals. Whitehouse Station, NJ: Merck and Co., Inc., 2006., p. 111
Heat of Fusion & Vaporization, Anthracene:
Rojas, Aarón; Orozco, Eulogio, Measurement of the enthalpies of vaporization and sublimation of solids aromatic hydrocarbons by differential scanning calorimetry,
Thermochimica Acta, 2003, 405, 1, 93-107
Heat of Sublimation, Anthracene:
Oja, Vahur; Chen, Xu; Hajaligol, Mohammad R.; Chan, W. Geoffrey, Sublimation Thermodynamic Parameters for Cholesterol, Ergosterol, β-Sitosterol, and Stigmasterol, J.
Chem. Eng. Data, 2009, 54, 3, 730-734.
Thermogravimetric Methodology:
Price, Duncan M. "Vapor Pressure Determination by Thermogravimetry."Thermochimica Acta 367-368 (2001): 253-62.
38
Editor's Notes
We ball out
Molecular Glasses’ problem is that determining the properties of their new materials takes far too long and costs too much material.
They basically purify their sample under trial conditions and see how well it separates… then do it again… and again…
The goals of our project were:
Measure the heat of sublimation of model compounds
FInd ways to reduce pressure and/or avoid the high temps that degrade Molecular Glasses’ materials
The company isn’t looking for specific values, but a ballpark range for purification purposes
Just like all the other teams, we had a timeline of about 13 weeks and a budget of $500
(Nick) (I can talk about model compounds because it seems to lump in well with the previous slide)
Our two model compounds were naphthalene and anthracene. These compounds are high vapor pressure solids that work well to model the organic compounds that Molecular Glasses will need to test.
Anthracene is less volatile than naphthalene, both are less volatile than real OLEDs
We tested two experimental methods to determine heat of sublimation
One of the methods we used to determine vapor pressure and heat of vaporization of these model compounds is thermogravimetric analysis. This is a type of thermal analysis that measures mass loss as a function of temperature and time. It is a versatile instrument that can reach temperatures of over 1000 degrees celsius and is therefore commonly used to measure the thermal stability of chemical compounds. Our use of TGA focuses around a paper published by Duncan Price in which he uses a TGA under normal operating conditions to estimate the vapor pressure and heat of vaporization of various compounds.
Price’s methodology begins from the Langmuir equation for free evaporation. This equation has a couple assumptions, including that vaporization is a zeroth order process, meaning that rate of vaporization is independent of the amount of material, and that there is a uniform surface area for evaporation to occur.
Both the vapor pressure, p, and the vaporization coefficient, alpha, are unknown in this equation when the process is carried out under atmospheric conditions. Rearranging this equation and letting k = READ SLIDE and v = READ slide, we are able to obtain a linear relationship between vapor pressure and v with a slope of k, which is a calibration constant that is assumed to be independent of the chemical being vaporized. If we are able to determine this calibration constant, we will then be able to calculate vapor pressure using this value of k and v, which can be calculated from the results of a TGA trial.
Once vapor pressure is known, heat of vaporization can be determined using the Clausius-Clapeyron equation.
The experimental outline for the TGA method are as follows:
Various tests were conducted on naphthalene and anthracene and the using the results of the tests and the literature vapor pressures, a calibration constant for the machine was calculated.
This k value was used to calculate the vapor pressures of the model compounds
Once these vapor pressures were calculated, the Clausius-Clapeyron Equation was used to calculate the heat of vaporization of the model compounds.
These values were then compared to literature values to analyze the validity of the method.
The method was then repeated in order to calculate the vapor pressures and heat of vaporization of a compound with no known thermodynamic literature data.
Above is an example of the output of a single TGA trial, in this case naphthalene. As you can see the software very nicely allows us to calculate the rate of mass loss, which is denoted by the slope. It also confirms the assumption that rate of vaporization is independent of amount of material. These slope values, along with corresponding temperature and molecular weight of the given compound, are what was used to calculate v.
