Terahertz Spectra Research Articles

Non-destructive detection of adulteration of weight-loss drugs in the field of spectral feature fusion

To crack down on criminals using the delivery channel to transport weight-loss drugs doped with toxic and harmful nonfood raw materials, a pattern recognition method of weight-loss drugs based on terahertz time-domain spectroscopy was proposed. Compared with traditional methods, terahertz spectrum had high signal-to-noise ratio in time-domain spectrum, which was fast, time-saving and lossless. In this study, seven kinds of weight-loss drugs were selected as experimental samples. The terahertz time-domain spectra of the samples were collected. Three characteristic frequency intervals of 0–0.19, 1.75–2.14 and 2.23–2.5 (THz) were found by automatic peak finder. The characteristic frequency intervals were processed by Hilbert transform, Butterworth low-pass filter, fast Fourier transform low-pass filter and the first-order derivatives after standard normal transform, the feature data was fused with the original spectra, and the original data and the data fused by the four methods were classified and recognized by particle swarm optimization least squares support vector machine and extreme learning machine model optimized by Cuckoo algorithm. The experimental results showed that the particle swarm optimization least squares support vector machine model had the best recognition effect on the spectral feature fusion data after Hilbert transform, and the accuracy can reach 100 %. It had a certain reference significance for the identification of weight-loss drugs in forensic science.

Effects of Morphology and Solvent/Temperature on THz Spectra: Take Nucleosides as Example.

Water molecules were easy to combine with organic molecules and embed into the lattice of solid molecules to form a hydrate. Compared with anhydrous compounds, a hydrate has completely different physical and chemical properties. In this paper, terahertz (THz) spectra of five nucleosides in the solid and liquid phases were studied experimentally by Fourier-transform infrared spectroscopy (FTIR) in the frequency of 0.5-9 THz. In addition, the lattice energy, geometric structure, and vibration spectrum of the molecular crystal of the nucleosides were analyzed theoretically by the generalized energy-based fragmentation approach under periodic boundary conditions (denoted as PBC-GEBF). Furthermore, different nucleoside molecular morphology (monomer, polymer, and crystal), solvent (implicit and explicit water), and temperature/theoretical model effect on the THz spectra were mainly investigated. It was found that in the low-frequency band, the vibrational modes were generally originated from the collective vibration of all molecules involved (more than 99% of them were vibration; only less than 1% of them were rotation and translation), which can reflect the molecular structure and spatial distribution of different substances. The Gibbs free energy of thymidine monomer, dimer, tetramer, and crystal was studied. It was found that the cell-stacking energy had the greatest influence on the spectrum, indicating that only the crystal structure constrained by the periodic boundary conditions could well describe the experimental results. In addition, hydrophobic forces dominated the formation of new chemical bonds and strong inter-molecular interactions; the free water had little contribution to the THz spectrum of nucleosides, while crystalline water had a great influence on the spectrum.

Graphene surface modes enabling terahertz pulling force.

Plasmonic substrates are widely reported for their use in the manipulation of sub-wavelength particles. Here we analyze the optical force in the terahertz (THz) spectrum acting on a dielectric nanoparticle when located close to a graphene monolayer. When lying on a dielectric planar substrate, the graphene sheet enables the nano-sized scatterer to excite a surface plasmon (SP) well confined on the dielectric surface. Under quite general conditions, large pulling forces can be exerted on the particle as a consequence of conservation of linear momentum and a self-action effect. Our results show that the pulling force intensity critically depends on the particle shape and orientation. The low heat dissipation of graphene SPs paves the way for the development of a novel plasmonic tweezer for applications involving biospecimen manipulation in the THz region.

