We explored two ways to enhance light matter interaction in the THz range through spatial confinement of the electric field. Firstly, a broadband metallic waveguide with low losses and low dispersion used in a TDS setup to measure samples with volume as low as 200pL. In this proceeding, we explore a resonant structure allowing for tighter confinement at the price of narrower bandwidth. Split ring resonators are resonant structures analogous to LC circuit, where the electric field is confined in the capacitive part of the device. We fabricated SRRs with capacitive gaps as small as 30nm for measurements on extremely low volume sample such as macromolecules or viruses.
Terahertz spectroscopy provides information on the motion of the charges in a sample at a picosecond scale. To recover this information from Terahertz time-domain spectroscopy (THz-TDS), one usually extracts the experimental refractive index then fits these curves. This approach suffers from several limitations, among them the difficulty to compare models of motions, provide the error bar associated with the extracted magnitude and a resolution limitation coming from the Fourier criteria of the fast Fourier transform. By adopting a Bayesian framework taking into account the experimental uncertainties and directly fitting the time-domain trace, we overcame these limitations. When correlated and epistemic uncertainties/noise are present, the algorithm considers its distribution as part of the data to fit and can mistake it for real physical features. Hence, it offers poor discrimination between good models and bad ones. After a thorough analysis of the experimental noise, we developed a preprocessing software removing epistemic noise on the time traces and providing an estimate of the noise correlation matrix (generalization of the standard deviation). It allows the proper weighting of the error function of the fit using these uncertainties and therefore the derivation of the Akaike information criteria, a metric enabling to calculate the most probable model from a set of models one wants to compare. In addition, by being in the time domain we avoid the Fourier criteria for the resolution and thus could get information on experimental lines down to 30 MHz with a commercial THz-TDS system.
The Terahertz (THz) technology has now reached a level of maturation, which allows its uses beyond its core domains of application (telecom and imaging for security or healthcare). Vibrational spectroscopy in the THz range is employed in various fields and is specifically promising in (μ)biology. Indeed, the probed vibrational states extend over several nanometers and give a signature of the sample 3D structure at the nanoscale. This is particularly salient for macromolecules (proteins, DNA and RNA strands etc.) since, on one hand, their 3D structure is very difficult to probe in physiological condition with other techniques, and on the other hand, this structure determines their function and is consequently of utmost importance for the living. A major hurdle still arises when applying THz spectroscopy on biological or macromolecular samples. The samples are generally smaller than the THz wavelength, which requires concentrating the THz field in the sample. Solutions aimed at tackling this challenge by using μ/nano technology of THz field concentration and a proper data analysis will be presented.
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