Investigation of Dielectric Properties of Polymers and their Discrimination Using Terahertz Time-Domain Spectroscopy with Principal Component Analysis

Machine Learning in Polymer Research

Machine learning is increasingly being applied in polymer chemistry to link chemical structures to macroscopic properties of polymers and to identify chemical patterns in the polymer structures that help improve specific properties. To facilitate this, a chemical dataset needs to be translated into machine readable descriptors. However, limited and inadequately curated datasets, broad molecular weight distributions, and irregular polymer configurations pose significant challenges. Most off the shelf mathematical models often need refinement for specific applications. Addressing these challenges demand a close collaboration between chemists and mathematicians as chemists must formulate research questions in mathematical terms while mathematicians are required to refine models for specific applications. This review unites both disciplines to address dataset curation hurdles and highlight advances in polymer synthesis and modeling that enhance data availability. It then surveys ML approaches used to predict solid-state properties, solution behavior, composite performance, and emerging applications such as drug delivery and the polymer-biology interface. A perspective of the field is concluded and the importance of FAIR (findability, accessibility, interoperability, and reusability) data and the integration of polymer theory and data are discussed, and the thoughts on the machine-human interface are shared.

Model Fitting and Analysis of Dielectric Properties in Alcohol-Fuel Blends Using Terahertz and Gigahertz Spectroscopies

Alcohols from biological waste sources or renewable electricity (electrofuels) are gaining attention in hard-to-decarbonize sectors such as transport. Adding alcohol to conventional fuels has positive environmental effects on automotive applications, requiring minimal engine adjustments. Employing a combination of terahertz (THz) and gigahertz (GHz) spectroscopies, a comprehensive analysis of model fitting is presented for diesel-like fuels, pure alcohols (ethanol and n-butanol), and alcohol-fuel blends. Through the integration of data from both spectroscopic techniques, new Debye parameters are introduced to improve the accuracy of fitting for various fuels. This research demonstrates that THz spectroscopy alone is valuable for reasonable fits, particularly for alcohols. However, integrating THz and GHz spectroscopies leads to improved fitting, and to better potential to understand the behavior of fuel properties. In addition, the effect of alcohol concentration on the dielectric constant spectra in blends was investigated, highlighting the importance of molecular interactions. The results reveal a linear relationship between fitted parameters and alcohol content in the blends. However, the study acknowledges limitations, including challenges in achieving satisfactory fits at low alcohol concentrations and the necessity for assumptions in the modeling process. These findings provide a basis for future research and advances in fuel property modeling.

Identification of black plastics with terahertz time-domain spectroscopy and machine learning

Several optical spectroscopy and imaging techniques have already proven their ability to identify different plastic types found in household waste. However, most common optical techniques feasible for plastic sorting, struggle to measure black plastic objects due to the high absorption at visible and near-infrared wavelengths. In this study, 12 black samples of nine different materials have been characterized with Fourier-transform infrared spectroscopy (FTIR), hyperspectral imaging, and terahertz time-domain spectroscopy (THz-TDS). While FTIR validated the plastic types of the samples, the hyperspectral camera using visible and near-infrared wavelengths was challenged to measure the samples. The THz-TDS technique was successfully able to measure the samples without direct sample contact under ambient conditions. From the recorded terahertz waveforms the refractive index and absorption coefficient are extracted for all samples in the range from 0.4 to 1.0 THz. Subsequently, the obtained values were projected onto a two-dimensional map to discriminate the materials using the classifiers k-Nearest Neighbours, Bayes, and Support Vector Machines. A classification accuracy equal to unity was obtained, which proves the ability of THz-TDS to discriminate common black plastics.

Analytical Gas Sensing in the Terahertz Spectral Range

Exploiting the terahertz (THz) part of the electromagnetic spectrum is attracting attention in various scientific and applied disciplines worldwide. THz technology has also revealed its potential as an effective tool for gas analysis in astronomy, biomedicine and chemical analysis. Recently, it has also become important in environmental applications for monitoring hazardous and toxic gases in the atmosphere. This paper gives an overview of THz gas detection analytical methods for environmental and biomedical applications, starting with a brief introduction to THz technology and an explanation of the interaction of THz radiation with gaseous species and the atmosphere. The review focuses on several gaseous species and groups of air pollutants that have been or can be analysed by THz spectrometry. The review concludes that different but complementary THz detection methods allow unique detection, identification and quantification of gaseous and particulate air pollutants with high selectivity, specificity and sensitivity. THz detection methods also allow further technological improvements and open new application possibilities.

Chemometrics applied quantitative analysis of iron oxide mixtures by terahertz spectroscopy

A quantitative analysis method for corrosion products based on terahertz spectroscopy is proposed in this paper. Mixture samples consisting of three major corrosion products (magnetite, hematite, and goethite) were prepared in 51 different concentrations. The refractive index spectra measured by terahertz time-domain spectroscopy were projected to the 2D score diagram by performing principal component analysis. The Euclidean distances between the mixtures and pure analyte on the diagram were used to build a concentration prediction model. The results indicate that the established model can precisely predict the concentration of magnetite, which is essential for a stability evaluation of the corrosion system.

Quantitative determination of acacia honey adulteration by terahertz-frequency dielectric properties as an alternative technique

The dielectric characteristics in the terahertz region contribute to a revealing insight into the material components and provide intermolecular information. The dielectric properties of adulterated honey, described as the real and imaginary parts of the complex dielectric constant (Re[ε] and Im[ε]), were obtained from 0.3 to 1.5 THz. The relationship between invert syrup proportions and complex dielectric constants at different frequencies implied the possibility of using the dielectric property as an indicator of honey authenticity. The selected effective dielectric variables of Re[ε] and Im[ε] and their combination were chosen by stability competitive adaptive reweighted sampling (SCARS) algorithm and then used to establish PLS models. The accuracy and uncertainty result revealed SCARS-PLS model based on the combination of Re[ε] and Im[ε] is the best model relatively. These findings indicated the potential utility of this rapid, non-destructive, and on-site method for authenticity verification.

Terahertz imaging with room-temperature terahertz difference-frequency quantum-cascade laser sources

We demonstrate high-quality non-destructive imaging using a broadband terahertz quantum cascade laser source based on Cerenkov difference-frequency generation. The source exhibited ultra-broadband terahertz emission spectra, as well as a single-lobed Gaussian-like far-field pattern at -30 °C. These features allowed us to build a compact imaging system with a high spatial resolution, from which a nearly theoretical minimum beam spot size was obtained. As a result, we achieve well-resolved, high-contrast images of objects obscured by opaque materials. We also achieved terahertz imaging with the THz DFG-QCL operated at room temperature.

Far infrared spectroscopy of hydrogen bonding collective motions in complex molecular systems

Far infrared spectroscopy as a tool for the study of inter and intramolecular interactions in complex molecular structures.