Terahertz Wave Propagation Characteristics in Graded Teflon Based Solid-Core Photonic Crystal Fibre

In the past few years, photonic crystal fibre (PCF) in the Terahertz spectrum is drawing significant attention because of its multifaceted applications in high-speed data communication, spectroscopy, sensing, etc. The proposed PCF structure is based on a Teflon solid core surrounded by porous cladding. Teflon has been used as a background material because of its high flexibility and the possibility of making longer PCFs, which is capable of guiding waves in the THz region. The porous cladding consists of circular air-holes positioned hexagonally whose diameters increase with each subsequent layer keeping the pitch constant thus providing a graded-index profile. The diameters of air holes in each hexagonal layer are 1 mm, 1.2 mm and 1.5 mm respectively, maintaining a constant pitch of 2mm and a perfectly matched layer (PML) thickness of 3mm. We have examined the transmission characteristics of the proposed profile in the frequency range of 0.8 THz to 2.5 THz. The modal solution of the profile is solved using the Finite Element Method based on COMSOL Multiphysics version 5.5. Using the graded-index profile, we have obtained a large effective modal area of around 5.6 mm2 at 1 THz and a low confinement loss of 2.25 × 10−4 dB/km at the same frequency. Due to this large effective modal area, we get higher damage threshold and weaker non-linear effects, making it suitable for high power applications.

Application of terahertz spectroscopy in medical microbiological detection

In recent years, pathogenic bacteria and other microorganisms are still a very important aspect of human health. Nowadays, with the rapid development of information science, it has become a new research idea to explore scientific problems from the perspective of interdisciplinary integration. The research on the biomedical application of Terahertz (THz) wave is a hot frontier of the intersection between physical optics and bio-medicine. Based on the background of terahertz spectrum application, this paper introduces the application and progress of terahertz technology in medical microorganism detection, analyzes the characteristics of terahertz and the application technology in medical microorganism detection. Secondly, it tries to comprehensively summarize the application research results of terahertz technology in the field of microbial bio-medicine. Finally, it analyzes and prospects the shortcomings and advantages of the application of terahertz technology in the field of biomedical science.

Detection of biomarkers using terahertz metasurface sensors and machine learning.

To achieve classification and concentration detection of cancer biomarkers, we propose a method that combines terahertz (THz) spectroscopy, metasurface sensors, and machine learning. A metasurface sensor suitable for biomarker detection was designed and fabricated with five resonance frequencies in the range of 0.3-0.9THz. We collected biomarkers of five types and nine concentrations at 100 sets of time-domain spectra per concentration. The spectrum is processed by noise reduction and fast Fourier transform to obtain the frequency-domain spectrum. Five machine learning algorithms are used to analyze time- and frequency-domain spectra and ascertain which algorithm is more suitable for the classification of the biomarker THz spectrum. Experimental results show that random forest can better distinguish five biomarkers with an accuracy of 0.984 for the time-domain spectrum. For the frequency-domain spectrum, the support vector machine performs better, with an accuracy of 0.989. For biomarkers at different concentrations, we used linear regression to fit the relationship between biomarker concentration and frequency shift. Experimental results show that machine learning can distinguish different biomarker species and their concentrations by the THz spectrum. This work provides an idea and data processing method for the application of THz technology in biomedical detection.

Terahertz Vibrational Modes of Sodium Magnesium Chlorophyllin and Chlorophyll in Plant Leaves

The low-frequency (terahertz) vibrational spectroscopy has been investigated experimentally for two chlorophyll species, Chl-a and one of its magnesium derivatives (Chl-Mg-Na). The combination of terahertz time-domain spectroscopy and Fourier transform infrared spectroscopy has enabled a broad frequency range to be covered (0.2 to 18 THz). For Chl-Mg-Na, the terahertz spectra show clear and well-marked features at 1.44, 1.64, and 1.83 THz dominated by intermolecular interactions. The frequency dependent refractive index and absorption coefficient of Chl-Mg-Na were both determined using the Fit@TDS software. Below 1.0 THz, a refractive index of 2.09 was measured. In order to acquire further understanding of the observed vibrational modes, a detailed study of the temperature dependence of the line positions of the lowest modes in Chl-Mg-Na was performed. As the temperature was increased from 88 K to 298 K, the feature at 1.83 THz experienced a notable red shift of frequency and line shape broadening, whereas the feature at 1.44 THz showed little change. These results suggest that the 1.83 THz feature is dominated by intermolecular motions occurring over the crystalline unit cell of the Chl-Mg-Na molecular crystal. Finally, terahertz time-domain spectroscopy was used to acquire the spectra of an ornamental plant bearing yellow-green variegated leaves (ivy, Aureomarginata variety), the yellow sectors having lower chlorophyll content compared to the green sectors. In dehydrated green tissue, the chlorophyll molecules showed well-marked intermolecular vibrational modes at 1.86 THz, indicating that chlorophyll molecules are prone to packing with an ordered molecular arrangement. These results demonstrate the potential application of THz spectroscopy in the field of agronomy.

