Terahertz time-domain spectroscopy of chondroitin sulfate

Self Cite

Terahertz time-domain spectroscopy (THz-TDS) is an effective coherent detection technique for deeply understanding the structures and functions of biomolecules. However, generally not full information in the whole THz range can be obtained due to the limited detection bandwidth (usually less than 5 THz) of the traditional THz-TDS systems. In this paper, effective THz absorption spectra in 0.5–10 THz range of five typical nucleobases of DNA/RNA are characterized with a super broadband THz detection technique, called the air-biased- coherent-detection (THz-ABCD) technique. Few unexpected characteristic absorption peaks appeared in the low-frequency region and meanwhile a series of anticipated characteristic absorption peaks are found in the high-frequency region. The fingerprint spectra of these nucleobases are helpful for further analysis on the vibration and twisting behavior of hydrogen bonds, van der Waals and electrostatic forces etc. between and within DNA/RNA biomolecules.

Section: Introductionmentioning

confidence: 99%

Characterization of Nucleobases in Broadband Terahertz Spectra from 0.5 to 10 THz with the Air-Biased-Coherent-Detection Technique

Yan

Sun

et al. 2019

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“…In recent decades, the first pilot applications appeared in different scientific and industrial areas. Nowadays, many different applications in the field of THz devices can be found for material scanning and food inspection [2,3], imaging [4], tissue analysis [5], security scanning [6], etc. Unlike the other inspection techniques based on X-rays and infrared radiation, the THz represent non-ionizing waves with low quantum energy, which cannot damage the inspected material permanently, and has good penetration ability.…”

Section: Introductionmentioning

confidence: 99%

A Novel System for Quasi-Continuous THz Signal Transmission and Reception

Sarjaš

Pongrac

Gleich

2022

This paper presents a novel system for generating and receiving quasi-continuous (QC) TeraHertz (THz) waves. A system design and theoretical foundation for QC-THz signal generation are presented. The proposed QC-THz system consists of commercially available photo-conductive antennas used for transmission and reception of THz waves and a custom-designed QC optical signal generator, which is based on a fast optical frequency sweep of a single telecom distributed-feedback laser diode and unbalanced optical fiber Michelson interferometer used for a high-frequency modulation. The theoretical model for the proposed system is presented and experimentally evaluated. The experimental results were compared to the state-of-the-art continuous-wave THz system. The comparison between the continuous-wave THz system and the proposed QC-THz system showed the ability to transmit and receive QC-THz waves up to 300 GHz. The upper-frequency limit is bounded by the length of the used Michelson interferometer. The presented design of THz signal generation has a potential for industrial application because it is cost-efficient and can be built using commercially available components.

“…Most of the data analysis in THz-FDS is undertaken by determining the attenuation and the phase shift of THz waves spread through the medium [ 15 ]. The detected absorption lines of a medium are measured and compared with the reference values, where complex permeability was estimated using the Kramers–Kronig relation [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Automated Inorganic Pigment Classification in Plastic Material Using Terahertz Spectroscopy

Sarjaš

Pongrac

Gleich

2021

This paper presents an automatic classification of plastic material’s inorganic pigment using terahertz spectroscopy and convolutional neural networks (CNN). The plastic materials were placed between the THz transmitter and receiver, and the acquired THz signals were classified using a supervised learning approach. A THz frequency band between 0.1–1.2 THz produced a one-dimensional (1D) vector that is almost impossible to classify directly using supervised learning. This paper proposes a novel pre-processing of 1D THz data that transforms 1D data into 2D data, which are processed efficiently using a convolutional neural network. The proposed pre-processing algorithm consists of four steps: peak detection, envelope extraction, and a down-sampling procedure. The last main step introduces the windowing with spectrum dilatation that reorders 1D data into 2D data that can be considered as an image. The spectrum dilation techniques ensure the classifier’s robustness by suppressing measurement bias, reducing the complexity of the THz dataset with negligible loss of accuracy, and speeding up the network classification. The experimental results showed that the proposed approach achieved high accuracy using a CNN classifier, and outperforms 1D classification of THz data using support vector machine, naive Bayes, and other popular classification algorithms.