THz Spectra Research Articles

Roller compaction: Measuring ribbon porosity by terahertz spectroscopy and machine learning

Roller compaction is a crucial unit operation in pharmaceutical manufacturing, with its ribbon porosity widely recognised as a critical quality attribute. Terahertz spectroscopy has emerged as a fast and non-destructive technique to measure porosity in pharmaceutical products. From a sensing perspective, the irregular shape and uneven surface of fragmented ribbon pieces can affect the accuracy and precision of the measurements, particularly for techniques that probe only a small sampling volume. It is known that the porosity is not uniform within the ribbon structure, with variations expected across the width of the ribbon and in the microstructure corresponding to its surface texture. However, typical pharmaceutical analysis methods, such as envelope density, only report an average bulk porosity, are slow to operate and limited in accuracy. To address this challenge, we developed and trained convolutional neural network models using THz spectra as input to classify four types of topography typically encountered in ribbons: ridge, valley, flat plane and edge points. The classifiers achieved 91% validation accuracy in both identifying outliers and differentiating between ribbons of smooth and knurled surfaces. For the more challenging task of distinguishing between the ridges and valleys of knurled surfaces, an 81% testing accuracy was achieved. Once each measurement is paired with its topography, resolving the density distribution within the sample is possible. This data can be combined to arrive at an average bulk porosity value compatible with conventional pharmaceutical analysis.

Optimized terahertz generation in BNA organic crystals with chirped Ti:sapphire laser pulses.

We report on the efficient generation of intense terahertz radiation from the organic crystal N-benzyl-2-methyl-4-nitroaniline pumped by chirped Ti:sapphire femtosecond laser pulses. The THz energy and spectrum as a function of the pump fluence and duration of the chirped laser pulses are studied systematically. For the appropriate positively chirped pump pulses, a significant boost in the THz generation efficiency by a factor of around 2.5 is achieved, and the enhancement of high-frequency components (>1 THz) shortens the THz pulse duration. Via complete characterization of THz properties and transmitted laser spectra, this nonlinear behavior is attributed to the extended effective interaction length for phase matching as a result of the self-phase modulation of the intense pump laser pulses. Numerical calculations well reproduce the experimental observation. Our results demonstrate a robust, efficient, strong-field (up to several MV/cm) THz source using the common sub-10 mJ and sub-100 fs Ti:sapphire laser systems without optical parametric amplifiers.

Component analysis of gas mixtures by THz spectra based on machine learning with training on mixtures or individual components data

Component analysis of gas mixtures by THz spectra based on machine learning with training on mixtures or individual components data

Polarization insensitive and wideband terahertz absorber using high-impedance resistive material of RuO2

This paper introduces a novel, cost-effective solution designed to achieve large absorption bandwidth within the THz spectrum employing a miniaturized, single-layer metamaterial structure. The designed structure features a single circular ring composed of an ohmic resistive sheet with notably higher sheet resistance than traditional metallic resonators. This distinctive design is implemented on a lossy dielectric polyimide substrate with a backing of metallic gold. Our developed absorbing structure demonstrates the capability to achieve a substantial absorption bandwidth ranging from 3.78 to 4.25 THz, maintaining a consistent absorption rate of over 90%. Moreover, we conducted an analysis to assess its absorption performance under various sheet resistance values within the top layer. Additionally, we characterized its angular stability and polarization insensitivity through oblique incident and polarization angle analysis. Finally, an RLC circuital and interference theory approach is adopted to justify its simulated results. The proposed absorber shows potential for a broad spectrum of applications, encompassing communication, imaging, and diverse integrated circuits operating within the THz band.

An ultra broadband metamaterial absorber based on metal-dielectric-metal technology for THz spectrum

This paper introduces a novel ultra-broadband Metamaterial Absorber (UBMA) demonstrating significant absorption capabilities across a wide terahertz frequency range from 2.42 THz to 6.11 THz. The 3.7 THz bandwidth represents 87% of the central frequency. The proposed UBMA comprises three layers: a star-shaped metal patch on top, a dielectric substrate in the middle, and a metallic ground plane below. Simulations using CST Microwave Studio software reveal that the design achieves high absorption at five distinct frequencies: 2.47, 3.45, 4.89, 6.01, and 6.87 THz, with absorption rates of 99% for the first four peaks and 90% for the fifth peak. The study of electric field and surface current distribution provides insights into the absorption mechanism. While the UBMA exhibits polarization-independent performance, its angular response shows some sensitivity to the incident angle, especially beyond 30° Despite this, the absorber maintains over 70% absorptivity up to a 45° incidence angle for both TE and TM polarizations within specific frequency ranges. The simple structure combined with high absorption efficiency makes the UBMA suitable for THz imaging, detection, and stealth applications, although its angular sensitivity must be considered for certain applications.

