Array Substrate Research Articles

Multiplex Detection and Quantification of Virus Co-Infections Using Label-free Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms.

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.2 million SERS spectra are collected from 11 viruses, nine two-virus mixtures, and four three-virus mixtures at various concentrations in saliva. A deep learning model, MultiplexCR, is developed to simultaneously predict virus species and concentrations from SERS spectra. It achieves an impressive 98.6% accuracy in classifying virus coinfections and a mean absolute error of 0.028 for concentration regression. In blind tests, the model demonstrates consistent high accuracy and precise concentration predictions. This SERS-MultiplexCR platform completes the entire detection process in just 15 min, offering significant potential for rapid, point-of-care diagnostics in infection detection, as well as applications in food safety and environmental monitoring.

Au Ordered Array Substrate for Rapid Detection and Precise Identification of Etomidate in E-Liquid Through Surface-Enhanced Raman Spectroscopy.

Etomidate (ET), a medical anesthetic, is increasingly being incorporated into e-liquids for consumption and abuse as a new psychoactive substance (NPS), leading to significant social issues. In this work, large-area Au micro- and nano-structured ordered arrays were engineered as surface-enhanced Raman spectroscopy (SERS) substrates for fast detection and precise identification of ET and its metabolites. This ordered array, characterized by abundant electromagnetic enhancement hotspots and structural uniformity, imparts unique properties to the SERS substrate, including ultra-sensitivity, spectral signal reproducibility, and precise quantitative capabilities. Furthermore, it effectively mitigates interference from the complex matrix of e-liquids, facilitating the rapid detection of trace amounts of ET molecules. This SERS rapid detection technology can act as a preliminary screening method for gold-standard spectroscopic analysis, facilitating the on-site rapid screening of suspicious samples and thereby enabling efficient detection and precise verification.

CuO nanowire array induced thermal effect from long wavelength light enhances photo-carrier transport in FeOCl for improved photo-fenton reaction

In this work, we aim to address the issue of hindered photo-carrier transport in layered FeOCl by means of the conversion of long-wavelength light into thermal energy through a CuO nanowire array substrate, thereby enhancing its Photo-Fenton activity. The results indicate that the CuO nanowire array can elevate the temperature of FeOCl from room temperature to approximately 55 °C under AM 1.5G conditions, extending the diffusion length of photo-carriers from 4 nm to ∼15 nm. This significant enhancement facilitates the separation of photo-carriers and results in a 2-fold enhancement in the Photo-Fenton degradation activity of ciprofloxacin. This work provides a feasible strategy for optimizing layered photocatalysts to improve their performances in advanced oxidation processes.

Integrated SERS-Microfluidic Sensor Based on Nano-Micro Hierarchical Cactus-like Array Substrates for the Early Diagnosis of Prostate Cancer.

The detection and analysis of cancer cell exosomes with high sensitivity and precision are pivotal for the early diagnosis and treatment strategies of prostate cancer. To this end, a microfluidic chip, equipped with a cactus-like array substrate (CAS) based on surface-enhanced Raman spectroscopy (SERS) was designed and fabricated for the detection of exosome concentrations in Lymph Node Carcinoma of the Prostate (LNCaP). Double layers of polystyrene (PS) microspheres were self-assembled onto a polyethylene terephthalate (PET) film to form an ordered cactus-like nanoarray for detection and analysis. By combining EpCAM aptamer-labeled SERS nanoprobes and a CD63 aptamer-labeled CAS, a 'sandwich' structure was formed and applied to the microfluidic chips, further enhancing the Raman scattering signal of Raman reporter molecules. The results indicate that the integrated microfluidic sensor exhibits a good linear response within the detection concentration range of 105 particles μL-1 to 1 particle μL-1. The detection limit of exosomes in cancer cells can reach 1 particle μL-1. Therefore, we believed that the CAS integrated microfluidic sensor offers a superior solution for the early diagnosis and therapeutic intervention of prostate cancer.

