Surface plasmons-phonons for mid-infrared hyperspectral imaging.

Surface plasmons have proven their ability to boost the sensitivity of mid-infrared hyperspectral imaging by enhancing light-matter interactions. Surface phonons, a counterpart technology to plasmons, present unclear contributions to hyperspectral imaging. Here, we investigate this by developing a plasmon-phonon hyperspectral imaging system that uses asymmetric cross-shaped nanoantennas composed of stacked plasmon-phonon materials. The phonon modes within this system, controlled by light polarization, capture molecular refractive index intensity and lineshape features, distinct from those observed with plasmons, enabling more precise and sensitive molecule identification. In a deep learning-assisted imaging demonstration of severe acute respiratory syndrome coronavirus (SARS-CoV), phonons exhibit enhanced identification capabilities (230,400 spectra/s), facilitating the de-overlapping and observation of the spatial distribution of two mixed SARS-CoV spike proteins. In addition, the plasmon-phonon system demonstrates increased identification accuracy (93%), heightened sensitivity, and enhanced detection limits (down to molecule monolayers). These findings extend phonon polaritonics to hyperspectral imaging, promising applications in imaging-guided molecule screening and pharmaceutical analysis.

Dynamic construction of refractive index-dependent vibrations using surface plasmon-phonon polaritons.

One of the fundamental hurdles in infrared spectroscopy is the failure of molecular identification when their infrared vibrational fingerprints overlap. Refractive index (RI) is another intrinsic property of molecules associated with electronic polarizability, but with limited contribution to molecular identification in mixed environments currently. Here, we investigate the coupling mode of localized surface plasmon and surface phonon polaritons for vibrational de-overlapping. The coupling mode is sensitive to the molecular refractive index, attributed to the RI-induced vibrational variations of surface phonon polaritons (SPhP) within the Reststrahlen band, referred to as RI-dependent SPhP vibrations. The RI-dependent SPhP vibrations are linked to molecular RI features. According to the deep-learning-augmented demonstration of bond-breaking-bond-making dynamic profiling in biological reaction, we substantiate that the RI-dependent SPhP vibrations effectively disentangle overlapping vibrational modes, achieving a 92% identification accuracy even for the strongly overlapping vibrational modes in the reaction. Our findings offer insights into the realm of light-matter interaction and provide a valuable toolkit for biomedicine applications.

Eliciting tactile sensations in the hand through non-invasive proximal nerve stimulation: a feasibility study.

Recently, non-invasive proximal nerve stimulation has been widely investigated to restore tactile sensations. It has been demonstrated that tactile sensations in the hand could be elicited by nerve stimulation on the upper arm. However, it is still unknown whether tactile sensations could be elicited by stimulation at a proximal location close to the neck. In this study, non-invasive proximal nerve stimulation tests were performed to elicit tactile sensations in the hand of subjects. Six Ag/AgCl gel electrodes (2 × 3) were placed on the supraclavicular fossa where the proximal parts of the brachial plexus nerves were located. Then, fifteen potential electrode pairs were tested to explore whether tactile sensations could be elicited by non-invasive proximal nerve stimulation. Eight able-bodied subjects (male) were recruited to participate in the test. The stimulated sensation regions in the hand and the sensory intensity were reported and recorded during the experiment. The results demonstrated that the tactile sensations in various regions in the hand could be elicited through non-invasive nerve stimulation at the proximal location close to the neck.

Generation of a monoclonal antibody against duck circovirus capsid protein and its potential application for native viral antigen detection.