Tunable polymer-based ternary one-dimensional photonic crystal with PVDF piezoelectric layer in the THz spectrum

This research introduces an innovative method for crafting adjustable one-dimensional photonic crystals by integrating a polyvinylidene fluoride (PVDF) piezoelectric layer into a ternary polymer structure. The incorporation of PVDF as a piezoelectric polymer in the photonic crystal allows for the simulation of an electric field sensitive photonic crystal. Two structures of the photonic crystal are examined, one with a defect layer and one without, while the impact of piezoelectric parameters on the transmission spectrum is scrutinized. The computational outcomes clearly demonstrate that the photonic band gap can be efficiently modified by applying an external electric field in the THz frequency. Incorporating a defect mode that is sensitive to electric field allows for the creation of a narrow bandpass region (∼ 5 GHz) within a bandgap. This narrow region has the capacity to be precisely modified through the application of an external electrical field. This distinctive design proposal provides a means to govern and modify the optical characteristics of the crystal, rendering it a promising candidate for diverse photonic applications.

Roadmap on specialty optical fibers

Abstract Optical fibers, long an enabling technology for telecommunications, are proving to play a central role in a growing number of modern applications, starting from high speed broad band internet to medical surgery and entering across the entire spectrum of scientific, military, industrial and commercial applications. Specialty optical fibers either special waveguide structure or novel material composition becomes heart of all fiber based advanced photonics devices and components. This rapidly evolving field calls on the expertise and skills of a broad set of different disciplines: materials science, ceramic engineering, optics, electrical engineering, physics, polymer chemistry, and several others. This roadmap on specialty optical fibers addresses different technologies and application areas. It is constituted by fourteen contributions authored by world-leading experts, providing insight into the current state-of-the-art and the challenges their respective fields face. Some articles address the area of multimode fibers, including the nonlinear effects occurring in them. Several other articles are dedicated to doped, plastic, and soft-glass fibers. Large mode area fibers, hollow-core fibers, and nanostructured fibers are also described in different sections. The use of some of such fibers for optical amplification and to realize several kinds of optical sources - including lasers, single photon sources and supercontinuum sources - is described in some other sections. Different approaches to satisfy applications at visible, infrared and THz spectra regions are also discussed. Throughout the roadmap there is an attempt to foresee and to suggest future directions in this particularly dynamic area of optical fiber technology.

Design and characterization of novel broadband chalcone-based THz optical crystals

By combining extended π-conjugated structures and halogen substituents, two novel chalcone-based optical THz crystals were designed: CBC (C22H17ClO2, Pc) and TFBC (C23H17F3O2, P21). These crystals were synthesized and successfully grown using the solution evaporation method. The effects of different types and quantities of halogen substituents on hydrogen bonding interactions, molecular alignment, and nonlinear strength were analyzed. The second harmonic generation (SHG) efficiency, thermal stability, transmission spectra, dielectric constant, and THz generation of the crystals were characterized. Theoretical calculations were conducted to determine the hyperpolarizability, band gap, density of states, and nonlinear optical coefficients of the crystals. The results showed that the synthesized crystals exhibited higher transparency (≥85%) and SHG efficiencies of 9.5 times and 6.2 times that of standard potassium dihydrogen phosphate (KDP), respectively, compared to previously reported chalcone NLO crystals. For the first time, the THz generation efficiency of the two crystals was confirmed through the optical rectification method, with TFBC demonstrating a wider THz spectrum range compared to CBC.