Three-dimensional composite substrate based on pyramidal pitted silicon array adhered Au@Ag nanospheres for high-performance surface-enhanced Raman scattering.

As a noninvasive and label-free optical technique, Raman spectroscopy offers significant advantages in studying the structure and properties of biomacromolecules, as well as real-time changes in cellular molecular structure. However, its practical applications are hindered by weak scattering responses, low signal intensity, and poor spectral uniformity, which affect the subsequent accuracy of spectral analysis. To address these issues, we report a novel surface-enhanced Raman scattering (SERS) substrate based on a pyramidal pitted silicon (PPSi) array structure adhered with Au-shell Ag-core nanospheres (Au@Ag NSs). By preparing a highly uniform PPSi array substrate with controllable size and arrangement, and constructing SERS-active Au@Ag NSs on this substrate, a three-dimensional (3D) composite SERS substrate is realized. The enhancement performance and spectral uniformity of 3D composite SERS substrate were examined using crystal violet (CV) and Rhodamine 6G (R6G) molecules, achieving a minimum detectable concentration of R6G at 10-9 M and the analytical enhancement factor (AEF) of 4.2 × 108. Moreover, SERS detection of biological samples with varying concentrations of Staphylococcus aureus demonstrated excellent biocompatibility of the SERS substrate and enabled quantitative analysis of bacterial concentration (R 2 = 99.7 %). Theoretical simulations using finite-difference time-domain (FDTD) analysis were conducted to examine the electromagnetic field distribution of the three-dimensional SERS composite substrate, confirming its local electric field enhancement effect. These experimental and theoretical results indicate that the Au@Ag NSs/PPSi substrate with a regulable pyramidal pitted array is a promising candidate for sensitive, label-free SERS detection in medical and biotechnological applications.

Molybdenum Truncated Cone Arrays with Localized Surface Plasmon Resonance for Surface-Enhanced Raman Scattering Application

Plasmonic materials have been extensively explored for surface-enhanced Raman scattering (SERS) due to their high tunability and excellent localized electric field enhancement. Most research for now has focused on noble metals, with limited investigation into corrosion-resistant materials for SERS effects. In this study, a photolithography process is firstly used to create a patterned dot array on a silicon substrate. Next, magnetron sputtering is employed to deposit molybdenum films, finally resulting in the molybdenum truncated cone array substrates for SERS applications. The fabricated truncated cone array experimentally facilitates the coupling of localized surface plasmon polaritons, consistent with simulation results obtained via the finite-difference time-domain method. The formation of hot spots between the cone unit cell arrays leads to the improved Raman signals and can act as traps for target molecules. This study demonstrates that molybdenum-based micro-nano structures can serve as reliable SERS substrates for sensitive molecular sensing applications in highly corrosive environments.

High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.

Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemporal reporting at the single-molecule level within a nanometer-scale area. However, their superior sensitivity also makes them susceptible to slight environmental influences such as reference analytes in media, external fluid flow, and mechanical modulations. Consequently, they often fail to achieve the optimal limit of detection (LOD) and frequently convey misinformation spatiotemporally. To address this challenge, we developed a single-pixel mapping technique for optical nanosensor arrays that operates with high spatiotemporal precision using machine learning. We systematically measured the spatial sensing images of various analyte concentrations below the LOD by using a near-infrared (nIR) fluorescent SWCNT nanosensor array. For dopamine (DA) as an example analyte, we extracted single-pixel level sensing features such as entropy, the Laplacian operator, and neighboring values under noise levels. We then trained the artificial intelligence (AI) model to accurately identify specific reaction pixels of the nanosensor array, even below the LOD region. Additionally, our method can distinguish subtle noise caused by fluid in the media or mechanical modulation of the array substrate. As a result, our approach significantly improved the detection sensitivity of the nanosensor array, achieving a 13-fold increase over the original LOD and halving the detection time of the reporter pixels, with F1 scores exceeding 0.9. This method not only lowers the LOD of optical nanosensors but also isolates sensor responses specific to the analyte, providing accurate spatiotemporal information to the user, even in noisy conditions. It can be universally applied to various optical nanosensor materials and analytes, maximizing the sensitivity and accuracy of the nanosensors used in diagnostics and analysis.