As was described on a previous slide, the first step in the analysis was to determine the calibration constant.
To do this we plotted literature vapor pressure values as a function of v for both naphthalene and anthracene. This resulted in a k value of 1,503,009 for naphthalene and 887,652 for anthracene. Clearly, these values are the same as was the assumption made when deriving the equations. We had to come up with a way to find an optimal k value to use for vapor pressure calculations.
After a lot of thought, it was decided to use a least squares regression of all the data (naphthalene and anthracene) , minimizing the error between the back-calculated vapor pressures and the literature values, to calculate an optimal k value. This optimized calibration constant was used to calculate the vapor pressures shown. As we can see, this results are reasonable. We are able to calculate average vapor pressures to within 21% of the literature values. The average error is 13%, which is lends some credibility to the method for determining vapor pressures. If more model compounds were tested this uncertainty could presumable be improved.
Using these calculated vapor pressures, the Clausius-Clapeyron equation was used to calculate the heat of vaporization of both naphthalene and anthracene. For those who may be unfamiliar with this formulation, a plot of the natural log of vapor pressure vs the reciprocal absolute temperature gives a linear relationship with a slope of heat of vaporization divided by the gas constant. Multiplying through by the gas constant gives us our heat of vaporization. As can be seen, the heat of vaporization of naphthalene was calculated to be 49.3 kJ/mol, resulting in a 12.1% error from the literature value. Likewise, anthracene had a calculated vapor pressure of 41.2 kJ/mol, resulting in a 21% error. As we see, our calculated enthalpies are less than the literature values, which could be the result of the Clausius-Clapeyron equation assuming that heats of vaporization are independent of temperature, which is an assumption that is made to make the calculations easier but is not exact.. Also, the level of variance in the anthracene data could be resulting in the greater percent error.
One of the most fascinating results of the project was that we were able to determine that the value calculated for heat of vaporization is in fact independent of the k value. As long as k is greater than zero, any value can be entered and the same heat of vaporization will be calculated, as can be seen here. When k is altered, the only thing that changes is the y-intercept. Therefore, if all you are looking to calculate is the heat of vaporization and don’t care about vapor pressures, you can simply run a TGA test on your compound and use the Clausius-Clapeyron Equation and boom you have your heat of vaporization. However, if you’re interested in determining vapor pressures, it is still necessary to find an optimal calibration constant.
Since the method seems viable, we went ahead and ran a few TGA tests on tri-p-tolylamine, an actual OLED compound, that has no literature vapor pressure and heat of vaporization data. At 250 degrees Celsius the vapor pressure was calculated to be 2692 Pa and at 280 degrees C it was 5157 Pa. The heat of vaporization of the compound was found to be 52.2 kJ/mol. Clearly, due to time constraints, very few temperatures were able to be tested. However, the idea behind the methodology seems to be viable.
Differential Scanning Calorimetry compares required heat needed for a pan with sample vs. a pan without sample to maintain constant increase in temperature.
The proposed idea of Lab Group Serval was to hermetically seal a DSC pan under low pressure, in an attempt to decrease observed boiling point of model compounds Naphthalene and Anthracene.
This would aid Molecular Glasses in their attempt to experimentally determine heats of sublimation/vaporization for their compounds in question
Anthracene 1atm Sealed
Anthracene 1atm Sealed
To visualize this effect, box and whisker plots were constructed with rate of mass loss being plotted as a function of temperature. As you can see, there does seem to be some correlation between temperature and degree of variability in the data, with the amount of spread increasing as temperature increases. However, we cannot confirm the temperature increase as the causation and further testing should be carried out on other heavy compounds that require high temperatures to see if this trend continues if this method if pursued. This is important to note because OLED materials tend to be involatile and therefore need to be purified at higher temperatures. This led to the problem of what value for k do we use to calculate vapor pressures and heat of vaporization?