Introduction: Duck circovirus (DuCV) infection is currently recognized as an important immunosuppressive disease in commercial duck flocks in China. Specific antibodies against DuCV viral proteins are required to improve diagnostic assays and understand the pathogenesis of DuCV infection. Methods and results: To generate DuCV-specific monoclonal antibodies (mAbs), a recombinant DuCV capsid protein without the first 36 N-terminal amino acids was produced in Escherichia coli. Using the recombinant protein as an immunogen, a mAb was developed that reacted specifically with the DuCV capsid protein, expressed in E. coli and baculovirus systems. Using homology modeling and recombinant truncated capsid proteins, the antibody-binding epitope was mapped within the region of 144IDKDGQIV151, which is exposed to solvent in the virion capsid model structure. To assess the applicability of the mAb to probe the native virus antigen, the murine macrophage cell line RAW267.4 was tested for DuCV replicative permissiveness. Immunofluorescence and Western blot analysis revealed that the mAb recognized the virus in infected cells and the viral antigen in tissue samples collected from clinically infected ducks. Discussion: This mAb, combined with the in vitro culturing method, would have widespread applications in diagnosing and investigating DuCV pathogenesis.

Expanding chiral metamaterials for retrieving fingerprints via vibrational circular dichroism.

Circular dichroism (CD) spectroscopy has been widely demonstrated for detecting chiral molecules. However, the determination of chiral mixtures with various concentrations and enantiomeric ratios can be a challenging task. To solve this problem, we report an enhanced vibrational circular dichroism (VCD) sensing platform based on plasmonic chiral metamaterials, which presents a 6-magnitude signal enhancement with a selectivity of chiral molecules. Guided by coupled-mode theory, we leverage both in-plane and out-of-plane symmetry-breaking structures for chiral metamaterial design enabled by a two-step lithography process, which increases the near-field coupling strengths and varies the ratio between absorption and radiation loss, resulting in improved chiral light-matter interaction and enhanced molecular VCD signals. Besides, we demonstrate the thin-film sensing process of BSA and ß-lactoglobulin proteins, which contain secondary structures α-helix and ß-sheet and achieve a limit of detection down to zeptomole level. Furthermore, we also, for the first time, explore the potential of enhanced VCD spectroscopy by demonstrating a selective sensing process of chiral mixtures, where the mixing ratio can be successfully differentiated with our proposed chiral metamaterials. Our findings improve the sensing signal of molecules and expand the extractable information, paving the way toward label-free, compact, small-volume chiral molecule detection for stereochemical and clinical diagnosis applications.

Triboelectric-induced ion mobility for artificial intelligence-enhanced mid-infrared gas spectroscopy.

Isopropyl alcohol molecules, as a biomarker for anti-virus diagnosis, play a significant role in the area of environmental safety and healthcare relating volatile organic compounds. However, conventional gas molecule detection exhibits dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interaction of mid-infrared spectroscopy, yielding limited response of targeted molecules. We propose a synergistic methodology of artificial intelligence-enhanced ion mobility and mid-infrared spectroscopy, leveraging the complementary features from the sensing signal in different dimensions to reach superior accuracy for isopropyl alcohol identification. We pull in "cold" plasma discharge from triboelectric generator which improves the mid-infrared spectroscopic response of isopropyl alcohol with good regression prediction. Moreover, this synergistic methodology achieves ~99.08% accuracy for a precise gas concentration prediction, even with interferences of different carbon-based gases. The synergistic methodology of artificial intelligence-enhanced system creates mechanism of accurate gas sensing for mixture and regression prediction in healthcare.

Ultrasensitive Molecular Fingerprint Retrieval Using Strongly Detuned Overcoupled Plasmonic Nanoantennas.

Tailoring light-matter interactions via plasmonic nanoantennas (PNAs) has emerged as a breakthrough technology for spectroscopic applications. The detuning between molecular vibrations and plasmonic resonances, as a fundamental and inevitable optical phenomenon in light-matter interactions, reduces the interaction efficiency, resulting in a weak molecule sensing signal at the strong detuning state. Here, it is demonstrated that the low interaction efficiency from detuning can be tackled by overcoupled PNAs (OC-PNAs) with a high ratio of the radiative to intrinsic loss rates, which can be used for ultrasensitive spectroscopy at strong plasmonic-molecular detuning. In OC-PNAs, the ultrasensitive molecule signals are achieved within a wavelength detuning range of 248 cm-1 , which is 173 cm-1 wider than previous works. Meanwhile, the OC-PNAs are immune to the distortion of molecular signals and maintain a lineshape consistent with the molecular signature fingerprint. This strategy allows a single device to enhance and capture the full and complex fingerprint vibrations in the mid-infrared range. In the proof-of-concept demonstration, 13 kinds of molecules with some vibration fingerprints strongly detuning by the OC-PNAs are identified with 100% accuracy with the assistance of machine-learning algorithms. This work gains new insights into detuning-state nanophotonics for potential applications including spectroscopy and sensors.