Effect of micropillar density on morphology and migration of low and high metastatic potential breast cancer cells

Study of cell migration in cancer is crucial to the comprehension of the processes and factors that govern tumor spread. Cancer cells migrate invading tissues, causing alterations in cell adhesion, cytoskeleton, and signaling pathways. Little is known about the physical attributes of cancer cells that change when interacting with microenvironments. In this work, the local topography of the ECM has been mimicked through micropillar array substrates. MDA-MB-231 and MCF-7 breast cancer cells, exhibiting high and low metastatic potential, respectively, were analyzed. Differences in morphology and migration of the cells were investigated by examining the cell spreading area, circularity, aspect ratio, migration speed, and migration path. This work encountered that none of the studied cell lines have preferential orientation migrating on uniform patterns. In contrast, cell migration on graded patterns shows preferential orientation along the longitudinal direction from sparser to denser zones which is significantly influenced by substrate stiffness and indicates that both cell lines can sense the spacing gradient and respond to this topographical cue. The migration speed of the breast cancer cell lines significantly decreases from the sparse to medium to dense zones, registering higher values for the MDA-MB-231.

Effect of a three-dimensional nanotube array substrate on photocatalytic conversion performance of CO2 gas to methanol by amine-loaded CuO/ZnO catalysts

The photocatalytic conversion of CO2 gas into energy-dense hydrocarbons holds the potential to address both environmental and energy problems. Catalysts consisting of CuO clusters/nanoparticles and ZnO nanorods on a metallic nanotube array (MeNTA) silicon substrate were utilized for CO2 reduction. The surface of the catalysts was modified with 3-amino-propyltriethoxysilane (APTES), the amine terminal of which can selectively bind CO2 gas. When photocatalytic CO2 reduction was performed with varying APTES and CuO contents, the highest methanol production of 4.5 mmol/g(catalyst) was obtained at 10 wt% APTES and 7.5 mM CuO contents. The high yield in the present work in comparison with previous reports is due to some advantages of the present catalytic system such as its enhanced activity, significant selectivity, and easy production: Nanometer-sized CuO produced by femtosecond pulse laser irradiation provides a larger active surface per volume and a free surface without a protector, which is favorable for advancing the catalytic activity. The formation of a heterojunction interface in a nanocomposite of p-type CuO and n-type ZnO increases holes at the valence band level of CuO, resulting in advantageous photovoltaic efficiency. The introduction of APTES on the catalyst surface enhances CO2 adsorption and brings about CO2 gas near the catalyst to accelerate the reaction rate. Finally, a three-dimensional tube array on the substrate enlarges the surface per volume for catalyst-loading compared to the two-dimensional substrate. Thus, the proposed catalytic system consisting of amine-loaded CuO/ZnO constructed on a three-dimensional nanotube array substrate is preferable for the photocatalytic conversion of CO2 gas to methanol.

Multi-dimensional synergistically coupled signal enhancement on nano-micro hierarchical anemone-like substrates integrated SERS-based microfluidic sensor

We designed and prepared a novel anemone-like array substrate (ALAS) integrated pump-free microfluidic sensor based on surface-enhanced Raman spectroscopy (SERS). ALAS substrate forms ordered nanoantenna arrays on polystyrene (PS) nanospheres, which can improve the light-capturing efficiency of the substrate and induce surface plasmon resonance. It successfully achieved multi-dimensional enhancement of electric field coupling and further enhanced the Raman scattering signals of the Raman reporter molecules. Driven by a capillary pump, the seawater containing Hg2+ can be loaded in 100 s without the need for cumbersome syringe pumps. Our results demonstrated that the integrated sensor exhibits excellent responsiveness in detecting Hg2+ within the concentration range of 10−7 to 10−12 mol L−1. The detection limit can reach 1 pmol L−1. Therefore, we believe that this ALAS integrated microfluidic sensor provides a promising solution for the rapid and sensitive detection of Hg2+.

