1:45 PM - 3:15 PM
[SMP27-P08] Feasibility study for Particle morphology speciation analysis on the soil minerals using Statistical Raman Analysis.
Keywords:a statistical Raman analysis, particle size, particle shape, particle morphology
Introduction
A particle morphology like a particle size and a particle shape is known to become a marker of mechanical behaviors of ground to indicate past seismic activities, for example. Therefore, the analysis of particle morphology is expected to enable to analyze of a mechanical behavior of seismic activities and ground strain. But it is difficult to evaluate only by analyzing the particle morphology of actual sample which comes from sampling. The main reason for this is the number of components in the sample. Almost of all samples contains does not one component but more. And the mechanical properties of each mineral species are different. In order to make evaluate simpler, a preprocessing by hydrogen peroxide solution to exclude organic materials from the sample has been done. But only this preprocessing does not change the situation where a sample contains several components. A fraction such as a sedimentation method is not also able to evaluate of single component because a particle size related to particle specific gravity closely under the situation that the sample contains several minerals.
We focused on a statistical Raman analysis here. The method measures particle morphology at first. Then Raman spectrum of each particle is acquired. We are able to classify to single material group using Raman spectrum information. And also, it is able to evaluate particle morphology of each material. It is possible to evaluate particle morphology focus on one specific mineral with using a statistical Raman analysis. And it is expected that more accurate simulations will be possible by evaluating the grain morphology of minerals whose mechanical properties are known using this method.
Oxygen is the most abundant element followed by silicon, according to the Clarke number. It shows the weight percent of the elements present near the ground surface. Oxygen is present in combination with other elements to form oxides. In other words, it means that oxides of silicon are the most abundant compound.
We analyzed the particle morphology in the mixture using a statistical Raman analysis method. Especially we tried to analyze the simplest silicon oxide SiO2 focused on. Here we report these evaluation results.
Material and Method
A Raman spectrum of silica sand (Silica sand 50-80mesh, Junsei Chemical Co., Ltd.) was acquired at first. The spectrum was identified SiO2. Several specific scattering peaks were obtained (466cm-1, 211cm-1, etc.) as shown in Fig.1. We planned to perform spectral correlation using the obtained spectra as a library. Morphologi 4ID (Malvern Panalytical, Spectris Co., Ltd.) was used for a statistical Raman analysis method.
The sample was dispersed a circular shape with a diameter of about 80 mm on a glass plate (180mmm x 110mm) using the SDU (Sample Dispersion Unit) attached to the device. Then, the particle size and particle shape of the dispersed particles were evaluated. After that, a Raman spectrum (excitation wavelength: 785nm) was obtained for each particle. Based on SiO2 spectrum in the library, we fractionated only SiO2 from the acquired spectrum and tried to analyzing to that particle morphology of SiO2.
Result
First of all, we tried to evaluate Tohoku Silica Sand No.8 as a sample. Each Raman spectra over than 500 particles was acquired after measuring particle size and particle shape for each particle. Then each spectrum was compared with a library spectrum. As a result, 88% based on volume of the sample was SiO2. About 85% of Tohoku Silica Sand No.8 is known to be SiO2. The results obtained here were almost same to this result.
When these particle sizes were compared, it was confirmed that there was no large difference between Tohoku silica sand and SiO2 of this sample. A particle shape, circularity was focused on here suggested that SiO2 was little bit more distorted shape than Tohoku silica sand (Table 1.).
Other results will be discussed on the day.
A particle morphology like a particle size and a particle shape is known to become a marker of mechanical behaviors of ground to indicate past seismic activities, for example. Therefore, the analysis of particle morphology is expected to enable to analyze of a mechanical behavior of seismic activities and ground strain. But it is difficult to evaluate only by analyzing the particle morphology of actual sample which comes from sampling. The main reason for this is the number of components in the sample. Almost of all samples contains does not one component but more. And the mechanical properties of each mineral species are different. In order to make evaluate simpler, a preprocessing by hydrogen peroxide solution to exclude organic materials from the sample has been done. But only this preprocessing does not change the situation where a sample contains several components. A fraction such as a sedimentation method is not also able to evaluate of single component because a particle size related to particle specific gravity closely under the situation that the sample contains several minerals.
We focused on a statistical Raman analysis here. The method measures particle morphology at first. Then Raman spectrum of each particle is acquired. We are able to classify to single material group using Raman spectrum information. And also, it is able to evaluate particle morphology of each material. It is possible to evaluate particle morphology focus on one specific mineral with using a statistical Raman analysis. And it is expected that more accurate simulations will be possible by evaluating the grain morphology of minerals whose mechanical properties are known using this method.
Oxygen is the most abundant element followed by silicon, according to the Clarke number. It shows the weight percent of the elements present near the ground surface. Oxygen is present in combination with other elements to form oxides. In other words, it means that oxides of silicon are the most abundant compound.
We analyzed the particle morphology in the mixture using a statistical Raman analysis method. Especially we tried to analyze the simplest silicon oxide SiO2 focused on. Here we report these evaluation results.
Material and Method
A Raman spectrum of silica sand (Silica sand 50-80mesh, Junsei Chemical Co., Ltd.) was acquired at first. The spectrum was identified SiO2. Several specific scattering peaks were obtained (466cm-1, 211cm-1, etc.) as shown in Fig.1. We planned to perform spectral correlation using the obtained spectra as a library. Morphologi 4ID (Malvern Panalytical, Spectris Co., Ltd.) was used for a statistical Raman analysis method.
The sample was dispersed a circular shape with a diameter of about 80 mm on a glass plate (180mmm x 110mm) using the SDU (Sample Dispersion Unit) attached to the device. Then, the particle size and particle shape of the dispersed particles were evaluated. After that, a Raman spectrum (excitation wavelength: 785nm) was obtained for each particle. Based on SiO2 spectrum in the library, we fractionated only SiO2 from the acquired spectrum and tried to analyzing to that particle morphology of SiO2.
Result
First of all, we tried to evaluate Tohoku Silica Sand No.8 as a sample. Each Raman spectra over than 500 particles was acquired after measuring particle size and particle shape for each particle. Then each spectrum was compared with a library spectrum. As a result, 88% based on volume of the sample was SiO2. About 85% of Tohoku Silica Sand No.8 is known to be SiO2. The results obtained here were almost same to this result.
When these particle sizes were compared, it was confirmed that there was no large difference between Tohoku silica sand and SiO2 of this sample. A particle shape, circularity was focused on here suggested that SiO2 was little bit more distorted shape than Tohoku silica sand (Table 1.).
Other results will be discussed on the day.