Meta-Transcriptomic Analysis Reveals Novel RNA Viruses in Hippocampus erectus.

Lined seahorse, Hippocampus erectus, is an important aquatic animal due to its medicinal and ornamental purposes. However, our understanding of the viral spectrum in H. erectus is still limited. Here, we studied the viruses in H. erectus using meta-transcriptomic sequencing. A total of 213,770,166 reads were generated and assembled de novo into 539 virus-associated contigs. Three novel RNA viruses from the Astroviridae, Paramyxoviridae, and Picornaviridae families were finally identified. In addition, we identified a strain of nervous necrosis virus from H. erectus. In particular, the unhealthy group showed a higher viral diversity and abundance than the normal group. These results revealed the diversity and cross-species transmission of viruses in H. erectus and highlighted the threat of viral infections to H. erectus.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics.

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

Midinfrared Spectroscopic Analysis of Aqueous Mixtures Using Artificial-Intelligence-Enhanced Metamaterial Waveguide Sensing Platform.

As miniaturized solutions, mid-infrared (MIR) waveguide sensors are promising for label-free compositional detection of mixtures leveraging plentiful absorption fingerprints. However, the quantitative analysis of liquid mixtures is still challenging using MIR waveguide sensors, as the absorption spectrum overlaps for multiple organic components accompanied by strong water absorption background. Here, we present an artificial-intelligence-enhanced metamaterial waveguide sensing platform (AIMWSP) for aqueous mixture analysis in the MIR. With the sensitivity-improved metamaterial waveguide and assistance of machine learning, the MIR absorption spectra of a ternary mixture in water can be successfully distinguished and decomposed to single-component spectra for predicting concentration. A classification accuracy of 98.88% for 64 mixing ratios and 92.86% for four concentrations below the limit of detection (972 ppm, based on 3σ) with steps of 300 ppm are realized. Besides, the mixture concentration prediction with root-mean-squared error varying from 0.107 vol % to 1.436 vol % is also achieved. Our work indicates the potential of further extending this sensing platform to MIR spectrometer-on-chip aiming for the data analytics of multiple organic components in aqueous environments.

MOF/Polymer-Integrated Multi-Hotspot Mid-Infrared Nanoantennas for Sensitive Detection of CO2 Gas.

Metal-organic frameworks (MOFs) have been extensively used for gas sorption, storage and separation owing to ultrahigh porosity, exceptional thermal stability, and wide structural diversity. However, when it comes to ultra-low concentration gas detection, technical bottlenecks of MOFs appear due to the poor adsorption capacity at ppm-/ppb-level concentration and the limited sensitivity for signal transduction. Here, we present hybrid MOF-polymer physi-chemisorption mechanisms integrated with infrared (IR) nanoantennas for highly selective and ultrasensitive CO2 detection. To improve the adsorption capacity for trace amounts of gas molecules, MOFs are decorated with amino groups to introduce the chemisorption while maintaining the structural integrity for physisorption. Additionally, leveraging all major optimization methods, a multi-hotspot strategy is proposed to improve the sensitivity of nanoantennas by enhancing the near field and engineering the radiative and absorptive loss. As a benefit, we demonstrate the competitive advantages of our strategy against the state-of-the-art miniaturized IR CO2 sensors, including low detection limit, high sensitivity (0.18%/ppm), excellent reversibility (variation within 2%), and high selectivity (against C2H5OH, CH3OH, N2). This work provides valuable insights into the integration of advanced porous materials and nanophotonic devices, which can be further adopted in ultra-low concentration gas monitoring in industry and environmental applications.

Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy.

Infrared (IR) plasmonic nanoantennas (PNAs) are powerful tools to identify molecules by the IR fingerprint absorption from plasmon-molecules interaction. However, the sensitivity and bandwidth of PNAs are limited by the small overlap between molecules and sensing hotspots and the sharp plasmonic resonance peaks. In addition to intuitive methods like enhancement of electric field of PNAs and enrichment of molecules on PNAs surfaces, we propose a loss engineering method to optimize damping rate by reducing radiative loss using hook nanoantennas (HNAs). Furthermore, with the spectral multiplexing of the HNAs from gradient dimension, the wavelength-multiplexed HNAs (WMHNAs) serve as ultrasensitive vibrational probes in a continuous ultra-broadband region (wavelengths from 6 µm to 9 µm). Leveraging the multi-dimensional features captured by WMHNA, we develop a machine learning method to extract complementary physical and chemical information from molecules. The proof-of-concept demonstration of molecular recognition from mixed alcohols (methanol, ethanol, and isopropanol) shows 100% identification accuracy from the microfluidic integrated WMHNAs. Our work brings another degree of freedom to optimize PNAs towards small-volume, real-time, label-free molecular recognition from various species in low concentrations for chemical and biological diagnostics.

Reconfigurable terahertz metamaterials: From fundamental principles to advanced 6G applications.

Terahertz (THz) electromagnetic spectrum ranging from 0.1THz to 10THz has become critical for sixth generation (6G) applications, such as high-speed communication, fingerprint chemical sensing, non-destructive biosensing, and bioimaging. However, the limited response of naturally existing materials THz waves has induced a gap in the electromagnetic spectrum, where a lack of THz functional devices using natural materials has occurred in this gap. Metamaterials, artificially composed structures that can engineer the electromagnetic properties to manipulate the waves, have enabled the development of many THz devices, known as "metadevices". Besides, the tunability of THz metadevices can be achieved by tunable structures using microelectromechanical system (MEMS) technologies, as well as tunable materials including phase change materials (PCMs), electro-optical materials (EOMs), and thermo-optical materials (TOMs). Leveraging various tuning mechanisms together with metamaterials, tremendous research works have demonstrated reconfigurable functional THz devices, playing an important role to fill the THz gap toward the 6G applications. This review introduces reconfigurable metadevices from fundamental principles of metamaterial resonant system to the design mechanisms of functional THz metamaterial devices and their related applications. Moreover, we provide perspectives on the future development of THz photonic devices for state-of-the-art applications.

Heterogeneous Wafer Bonding Technology and Thin-Film Transfer Technology-Enabling Platform for the Next Generation Applications beyond 5G.

Wafer bonding technology is one of the most effective methods for high-quality thin-film transfer onto different substrates combined with ion implantation processes, laser irradiation, and the removal of the sacrificial layers. In this review, we systematically summarize and introduce applications of the thin films obtained by wafer bonding technology in the fields of electronics, optical devices, on-chip integrated mid-infrared sensors, and wearable sensors. The fabrication of silicon-on-insulator (SOI) wafers based on the Smart CutTM process, heterogeneous integrations of wide-bandgap semiconductors, infrared materials, and electro-optical crystals via wafer bonding technology for thin-film transfer are orderly presented. Furthermore, device design and fabrication progress based on the platforms mentioned above is highlighted in this work. They demonstrate that the transferred films can satisfy high-performance power electronics, molecular sensors, and high-speed modulators for the next generation applications beyond 5G. Moreover, flexible composite structures prepared by the wafer bonding and de-bonding methods towards wearable electronics are reported. Finally, the outlooks and conclusions about the further development of heterogeneous structures that need to be achieved by the wafer bonding technology are discussed.