Research on a nondestructive model for the detection of the nitrogen content of tomato.

The timely detection of information on crop nutrition is of great significance for improving the production efficiency of facility crops. In this study, the terahertz (THz) spectral information of tomato plant leaves with different nitrogen levels was obtained. The noise reduction of the THz spectral data was then carried out by using the Savitzky-Golay (S-G) smoothing algorithm. The sample sets were then analyzed by using Kennard-Stone (KS) and random sampling (RS) methods, respectively. The KS algorithm was optimized to divide the sample sets. The stability competitive adaptive reweighted sampling (SCARS), uninformative variable elimination (UVE), and interval partial least-squares (iPLS) algorithms were then used to screen the pre-processed THz spectral data. Based on the selected characteristic frequency bands, a model for the detection of the nitrogen content of tomato based on the THz spectrum was established by the radial basis function neural network (RBFNN) and backpropagation neural network (BPNN) algorithms, respectively. The results show that the root-mean-square error of correction (RMSEC) and root-mean-square error of prediction (RMSEP) of the BPNN model were respectively 0.1722% and 0.1843%, and the determination coefficients of the correction set (Rc 2) and prediction set (Rp 2) were respectively 0.8447 and 0.8375. The RMSEC and RMSEP values of the RBFNN model were respectively 0.1322% and 0.1855%, and the Rc 2 and Rp 2 values were respectively 0.8714 and 0.8463. Thus, the accuracy of the model established by the RBFNN algorithm was slightly higher. Therefore, the nitrogen content of tomato leaves can be detected by THz spectroscopy. The results of this study can provide a theoretical basis for the research and development of equipment for the detection of the nitrogen content of tomato leaves.

Frequency Range Optimization for Continuous Wave Terahertz Imaging

With shorter wavelengths than microwaves and greater penetration depth than infrared light, waves in the terahertz spectrum offer unique material testing opportunities. Terahertz technology offers non-invasive and non-destructive testing in the form of spectroscopy and imaging. The most used systems for terahertz imaging are time-domain spectroscopy systems. However, frequency domain spectroscopy systems could offer excellent frequency resolution and be more suitable for biomedical applications. Terahertz imaging based on frequency domain spectroscopy systems is slow, and suffers from frequency tuning errors. A novel one-dimensional imaging principle is presented in this paper. In addition, frequency range optimization based on convolutional neural networks and occlusion sensitivity is utilized for frequency range optimization. Frequency range optimization is used to determine the optimal frequency range for data acquisition. The optimal frequency range or bandwidth should be wide enough for effective phase detection, and should be at the intersection of several spectral footprints in the observed medium. The intersection of spectral footprints is estimated using the proposed frequency range optimization algorithm based on a convolutional neural network and occlusion sensitivity algorithm. The proposed algorithm selects the most sensitive frequency band of THz spectrum automatically, and enables very fast acquisitions for object inspection and classification.

Terahertz Microjets as Realizations of Subwavelength Focusing in the Terahertz Spectrum

In this article, we recognize the growing interest to realize terahertz (THz) spectroscopy on the submillimetre scale and target its fundamental challenge—in the need for subwavelength focusing. The challenge is addressed here by way of the THz microjet. We show that THz microjets can be formed as intense focal spots with subwavelength sizes by focusing THz radiation through engineered dielectric spheres. The dielectric spheres are analyzed via the electromagnetic (Mie) theory and effective medium (Bruggeman) theory, and then implemented out of microcomposite material with the requisite (optimal) refractive indices and (minimal) extinction coefficients for the targeted 0.3–0.7-THz spectrum. Ultimately, the dielectric spheres are tested and found to realize THz microjets as intense focal spots with the desired subwavelength sizes.