Large-area Ag “sesame cake-like” arrays with high-density hotspots for efficient SERS analysis

Nanogap-rich plasmonic metal nanostructures have attracted great attention in surface enhanced Raman scattering (SERS) applications due to their prominent performances. Herein, utilizing enhanced surface diffusion of Ag atoms on a low energy surface, a facile fabrication strategy is developed to construct a large-area Ag “sesame cake-like” (ASCL) array by combining the ultra-thin alumina mask (UTAM) and vapor deposition technique. Owing to the multiple plasmonic coupling effects, the proposed ASCL array possesses enormous hotspots responsible for remarkable sensitivity with an enhancement factor of 4.9 × 106, excellent reproducibility with a relative standard deviation (RSD) smaller than 7.12 % and obvious polarization independent in SERS analysis, which are confirmed by numerical simulations. In addition, the possibility to be fabricated on the flexible substrate makes the ASCL array substrate well meet the increasing demands for practical applications in the fields of food safety, health and environment monitoring.

Precision classification and quantitative analysis of bacteria biomarkers via surface-enhanced Raman spectroscopy and machine learning

The SERS spectra of six bacterial biomarkers, 2,3-DHBA, 2,5-DHBA, Pyocyanin, lipoteichoic acid (LTA), Enterobactin, and β-carotene, of various concentrations, were obtained from silver nanorod array substrates, and the spectral peaks and the corresponding vibrational modes were identified to classify different spectra. The spectral variations in three different concentration regions due to various reasons have imposed a challenge to use classic calibration curve methods to quantify the concentration of biomarkers. Depending on baseline removal strategy, i.e., local or global baseline removal, the calibration curve differed significantly. With the aid of convolutional neural network (CNN), a two-step process was established to classify and quantify biomarker solutions based on SERS spectra: using a specific CNN model, a remarkable differentiation and classification accuracy of 99.99 % for all six biomarkers regardless of the concentration can be achieved. After classification, six regression CNN models were established to predict the concentration of biomarkers, with coefficient of determination R2 > 0.97 and mean absolute error (MAE) < 0.27. The feature of important calculations indicates the high classification and quantification accuracies were due to the intrinsic spectral features in SERS spectra. This study showcases the synergistic potential of SERS and advanced machine learning algorithms and holds significant promise for bacterial infection diagnostics.

5‐1: Incell Electromagnetic Resonance Touch LCD with Antenna Coil Integrated in Array Substrate

In this paper, we present an incell integrated electromagnetic resonance(EMR) active pen solution that can form a closed magnetic induction coil without additional panel manufacturing process compared to a regular L CD panel. The Incell EMR touch solution exhibits extremely high accuracy and linearity, such as 0.16mm accuracy and 0.36mm linearity, respectively. Our solution shows significant advantages over capacitive active pen solution especially in slow scribing scenario without any sawtooth phenomenon, achieving a highly intergrated, lightweight, high‐performance, and low‐power consumption solution for handwriting active pen LCD.

31‐4: Curved and Fast Response Time Vertical‐alignment (VA) Liquid Crystal Gaming Display Development

We propose a fast response scheme for high definition curved VA LCD Panel. We make curved panel with different dual PI on the Array and CF substrate to obtain different pretilt angle. Fast response liquid crystal (LC) and Larger storage capacitance are used on curved panel, we can obtain fast response time without over driving (GTGavg= 6.2ms, GTGmax =9.1ms).