Toward Healthcare Diagnoses by Machine-Learning-Enabled Volatile Organic Compound Identification.

As a natural monitor of health conditions for human beings, volatile organic compounds (VOCs) act as significant biomarkers for healthcare monitoring and early stage diagnosis of diseases. Most existing VOC sensors use semiconductors, optics, and electrochemistry, which are only capable of measuring the total concentration of VOCs with slow response, resulting in the lack of selectivity and low efficiency for VOC detection. Infrared (IR) spectroscopy technology provides an effective solution to detect chemical structures of VOC molecules by absorption fingerprints induced by the signature vibration of chemical stretches. However, traditional IR spectroscopy for VOC detection is limited by the weak light-matter interaction, resulting in large optical paths. Leveraging the ultrahigh electric field induced by plasma, the vibration of the molecules is enhanced to improve the light-matter interaction. Herein, we report a plasma-enhanced IR absorption spectroscopy with advantages of fast response, accurate quantization, and good selectivity. An order of ∼kV voltage was achieved from the multiswitched manipulation of the triboelectric nanogenerator by repeated sliding. The VOC species and their concentrations were well-quantified from the wavelength and intensity of spectra signals with the enhancement from plasma. Furthermore, machine learning has visualized the relationship of different VOCs in the mixture, which demonstrated the feasibility of the VOC identification to mimic patients.

Nanometer-Scale Heterogeneous Interfacial Sapphire Wafer Bonding for Enabling Plasmonic-Enhanced Nanofluidic Mid-Infrared Spectroscopy.

As one of the most effective surface-enhanced infrared absorption (SEIRA) techniques, metal-insulator-metal structured metamaterial perfect absorbers possess an ultrahigh sensitivity and selectivity in molecular infrared fingerprint detection. However, most of the localized electromagnetic fields (i.e., hotspots) are confined in the dielectric layer, hindering the interaction between analytes and hotspots. By replacing the dielectric layer with the nanofluidic channel, we develop a sapphire (Al2O3)-based mid-infrared (MIR) hybrid nanofluidic-SEIRA (HN-SEIRA) platform for liquid sensors with the aid of a low-temperature interfacial heterogeneous sapphire wafer direct bonding technique. The robust atomic bonding interface is confirmed by transmission electron microscope observation. We also establish a design methodology for the HN-SEIRA sensor using coupled-mode theory to carry out the loss engineering and experimentally validate its feasibility through the accurate nanogap control. Thanks to the capillary force, liquid analytes can be driven into sensing hotspots without external actuation systems. Besides, we demonstrate an in situ real-time dynamic monitoring process for the acetone molecular diffusion in deionized water. A small concentration change of 0.29% is distinguished and an ultrahigh sensitivity (0.8364 pmol-1 %) is achieved. With the aid of IR fingerprint absorption, our HN-SEIRA platform brings the selectivity of liquid molecules with similar refractive indexes. It also resolves water absorption issues in traditional IR liquid sensors thanks to the sub-nm long light path. Considering the wide transparency window of Al2O3 in MIR (up to 5.2 µm), the HN-SEIRA platform covers more IR absorption range for liquid sensing compared to fused glass commonly used in micro/nanofluidics. Leveraging the aforementioned advantages, our work provides insights into developing a MIR real-time liquid sensing platform with intrinsic IR fingerprint selectivity, label-free ultrahigh sensitivity, and ultralow analyte volume, demonstrating a way toward quantitative molecule identification and dynamic analysis for the chemical and biological reaction processes.

Vernier effect-based tunable mid-infrared sensor using silicon-on-insulator cascaded rings.

