A Conversion and Tribology Investigation on Used Ayurvedic Oil

2015 ◽  
Vol 813-814 ◽  
pp. 885-889 ◽  
Author(s):  
Ranganathan Balakumar ◽  
G. Sriram ◽  
S. Arumugam ◽  
V. Abhijith Koushal ◽  
Villa Sai Surya Venkatesh
Keyword(s):  
Fourier Transform ◽  
Methyl Ester ◽  
Ftir Spectroscopy ◽  
Diesel Fuel ◽  
Alternative Fuels ◽  
Fourier Transform Infrared ◽  
Wear Scar ◽  
Spectroscopy Analysis ◽  
Ic Engine ◽  
The Fourier Transform

Biofuel plays a major role in IC engine nowadays. Used Ayurvedic Oil (UAO) is one among the alternative fuels utilized. The preliminary property studies were carried out and the UAO had undergone simple Transesterification process to be converted to Used Ayurvedic Oil Methyl Ester (UAOME). The Fourier Transform Infrared (FTIR) spectroscopy analysis confirmed the UAO to UAOME conversion. The Trobological investigation on UAOME is also conducted using Four Ball Wear Tester. The results showed that lower wear scar was observed in UAOME comparatively with diesel. From the results it is clear that the UAO can be a novel partial substitute for diesel fuel.

Analysis of SCS-6 silicon carbide fibers by Fourier transform infrared spectroscopy

1997 ◽  
Vol 12 (2) ◽  
pp. 329-331
Author(s):  
S. Krishnamurthy
Keyword(s):  
Silicon Carbide ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Ftir Spectroscopy ◽  
Fourier Transform Infrared ◽  
Spectroscopy Analysis ◽  
Silicon Carbide Fibers ◽  
Low Levels ◽  
Reported Data ◽  
No Absorption

Fourier transform infrared (FTIR) spectroscopy analysis of SCS-6 silicon carbide fibers was performed to detect the presence of oxygen in the form of SiO2. The results showed infrared peaks corresponding to SiC fundamental lattice absorption as well as reflection. No absorption peak due to SiO2 was observed. These results are in agreement with previously reported data indicating low levels of oxygen in this fiber.

Detection of bloodstains using attenuated total reflectance-Fourier transform infrared spectroscopy supported with PCA and PCA–LDA

2021 ◽  
pp. 002580242110109
Author(s):  
Sweety Sharma ◽  
Rito Chophi ◽  
Jaskirandeep Kaur Jossan ◽  
Rajinder Singh
Keyword(s):  
Fourier Transform ◽  
Ftir Spectroscopy ◽  
Body Fluid ◽  
Due Process ◽  
Dna Analysis ◽  
Fourier Transform Infrared ◽  
Body Fluids ◽  
Attenuated Total Reflectance ◽  
Total Reflectance ◽  
Non Destructive

The most important task in a criminal investigation is to detect and identify the recovered biological stains beyond reasonable scientific doubt and preserve the sample for further DNA analysis. In the light of this fact, many presumptive and confirmatory tests are routinely employed in the forensic laboratories to determine the type of body fluid. However, the currently used techniques are specific to one type of body fluid and hence it cannot be utilized to differentiate multiple body fluids. Moreover, these tests consume the samples in due process, and thus it becomes a great limitation especially considering the fact that samples are recovered in minute quantity in forensic cases. Therefore, such limitations necessitate the use of non-destructive techniques that can be applied simultaneously to all types of bodily fluids and allow sample preservation for further analysis. In the current work, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy has been used to circumvent the aforementioned limitations. The important factors which could influence the detection of blood such as the effect of substrates, washing/chemical treatment, ageing, and dilution limits on the analysis of blood have been analysed. In addition, blood discrimination from non-blood substance (biological and non-biological in nature) has also been studied. Chemometric technique that is PCA–LDA has been used to discriminate blood from other body fluids and it resulted in 100% accurate classification. Furthermore, blood and non-blood substances including fake blood have also been classified into separate clusters with a 100% accuracy, sensitivity, and specificity. All-inclusive, this preliminary study substantiates the potential application of ATR-FTIR spectroscopy for the non-destructive identification of blood traces in simulated forensic casework conditions with 0% rate of false classification.

scholarly journals Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2506 ◽  
Author(s):  
Yunfeng Chen ◽  
Yue Chen ◽  
Xuping Feng ◽  
Xufeng Yang ◽  
Jinnuo Zhang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Spectroscopic Technique ◽  
Variety Identification ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Discriminant Models ◽  
The Fourier Transform ◽  
Better Than

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000–550 cm−1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

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