Highly sensitive photonic crystal fiber chemical sensor for detecting carbon disulfide and bromoform in the THz regime

In this study, an innovative photonic crystal fiber (PCF) designed specifically for the detection of carbon disulfide and bromoform liquid chemicals within the THz frequency range was introduced. The PCF’s structural design was achieved using the Finite Element Method (FEM) and Perfectly Matched Layer (PML) boundary conditions within COMSOL Multiphysics, ensuring precision through appropriate numerical parameters. Six distinct configurations were developed, incorporating circular, square, rectangular slotted, benzene-shaped circular, and two elliptical core designs, as well as an eight-elliptical core design. The PCF models were constructed utilizing the dielectric material TOPAS for accurate simulation and analysis. Various crucial parameters of the proposed PCF were examined across a wide THz spectrum spanning from 0.2 to 1.2 THz. The PCF model exhibited a peak output at the operating frequency of 0.8 THz for the square-shaped core design, achieving a relative sensitivity of 96.891% for bromoform and 95.603% for carbon disulfide. Remarkably low material losses of 0.0081104 cm−1 for bromoform and 0.006703 cm−1 for carbon disulfide were observed, along with a core power fraction of 93.107% for bromoform and 94.263% for carbon disulfide. The effective area was determined to be 1.77 × 10−07 μm2 for bromoform and 1.70 × 10−07 μm2 for carbon disulfide, while the confinement loss measured 2.25 × 10−17 dB/cm for bromoform and 4.76 × 10−17 dB/cm for carbon disulfide. These superior attributes strongly suggest that this model will be crucial in applications like supercontinuum generation, sensing, and biomedical imaging.

Multi-Antenna Array-Based Massive MIMO for B5G/6G: State of the Art, Challenges, and Future Research Directions

This comprehensive article explores the massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, cell-free MIMO, and security considerations, this article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights the challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of federated learning in M-MIMO systems. By examining these cutting-edge developments, this article aims to advance knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Investigation of Nerve Fiber Network in THz Spectrum Range

The behavior of the nerve fiber system of the spinal cord of animals in the THz wavelength range (0.1-3 THz) was experimentally studied using a time domain spectrometer. Terahertz wave transmittance of nerve tissue is investigated, when DC voltage is applied to the sample. It has been shown that when a constant voltage is applied along the nerve fibers (also in the absence of voltage), no noticeable changes occur in the transmitted THz wave, regardless of the orientation of the sample relative to the THz E-field vector. Significant changes in the electrodynamic properties of the sample were observed when the nerve fibers were parallel to the THz E-field vector and the applied voltage was perpendicular to the nerve fibers, particularly, resonant absorption was observed at frequencies of 0.6 THz and 2 THz.

Tunable THz absorbers based on LC-tuned Yagi-Uda antennas

ABSTRACT This study examines the structural configuration of Yagi-Uda micro-antenna arrays, the resonant properties of which are tunable through nematic liquid crystals in the terahertz spectral region. Reorienting liquid crystals by varying the voltage applied to the liquid crystal cell allows for control of the reflectance and absorbance amplitudes within the 7–12 THz operational frequency range. The reflectance and absorbance control ranges are around 50–60% across most of the frequency range, notably reaching approximately 90% at 11.1 THz. The optimal operational voltage ranges for the presented structure were approximately 1.1–1.9 V at the lower frequencies and 1.4–2.5 V at higher frequencies. This research highlights the potential of such metamaterial designs for efficient and adaptable applications in the THz spectrum.

Effect of the boson peak and the ionic resonance in the dielectric properties of silicate materials at mm-wave and THz frequencies

In this paper, a broadband measurement of the dielectric properties of silicates has been done to cover the seldom characterized mm-wave spectrum and the low THz spectrum. The dielectric properties, i.e. loss and permittivity, show a frequency independent response up to approximately 40 GHz and the loss monotonically increases to the THz frequency range. Two resonance peaks appear at THz frequencies: the first is the boson peak, and the second one corresponds to the ionic resonance of the network former, which in this case is silicon. Even though the materials belong to different groups in the silicate family (crystalline and non-crystalline, with different levels of purity), they seem to have the same overall tendency in the dielectric properties. Argand plots are used for the first time at THz frequencies to provide physical insight into the boson peak and ionic resonance. The complex plane analysis reveals details on the polarization mechanisms underlying silicate network vibrations through direct visualization of their characteristic signatures, and simplifies the process of modeling the dielectric response, leading to a better fit.