Vernier effect has been captivated as a promising approach to achieve high-performance photonic sensors. However, experimental demonstration of such sensors in mid-infrared (MIR) range, which covers abundant absorption fingerprints of molecules, is still lacking. Here, we report Vernier effect-based thermally tunable photonic sensors using cascaded ring resonators fabricated on the silicon-on-insulator (SOI) platform. The radii and the coupling gaps in two rings are investigated as key design parameters. By applying organic liquids on our device, we observe an envelope shift of 48 nm with a sensitivity of 3000 nm/RIU and an intensity drop of 6.7 dB. Besides, our device can be thermally tuned with a sensitivity of 0.091 nm/mW. Leveraging the characteristic molecular absorption in the MIR, our work offers new possibilities for complex index sensing, which has wide applications in on-chip photonic sensors.

Diagnostic value of multislice spiral computed tomography (CT) combined with CT angiography for intra-abdominal undescended testis secondary seminomas.

OBJECTIVE: To discuss the diagnostic value of multislice spiral tomography (CT) combined with CT angiography (CTA) technology in intra-abdominal undescended testis secondary seminoma cases. METHODS: We retrospectively analyzed the CT and CTA imaging features of CT and CTA findings of nine patients with an intra-abdominal undescended testis secondary seminoma. RESULTS: The tumors in all nine patients were mainly solid, and the average CT value was 38.4 ± 3.4 HU. Low-density areas of various sizes were visible in the tumors, and calcifications were detected in two patients. The tumors in eight patients had a complete capsule, which pressed on the surrounding structures. In one patient, the tumor had an incomplete capsule, which invaded the surrounding structures. Some of the solid tumors showed progressive and slight enhancement on the CT-enhanced scans. The values in the arterial phase, venous phase, and delayed phase were 46.3 ± 5.1 (40-55 HU), 57.3 ± 7.3HU (48-68 HU), and 65.1 ± 7.2HU (56-77 HU), respectively, with an average increase rate of 27.0 ± 7.2 HU. No enhancement was found in low-density areas on the CTA scans, and the supply arteries of the tumors in the nine patients all originated from the abdominal aortic wall 2-3 cm below the renal ostia. These arteries became thickened and tortuous when near the tumors, and there were no branching vessels. In eight patients, the supply arteries of the tumors originated from the posterior tumor and ended inside the tumor, and they originated from anterior of the tumor in one patient. Testicular venous drainage was detected in three patients, and lymph node metastasis in the abdominal aorta detected in two cases. CONCLUSION: An intra-abdominal undescended testis secondary seminoma exhibits a characteristic appearance on CT. CTA shows a three-dimensional testicular vascular pedicle sign of a seminoma. A combination of CT and CTA can improve the diagnostic accuracy of an intra-abdominal undescended testis secondary seminoma.

Intrapancreatic accessory spleen: Evaluation with CT and MRI.

The aim of the present study was to evaluate the characteristics of computed tomography (CT) and magnetic resonance imaging (MRI), particularly diffusion-weighted imaging (DWI), in the imaging of intrapancreatic accessory spleen (IPAS). The clinical and pathological records of 9 patients, including 8 patients with IPAS and 1 patient with splenosis, were reviewed. The patients had undergone plain and triple-phase enhanced CT scanning (n=9) and MRI scanning (n=8). The lesions of the 8 IPAS patients were located in the pancreatic tail, and were round (n=3), oval (n=4) or triangular (n=1) in shape. The CT and/or MRI densities, signal intensities and dynamic enhanced patterns of the lesions were similar to those of the orthotopic spleen. In DWI images (n=5), the IPAS regions presented high signal intensity (SI), and no significant difference in the apparent diffusion coefficient determined using a b-value of 600 sec/mm2 was identified between the IPAS and orthotopic spleen (P>0.05). One patient with splenosis complicated with cirrhosis had a nodule located in the pancreatic tail with an unenhanced CT value of 65 HU. In MRI examination, with the exception of the dynamic enhancement pattern, the T1-weighted, T2-weighted and DWI signals of splenosis were inconsistent with those of the normal spleen. In conclusion, in pre-contrast and post-contrast-enhanced CT and MRI images, IPAS exhibits similar characteristics to the orthotopic spleen. CT and MRI used in combination with DWI are important in the diagnosis of IPAS.