Qualitative and quantitative study on DL-glutamic acid and its monohydrate using terahertz spectra

The rotation, translation, and vibration of many amino acid molecules fall in the terahertz (THz) range, thus qualitative and quantitative researches of amino acids can be carried out through their THz absorption characteristic fingerprint peaks. In this work, the room-temperature THz absorption spectra of DL-glutamic acid and its monohydrate at 0.5–3.0 THz are measured by utilizing terahertz time-domain spectroscopy (THz-TDS). It is found that the THz characteristic peaks of these two amino acids are obviously different from each other. Moreover, according to the changes of the absorption amplitude of the characteristic absorption peak (1.24 THz) of DL-glutamate monohydrate at different sample concentrations, the mixed samples of DL-glutamate and its monohydrate are quantitatively analyzed, and the quantitative analysis formula is verified. In addition, the optical mode of DL-glutamic acid and its monohydrate in THz region are predicted by using density functional theory (DFT). On condition that the theoretical data are matched with the experimental peaks, the origins of THz absorption peaks obtained in the experiment are discussed and summarized. The results show that the THz characteristic peaks (<2.80 THz) of DL-glutamic acid and its monohydrate come from the intermolecular interactions, and the other absorption peaks result from the combination of intermolecular and intramolecular interactions.

Concise Cascade Methods for Transgenic Rice Seed Discrimination using Spectral Phenotyping.

Currently, the presence of genetically modified (GM) organisms in agro-food markets is strictly regulated by enacted legislation worldwide. It is essential to ensure the traceability of these transgenic products for food safety, consumer choice, environmental monitoring, market integrity, and scientific research. However, detecting the existence of GM organisms involves a combination of complex, time-consuming, and labor-intensive techniques requiring high-level professional skills. In this paper, a concise and rapid pipeline method to identify transgenic rice seeds was proposed on the basis of spectral imaging technologies and the deep learning approach. The composition of metabolome across 3 rice seed lines containing the cry1Ab/cry1Ac gene was compared and studied, substantiating the intrinsic variability induced by these GM traits. Results showed that near-infrared and terahertz spectra from different genotypes could reveal the regularity of GM metabolic variation. The established cascade deep learning model divided GM discrimination into 2 phases including variety classification and GM status identification. It could be found that terahertz absorption spectra contained more valuable features and achieved the highest accuracy of 97.04% for variety classification and 99.71% for GM status identification. Moreover, a modified guided backpropagation algorithm was proposed to select the task-specific characteristic wavelengths for further reducing the redundancy of the original spectra. The experimental validation of the cascade discriminant method in conjunction with spectroscopy confirmed its viability, simplicity, and effectiveness as a valuable tool for the detection of GM rice seeds. This approach also demonstrated its great potential in distilling crucial features for expedited transgenic risk assessment.

Research Progress in the Application of Terahertz Spectroscopy and Imaging Technology in Stomatology

Terahertz waves, the electromagnetic waves in the range of 0.1 to 10 THz, has the advantages of being damage-free, causing no ionizing radiation injury, and being capable of recognizing the fingerprint spectrum of molecular characteristics, thus holding encouraging prospects for wide applications in the field of biomedicine. Terahertz spectrum can be used to identify and characterize biological structures of different levels, from biomolecules such as proteins to cells and tissues, through the spectral signals and/or restored images of the samples. Herein, we summarized the current stomatogical application of and research progress in terahertz spectroscopy and imaging in dentistry, reported the latest research findings, strengths and limitations from three perspectives, tooth anatomical structure, the extent of caries progression, and oral soft tissue, and suggested possible directions for future exploration.

Rain-Based Attenuation and Dispersion Characteristics of Terahertz Wave in Tropical Climate: Experimentally Verified Reliability Study