Efficient Microstrip Monopole Antenna Design for Multi Technology Wireless Applications

The demand for compact, efficient antennas capable of supporting multiple wireless communication standards continues to drive innovation in the field. In this paper, we present a novel approach to designing microstrip monopole antennas, leveraging a unique set of design equations to achieve superior performance across 3GHz and 6GHz frequency bands. Additionally, we explore the development of array antennas by combining two microstrip monopoles, offering enhanced gain and radiation characteristics compared to single-element designs. By varying array substrate material, we aim to further optimize performance for applications such as WiFi, LTE, and WiMax. Keywords- Microstrip antenna, broadband monopole antenna, dual band monopole antenna, compact monopole.

Detection and Identification of Pesticides in Fruits Coupling to an Au-Au Nanorod Array SERS Substrate and RF-1D-CNN Model Analysis.

In this research, a method was developed for fabricating Au-Au nanorod array substrates through the deposition of large-area Au nanostructures on an Au nanorod array using a galvanic cell reaction. The incorporation of a granular structure enhanced both the number and intensity of surface-enhanced Raman scattering (SERS) hot spots on the substrate, thereby elevating the SERS performance beyond that of substrates composed solely of an Au nanorod. Calculations using the finite difference time domain method confirmed the generation of a strong electromagnetic field around the nanoparticles. Motivated by the electromotive force, Au ions in the chloroauric acid solution were reduced to form nanostructures on the nanorod array. The size and distribution density of these granular nanostructures could be modulated by varying the reaction time and the concentration of chloroauric acid. The resulting Au-Au nanorod array substrate exhibited an active, uniform, and reproducible SERS effect. With 1,2-bis(4-pyridyl)ethylene as the probe molecule, the detection sensitivity of the Au-Au nanorod array substrate was enhanced to 10-11 M, improving by five orders of magnitude over the substrate consisting only of an Au nanorod array. For a practical application, this substrate was utilized for the detection of pesticides, including thiram, thiabendazole, carbendazim, and phosmet, within the concentration range of 10-4 to 5 × 10-7 M. An analytical model combining a random forest and a one-dimensional convolutional neural network, referring to the important variable-one-dimensional convolutional neural network model, was developed for the precise identification of thiram. This approach demonstrated significant potential for biochemical sensing and rapid on-site identification.

Characteristic substance analysis and rapid detection of bacteria spores in cooked meat products by surface enhanced Raman scattering based on Ag@AuNP array substrate

BackgroundBacterial spores are the main potential hazard in medium- and high-temperature sterilized meat products, and their germination and subsequent reproduction and metabolism can lead to food spoilage. Moreover, the spores of some species pose a health and safety threat to consumers. The rapid detection, prevention, and control of bacterial spores has always been a scientific problem and a major challenge for the medium and high-temperature meat industry. Early and sensitive identification of spores in meat products is a decisive factor in contributing to consumer health and safety. ResultsIn this study, we developed a novel and stable Ag@AuNP array substrate by using a two-step synthesis approach and a liquid-interface self-assembly method that can directly detect bacterial spores in actual meat product samples without the need for additional in vitro bacterial culture. The results indicate that the Ag@AuNP array substrate exhibits high reproducibility and Raman enhancement effects (1.35 × 105). The differentiation in the Surface enhanced Raman scattering (SERS) spectra of five bacterial spores primarily arises from proteins in the spore coat and inner membrane, peptidoglycan of cortex, and Ca2⁺-DPA within the spore core. The correct recognition rate of linear discriminant analysis for spores in the meat product matrix can reach 100 %. The average recovery accuracy of the SERS quantitative model was at around 101.77 %, and the limit of detection can reach below 10 CFU/mL. SignificanceIt provides a promising technological strategy for the characteristic substance analysis and timely monitoring of spores in meat products.