Impact of sole layer duple substrates on GA-based optimised graphene antennas for THz applications

The widespread use of graphene patch antennas is escalating as evidence of their applicability in areas like 6 G communications and THz spectroscopy. Geometric uncertainty and fabrication issues while downsizing makes terahertz antenna design problematic. Graphene's electromagnetic and mechanical qualities make it ideal for miniaturizing antennas for Terahertz use. In the THz spectrum, a graphene antenna requires careful dielectric material selection since performance fall, especially efficiency. This paper compares dual band multi-layered genetic algorithm-based optimized antennas for the THz applications, especially spectroscopy and 6 G utilizing sole layer duple substrates concept, i.e., two distinct substrates at the same level between the ground and patch. Different antennas are designed using various substrates like Rogers RO3010, RO3210, RT5880, RT5880LZ, TMM 13i, Taconic TLY-3, RF-10, Silicon, & Teflon. Two segments of four antennas are planned; one has silicon as a common substrate with four additional materials, and another has Teflon. The proposed antenna's performance is assessed in terms of bandwidth, beamwidth, directivity, efficiency, gain, radiation pattern, return loss, and VSWR. The results reveal that Silicon and Rogers RT5880 LZ substrates-based antenna perform better in a segment I, with bandwidth (GHz) of 150.1 and 156.9, directivity (dBi) of 5.93 and 4.23, efficiency (%) of 76.65 and 78.98, and gain (dB) of 4.97 and 3.3. While in segment II, Teflon and Taconic RF-10-based antenna perform better with features 158 and 198 bandwidth, 6.43 and 4.43 directivity, 74 and 83 efficiency, and 4.67 and 3.65 gain.

THz spectroscopy on the amino acids L-serine and L-cysteine.

We present a detailed study on the temperature-dependent THz spectra of the polycrystalline amino acids, L-serine and L-cysteine, for wavenumbers from 20 to 120cm-1 and temperatures from 4 to 300K. Even though the structure of these two amino acids is very similar, with a sulfur atom in the side chain of cysteine instead of an oxygen atom in serine, the excitation spectra are drastically different. Obviously, the vibrational dynamics strongly depend on the ability of cysteine to form sulfur-hydrogen bonds. In addition, cysteine undergoes an order-disorder type phase transition close to 80K, documented by additional specific heat experiments, with accompanying anomalies in the THz results. On increasing temperatures, well-defined vibrational excitations exhibit significant shifts in the eigenfrequencies with concomitant line-broadening yielding partly overlapping modes. Interestingly, several modes completely lose all their dipolar strength and are unobservable under ambient conditions. Comparing the recent results to the published work utilizing THz, Raman, and neutron-scattering techniques, as well as with abinitio simulations, we aim at a consistent analysis of the results ascribing certain eigenfrequencies to distinct collective lattice modes. We document that THz spectra can be used to fine-tune the parameters of model calculations and as fingerprint properties of certain amino acids. In addition, we analyzed the low-temperature heat capacity of both the compounds and detected strong excess contributions compared to the canonical Debye behavior of crystalline solids, indicating soft excitations and a strongly enhanced phonon-density of states at low frequencies.

Terahertz Time-Domain Spectroscopy of Blood Serum for Differentiation of Glioblastoma and Traumatic Brain Injury

The possibility of the differentiation of glioblastoma from traumatic brain injury through blood serum analysis by terahertz time-domain spectroscopy and machine learning was studied using a small animal model. Samples of a culture medium and a U87 human glioblastoma cell suspension in the culture medium were injected into the subcortical brain structures of groups of mice referred to as the culture medium injection groups and glioblastoma groups, accordingly. Blood serum samples were collected in the first, second, and third weeks after the injection, and their terahertz transmission spectra were measured. The injection caused acute inflammation in the brain during the first week, so the culture medium injection group in the first week of the experiment corresponded to a traumatic brain injury state. In the third week of the experiment, acute inflammation practically disappeared in the culture medium injection groups. At the same time, the glioblastoma group subjected to a U87 human glioblastoma cell injection had the largest tumor size. The THz spectra were analyzed using two dimensionality reduction algorithms (principal component analysis and t-distributed Stochastic Neighbor Embedding) and three classification algorithms (Support Vector Machine, Random Forest, and Extreme Gradient Boosting Machine). Constructed prediction data models were verified using 10-fold cross-validation, the receiver operational characteristic curve, and a corresponding area under the curve analysis. The proposed machine learning pipeline allowed for distinguishing the traumatic brain injury group from the glioblastoma group with 95% sensitivity, 100% specificity, and 97% accuracy with the Extreme Gradient Boosting Machine. The most informative features for these groups’ differentiation were 0.37, 0.40, 0.55, 0.60, 0.70, and 0.90 THz. Thus, an analysis of mouse blood serum using terahertz time-domain spectroscopy and machine learning makes it possible to differentiate glioblastoma from traumatic brain injury.