In the frontier of next generation communication system, the terahertz spectrum can be treated un-parallel as far as the implementation of wireless link with high data-rate is concerned. Atmospheric condition can affect the electromagnetic/radio signal transmission severely. Since, the presence of seasonal hydrometeors in atmosphere may lead to drastic degradation in the free-space propagation of terahertz signal, therefore thorough and comprehensive investigation is essentially required to optimize the future channel-model for terahertz carrier frequency. The atmospheric attenuation causes power loss and in turn receiver signal amplitude gets attenuated. Rain attenuation has pronounced impact on terahertz signal propagation and attenuation of transmitted wave. In tropical weather scenario, the drop-dimension of seasonal rainfall exceeds the maximum dimension of temperate rain. Through an indigenously developed and experimentally verified Non-Linear Terahertz Rain Attenuation Model simulator, the authors have thoroughly investigated the rain-attenuation characteristics of terahertz signal in tropical climate condition for different hydrometeor properties including rain-rates and drop-size distribution. The effect of tropical thunderstorm has been uniquely incorporated by the authors in the present study along with atmospheric humidity and temperature based fluctuations. The reliability issues that are related with THz communication in tropical rain-fall have also been comprehensively analysed. Besides, a best-fit analysis has also been covered under different drop-size distribution statistics. It has been found that, in Indian Scenario (as a part of tropical climate), the peak attenuation level of THz spectrum under tropical rain-fall can be found in the range of (7THz-9THz). With increase of rain-rate from 2mm/hr to 200mm/hr, the peak attenuation level rises from ~100dB/km to ~1000dB/km. The basic model has been validated through experimental data where close proximity(with ± 10% variation from the mean data) has been observed. The present study on terahertz signal attenuation profile in tropical rainy weather will help the communication engineers to open the new door for the ultra-high speed world of 6G terahertz communication.

Terahertz Imaging and Sensing for Healthcare: Current Status and Future Perspectives

There is a keen interest in the exploration of new generation emitters and detectors due to advancements in innovation of new materials and device processing technologies which have opened up new frontiers in the Terahertz (THz) spectrum. Therefore, it is necessary to review the developments in THz technology for healthcare applications, their impact, implications and prospects for ongoing research and development. This paper provides a broad overview of the current status and prospects of application of THz imaging and sensing for the healthcare domain. We present current knowledge, identify existing challenges for wide scale clinical adoption of THz systems and prospective opinions to facilitate research and development towards optimized and miniaturized THz systems and biosensors that provide real operational convenience through emerging trends. Firstly, we provide an overview of the THz imaging and sensing techniques that exploit properties of THz generation and detection with emphasis on terahertz time domain spectroscopy (THz-TDS) and THz Metamaterials. The mechanisms of tissue image contrast and the application of THz imaging and sensing for biomedical applications in particular, the cancer detection application is reported. Secondly, an outlook toward the advancements in THz technology in the interface of healthcare 4.0 and its enabling technologies is explored for next generation smart and connected healthcare systems. Third, we identify the merits and existing challenges in THz cancer imaging and sensing and suggest prospective opinions to pave way to ongoing and future research. Further, we discuss the recent advances in THz imaging development and the contribution of near-field techniques based on plasmonic, and resonance based metasurfaces, waveguides etc. for breaking the diffraction limit towards development of THz systems that are convenient for point of care. We bring researchers a roadmap for future research scope.

Hybrid quantum dot-graphene layers with improved optical properties in the terahertz spectrum region

Recently, it has been shown that the graphene plasmonic (GP) effect can enhance the optical properties of quantum dots (QDs) through the Purcell's effect. This can happen when the electromagnetic field is concentrated tightly in a region where the ground state (S-state) and the first excited state (P-state) of electron are present, and the S-to-P transition frequency falls onto the frequency of plasmonic resonance of graphene layers. Here, we use a hybrid composition of graphene layers, consisting of a disk and four L-shaped layers, and a QD aimed to enhance the linear and third-order optical susceptibilities of QD in the terahertz (THz)/far infrared (FIR) spectrum region. Unlike the previous works, where much more graphene layers were used, in this work, we use fewer layers beneath the wetting layer and with a noticeably simpler scheme, we achieve comparable results in transition dipole moments (TDMs) and optical properties. By changing the Fermi's energy of graphene, we could reach 90-fold enhancement for TDM and 8 × 10 3 - and 6 × 10 7 -fold enhancements, respectively, for linear and third-order susceptibilities. Our scheme can noticeably reduce the difficulties in fabricating hybrid graphene-QD systems. • Graphene flakes in nanodisk and L-shaped geometry have been placed in conic-shaped InAs/GaAS quantum dots (QDs). • The emission of QDs has been tuned with graphene plasmonic (GP). • With use of GP effect, S-to-P transition dipole moment (TDM) of QD has been enhanced 120 times. • Linear susceptibility of QD has been multiplied by a factor of 8 × 10 3 . • Third-order susceptibility of QD has been multiplied by a factor of 6 × 10 7 . • GP has been used as a passive method to enhance significantly the optical properties of QDs.