A novel ratiometric aptasensor based on SERS for accurate quantification of cardiac troponin I

Cardiac troponin I (cTnI) as a biomarker of acute myocardial infarction (AMI) is directly related to myocardial damage. Here, we proposed a ratiometric aptamer-sensor (aptasensor) for quantifying cTnI based on surface-enhanced Raman scattering (SERS), in which the uniform and high-density gold array was decorated with highly specific aptamer Tro4 to form the capture substrate for target cTnI. Firstly, gold array was labeled with 5, 5’-dithio bis-(2-nitrobenzoic acid) (DTNB) as one SERS signal to effectively realize signal self-calibration. In addition, aptamer Tro6 targeting cTnI and 4-mercaptobenzoic acid (4-MBA) as another SERS signal were anchored to porous gold (pAu) to form a pAu signal probe. In the presence of cTnI, the capture substrate and pAu signal probes could build a typical sandwich structure, thus the ratio of SERS peak intensity (I4-MBA/IDTNB) could be used to quantify cTnI. The ratiometric aptasensor showed a good linearity from 0.001 to 100 ng mL−1 and a low detection limit down to 0.27 pg mL−1. Own to dual signal output and the gold array substrate, the aptasensor exhibited good reproducibility, high sensitivity and accuracy. When the aptasensor was applied to the quantification of cTnI in human serum samples, the detection performance was comparable to that of enzyme-linked immunosorbent assay (ELISA), proving that the sensor has a good prospect in the diagnosis of AMI disease.

Processivity and specificity of histone acetylation by the male-specificlethal complex.

Acetylation of lysine 16 of histone H4 (H4K16ac) stands out among the histone modifications, because it decompacts the chromatin fiber. The metazoan acetyltransferase MOF (KAT8) regulates transcription through H4K16 acetylation. Antibody-based studies had yielded inconclusive results about the selectivity of MOF to acetylate the H4 N-terminus. We used targeted mass spectrometry to examine the activity of MOF in the male-specificlethal core (4-MSL) complex on nucleosome array substrates. This complex is part of the Dosage Compensation Complex (DCC) that activates X-chromosomal genes in male Drosophila. During short reaction times, MOF acetylated H4K16 efficiently and with excellent selectivity. Upon longer incubation, the enzyme progressively acetylated lysines 12, 8 and 5, leading to a mixture of oligo-acetylated H4. Mathematical modeling suggests that MOF recognizes and acetylates H4K16 with high selectivity, but remains substrate-bound and continues to acetylate more N-terminal H4 lysines in a processive manner. The 4-MSL complex lacks non-coding roX RNA, a critical component of the DCC. Remarkably, addition of RNA to the reaction non-specifically suppressed H4 oligo-acetylation in favor of specific H4K16 acetylation. Because RNA destabilizes the MSL-nucleosome interaction in vitro we speculate that RNA accelerates enzyme-substrate turn-over in vivo, thus limiting the processivity of MOF, thereby increasing specific H4K16 acetylation.

Fully Enclosed Composite Micro/Nano‐Package for High‐Quality Micro‐LED Display Pixels and In Situ Nanoimprint Technology

AbstractMicro/mini‐light emitting diode (LED) arrays are regarded as the most promising next generation of display devices. However, the inherent Lambertian radiation of LED chips results in a significant pixel crosstalk. To improve the display quality, high‐quality micro/mini‐LED display pixels with fully enclosed composite micro/nano‐packages and in situ nanoimprint technology are proposed and demonstrated in this work. The nanoimprint template is designed as a composite structure comprising an intermediate sandwich cavity array and thin‐bottom nanostructure layer. Contact is maintained between the template and LED chips array substrate. By vacuuming the sealed sandwich cavities, the thin‐bottom nanostructure layer is deformed to drive the upward protrusion of the liquid optical polymer. Moreover, the nanocavities on the thin nanostructure layer are fully filled by the polymer, forming a composite micro/nano‐package. The characteristics of the composite micro/nano‐package, such as the aperture and protrusion height, can be flexibly adjusted by changing the template structure or process parameters. A 6 × 8 array LED chips display device enclosed by a composite micro/nanopackage is developed. The divergence angle of the single LED chip decreases to 72° from the original 138°, the light‐extraction efficiency increases18.4%, and the luminescence spectrum and current‐voltage characteristics changes only minimally.