Squeezing formaldehyde into C60 fullerene

The cavity inside fullerene C60 provides a highly symmetric and inert environment for housing atoms and small molecules. Here we report the encapsulation of formaldehyde inside C60 by molecular surgery, yielding the supermolecular complex CH2O@C60, despite the 4.4 Å van der Waals length of CH2O exceeding the 3.7 Å internal diameter of C60. The presence of CH2O significantly reduces the cage HOMO-LUMO gap. Nuclear spin-spin couplings are observed between the fullerene host and the formaldehyde guest. The rapid spin-lattice relaxation of the formaldehyde 13C nuclei is attributed to a dominant spin-rotation mechanism. Despite being squeezed so tightly, the encapsulated formaldehyde molecules rotate freely about their long axes even at cryogenic temperatures, allowing observation of the ortho-to-para spin isomer conversion by infrared spectroscopy. The particle in a box nature of the system is demonstrated by the observation of two quantised translational modes in the cryogenic THz spectra.

Interval-based sparse ensemble multi-class classification algorithm for terahertz data

Terahertz time-domain spectroscopy (THz-TDS) has been widely used for food and drug identification. The classification information of a THz spectrum usually does not exist in the whole spectral band but exists only in one or several small intervals. Therefore, feature selection is indispensable in THz-based substance identification. However, most THz-based identification methods empirically intercept the low-frequency band of the THz absorption coefficients for analysis. In order to adaptively find out important intervals of the THz spectra, an interval-based sparse ensemble multi-class classifier (ISEMCC) for THz spectral data classification is proposed. In ISEMCC, the THz spectra are first divided into several small intervals through window sliding. Then the data of training samples in each interval are extracted to train some base classifiers. Finally, a final robust classifier is obtained through a nonnegative sparse combination of these trained base classifiers. With l1 -norm, two objective functions that based on Mean Square Error (MSE) and Cross Entropy (CE) are established. For these two objective functions, two iterative algorithms based on the Alternating Direction Method of Multipliers (ADMM) and Gradient Descent (GD) are built respectively. ISEMCC transforms the problem of interval feature selection and decision-level fusion into a nonnegative sparse optimization problem. The sparse constraint ensures only a few important spectral segments are selected. In order to verify the performance of the proposed algorithm, comparative experiments on identifying the origin of Bupleurum and the harvesting year of Tangerine peel are carried out. The base classifiers used by ISEMCC are Support Vector Machine (SVM) and Decision Tree (DT). The experimental results demonstrate that the proposed algorithm outperforms six typical classifiers, including Random Forest (RF), AdaBoost, RUSBoost, ExtraTree, and the two base classifiers, in terms of classification accuracy.

Efficient Identification of Crude Oil via Combined Terahertz Time-Domain Spectroscopy and Machine Learning

The quality of crude oil varies significantly according to its geographical origin. The efficient identification of the source region of crude oil is pivotal for petroleum trade and processing. However, current methods, such as mass spectrometry and fluorescence spectroscopy, suffer problems such as complex sample preparation and a long characterization time, which restrict their efficiency. In this work, by combining terahertz time-domain spectroscopy (THz-TDS) and a machine learning analysis of the spectra, an efficient workflow for the accurate and fast identification of crude oil was established. Based on THz-TDS of 83 crude oil samples obtained from six countries, a machine learning protocol involving the dimension reduction of spectra and classification was developed to identify the geological origins of crude oil, with an overall accuracy of 96.33%. This work demonstrates that THz spectra combined with a modern numerical scheme analysis can be readily employed to categorize crude oil products efficiently.

THz spectrum processing method based on optimal wavelet selection.

Terahertz spectrum is easily interfered by system noise and water-vapor absorption. In order to obtain high quality spectrum and better prediction accuracy in qualitative and quantitative analysis model, different wavelet basis functions and levels of decompositions are employed to perform denoising processing. In this study, the terahertz spectra of wheat samples are denoised using wavelet transform. The compound evaluation indicators (T) are used for systematically analyzing the quality effect of wavelet transform in terahertz spectrum preprocessing. By comparing the optimal denoising effects of different wavelet families, the wavelets of coiflets and symlets are more suitable for terahertz spectrum denoising processing than the wavelets of fejer-korovkin and daubechies, and the performance of symlets 8 wavelet basis function with 4-level decomposition is the optimum. The results show that the proposed method can select the optimal wavelet basis function and decomposition level of wavelet denoising processing in the field of terahertz spectrum analysis.