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Related Concept Videos

IR Spectrum01:19

IR Spectrum

When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0% (complete...
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in the 3500–3100 cm−1 range. Even though both O−H and N−H bonds vibrate at a similar...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
Discrete Fourier Transform01:15

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...

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Related Experiment Video

Updated: Jun 29, 2026

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor
07:28

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor

Published on: August 30, 2012

Data encoding on terahertz signals for communication and sensing.

Lothar Möller1, John Federici, Alexander Sinyukov

  • 1Bell Laboratories, Alcatel-Lucent, 791 Holmdel-Keyport Road, Holmdel, New Jersey 07733, USA. lmoeller@alcatel-lucent.com

Optics Letters
|February 19, 2008
PubMed
Summary
This summary is machine-generated.

We demonstrate terahertz (THz) data modulation up to 1 Mbit/s by encoding signals with binary data. Bit error measurements show potential for higher data rates in optimized terahertz communication systems.

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Area of Science:

  • Terahertz (THz) science and technology
  • Optical communications
  • Signal processing

Background:

  • Terahertz (THz) frequencies offer potential for high-bandwidth wireless communication.
  • Data modulation techniques are crucial for transmitting information over THz signals.
  • Previous research has explored various aspects of THz communication, but achieving reliable data modulation at significant rates remains an active area of investigation.

Purpose of the Study:

  • To demonstrate and analyze data modulation of terahertz (THz) signals.
  • To investigate different modulation formats for THz communication.
  • To estimate the maximum achievable data rates for an optimized THz system.

Main Methods:

  • Encoding THz pulse trains with pseudorandom binary data using phase and amplitude modulation.
  • Transmitting modulated THz signals over a short distance.
  • Detecting the transmitted signals and performing bit error rate measurements.

Main Results:

  • Successful demonstration of data modulation for THz signals in the 1 Mbit/s range.
  • Generation and analysis of different modulation formats.
  • Characterization of the communication channel through bit error measurements.

Conclusions:

  • Data modulation of THz signals is feasible at rates up to 1 Mbit/s.
  • Experimental results provide insights into the performance of different modulation schemes.
  • The study estimates the potential for higher data rates in optimized THz communication systems.