Terahertz spectra of curcumin and catechol co-crystals

Curcumin (CUR) is a commonly used pharmaceutical with anti-inflammatory, antioxidant and anti-cancer effects, but its solubility in water is relatively low. In recent years, pharmaceutical co-crystal has been an effective method of enhancing the solubility of limited water-soluble pharmaceuticals. Based on this, terahertz time-domain spectroscopy (THz-TDS) is used to study the THz spectra of curcumin-catechol co-crystal. Firstly, the experimental spectra of curcumin, catechol (CTL), their physical mixture and their co-crystal are measured in a range of 0.5–3.5 THz, respectively. The experimental data show that CUR obtains six THz absorption peaks, while CTL possess three THz absorption peaks, the physical mixture obtains four absorption peaks, and their CUR-CTL co-crystal obtains three absorption peaks. These results indicate that THz-TDS can effectively identify curcumin, catechol and their co-crystals. The fact that the absorption peak at 3.31 THz obtained in co-crystal is entirely different from those of raw materials, implying that new weak interactional forces are generated between CUR molecule and CTL molecule, the co-crystal forms a new three-dimensional structure compared with their raw materials. These results are also verified by X-ray diffraction spectra of raw material and their Co-crystal. Moreover, four possible theoretical forms of curcumin-catechol co-crystal are optimized and simulated by using density functional theory (DFT). The calculated results indicate that the data of co-crystal form III are in good agreement with the experimental spectrum, and the simulation effectively reconstructs the experimental spectrum. So it can be inferred that the co-crystal is formed through the hydrogen bond between the carbonyl C10=O3 of CUR and the hydroxy O61-H55 of CTL. In addition, depending on the good match between experimental data and theoretical results, it is found that the three absorption peaks in the co-crystal do not origin from the action of a single molecule, but the joint action of the functional groups of the two molecules under the driving by the hydrogen bond. The existence of weak interaction forces, such as the hydrogen bond, not only changes the structural parameters of the two molecules, but also reestablishes a new intermolecular force, which then affects the interactional motions of the co-crystal. This fact directly leads the CUR-CTL co-crystal to exhibit THz absorption peaks different from those of raw materials in the THz band.

Air-photonics based terahertz source and detection system

Two-color air plasma-based broadband terahertz (THz) generation and subsequent air-biased coherent detection (ABCD) of the THz field are presented. Both source and detection systems are characterized experimentally and numerically, yielding excellent agreement of measured and simulated signals. We reveal that it is crucial to model the whole optical setup and include the various pump distortions, like temporal and spatial walk-off as well as ellipticity of polarization, in order to interpret the experimental measurements correctly. Moreover, it turns out that geometrical effects in the ABCD scheme shape the recorded THz spectra and need to be taken into account. We confirm that THz electric fields with peak amplitude in the MV/cm range and large spectral bandwidth are produced, allowing us to demonstrate THz spectroscopy with molecular samples.

A Numerical Investigation of Graphene-Based Hilbert-Shaped Multi-Band MIMO Antenna for the Terahertz Spectrum Applications.

We proposed the numerical investigation of Hilbert-shaped multiple-input multi-output (MIMO) with multi-band operation characteristics using graphene resonator material, which operates on the band of 1 to 30 THz of the frequency range. This numerical investigation of antenna structure was carried out for the multiple antenna types, consisting of graphene as a regular patch, Hilbert order 1, and Hilbert order 2 designs. This antenna is investigated for the multiple physical parameters, such as return loss, gain, bandwidth, radiation response, Envelope Correlation Coefficient (ECC), Total Active Reflection Coefficient (TARC), Mean Effective Gain (MEG), Directivity Gain (DG), and Channel Capacity Loss (CCL). These variables are also determined to verify compatibility and the difficulties connected with communicating over a short distance. The THz MIMO antenna that was recommended offers strong isolation values in addition to an operational band. The maximum gain of ~10 dBi for the band of <15 THz and ~17 dBi for the band of the >15 THz frequency range of the proposed antenna structures. The proposed antennas are primarily operated in three bands over 1 to 30 THz of frequency. This work aims to create a brand new terahertz antenna structure capable of providing an extraordinarily wider bandwidth and high gain while keeping a typical compact antenna size suited for terahertz applications.

Super-resolution image display using diffractive decoders.

High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning-enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.