The use of spectroscopy in the field of biomedical science has increased in recent years. Many biological samples such as viruses and bacteria could be detected using FTIR spectroscopy in the MIR range. An important challenge arises when analyzing samples with low concentrations is that they might not be detected or accurately predicted within the capabilities of the instrument's signal-to-noise ratio. To overcome such challenge, absorption signal enhancement techniques can be used to improve the detectability of the samples. One of such techniques is the use of quantum dots (QDs) that are particles of crystal structure with sizes ranging from a few to tens of nanometers, which exhibit interesting optical properties. In this work, we apply a multi-scale modeling approach to describe the enhancement of QDs starting with an atomistic simulator to extract the absorption lines by solving Schrödinger's equation. Next, the optical constants of the QDs and biological samples are extracted using Kramer-Kronig's (KK) relations and Fresnel coefficients, followed by using Maxwell Garnett model in an effective medium approximation. Then, a transfer matrix method (TMM) is used to model layered media containing biological samples mixed with QDs. Using this theoretical description, an enhancement of about 2.5x in a transmission configuration is predicted by simulations for a sample with refractive index representing a saliva sample mixed with mercury telluride (HgTe) QDs. This model can be used to predict the enhancement of different types of QDs with different types of samples, which enhances the detection of various biological samples. Then, the QDs are synthesized experimentally using a two-step injection method. Finally, a practical measurement of the attenuated total reflection (ATR) spectrum in the range of 400-4000 cm -1 of a dried saliva sample mixed with HgTe QDs is carried showing an absorption enhancement of about 1.3x.
