Semiconductor Fabrication Research Articles

Lubricant-Coated Organ-on-a-Chip for Enhanced Precision in Preclinical Drug Testing.

In drug discovery, human organ-on-a-chip (organ chip) technology has emerged as an essential tool for preclinical testing, offering a realistic representation of human physiology, real-time monitoring, and disease modeling. Polydimethylsiloxane (PDMS) is commonly used in organ chip fabrication owing to its biocompatibility, flexibility, transparency, and ability to replicate features down to the nanoscale. However, the porous nature of PDMS leads to unintended absorption of small molecules, critically affecting the drug response analysis. Addressing this challenge, the precision drug testing organ chip (PreD chip) is introduced, an innovative platform engineered to minimize small molecule absorption while facilitating cell culture. This chip features a PDMS microchannel wall coated with a perfluoropolyether-based lubricant, providing slipperiness and antifouling properties. It also incorporates an ECM-coated semi-porous membrane that supports robust multicellular cultures. The PreD chip demonstrates its outstanding antifouling properties and resistance to various biological fluids, small molecule drugs, and plasma proteins. In simulating the human gut barrier, the PreD chip demonstrates highly enhanced sensitivity in tests for dexamethasone toxicity and is highly effective in assessing drug transport across the human blood-brain barrier. These findings emphasize the potential of the PreD chip in advancing organ chip-based drug testing methodologies.

Substrate Neutrality for Obtaining Block Copolymer Vertical Orientation.

Nanopatterning methods utilizing block copolymer (BCP) self-assembly are attractive for semiconductor fabrication due to their molecular precision and high resolution. Grafted polymer brushes play a crucial role in providing a neutral surface conducive for the orientational control of BCPs. These brushes create a non-preferential substrate, allowing wetting of the distinct chemistries from each block of the BCP. This vertically aligns the BCP self-assembled lattice to create patterns that are useful for semiconductor nanofabrication. In this review, we aim to explore various methods used to tune the substrate and BCP interface toward a neutral template. This review takes a historical perspective on the polymer brush methods developed to achieve substrate neutrality. We divide the approaches into copolymer and blended homopolymer methods. Early attempts to obtain neutral substrates utilized end-grafted random copolymers that consisted of monomers from each block. This evolved into side-group-grafted chains, cross-linked mats, and block cooligomer brushes. Amidst the augmentation of the chain architecture, homopolymer blends were developed as a facile method where polymer chains with each chemistry were mixed and grafted onto the substrate. This was largely believed to be challenging due to the macrophase separation of the chemically incompatible chains. However, innovative methods such as sequential grafting and BCP compatibilizers were utilized to circumvent this problem. The advantages and challenges of each method are discussed in the context of neutrality and feasibility.

Performance Evaluation of Physical Properties on Zinc Sulfide (ZnS)-based Field Effect Transistor

The paper presents the performance evaluation of physical properties on Zinc Sulfide (ZnS)-based Field Effect Transistor. The most famous III-V compound-based semiconductor devices have several affected to the environment and the toxic contents are directly responded to the society. Due to the lack of technology on nontoxic compound-based semiconductor device fabrications, the novel device with II-VI compound materials are challenging issues for the environments. The specific objectives of doing research on fabrication of II-VI compound-based semiconductor devices in advanced laboratories are to emphasize the numerical modeling of the device structure and designing the FET based on ZnS material, to contribute the mathematical model for physical characteristics of the FET structure and the modification of the device structure will be easily established by using numerical simulation. The mathematical analyses on physical properties of device structure with ZnS material are confirmed and observed the several properties of electrical and electronic characteristics. The detailed implementations for ZnS-based FET devices are performed and evaluated the performance of the developed FET devices. There are two steps analyses in physical properties of ZnS-based FET devices with numerical implementation by MATLAB languages. The results observed in this study could be confirmed with the recent works from several research laboratories and the developed ZnS-based FET devices could be utilized in high performance wide band applications on switching in the power electronics and amplification purposes in modern amplifier design in real world applications.

Design of a temperature sensor based on a valley photonic crystal Mach–Zehnder interferometer

With the development of photonics device integration technology, Mach–Zehnder interferometers (MZIs) are widely applied as sensors because they are extremely sensitive to environmental parameters. Conventional MZI sensors are generally large and unsuitable for high-density integration. MZIs based on photonic crystals (PCs) can significantly improve compactness and are suitable for integration. However, PC MZIs experience substantial optical loss due to scattering. Based on the spin-valley locking effect that can achieve defect-immune unidirectional transmission of topological edge states in valley photonic crystals (VPCs), we propose an MZI sensor based on a VPC structure and apply it in temperature sensing for what we believe is the first time. The interference peaks redshift with an increase in the temperature, which allows accurate sensing of the temperature shift with a high sensitivity of 0.06 nm/K in the temperature range of 100 K–750 K. The ultracompact device has a small footprint of 9.26×7.99µm2 and a high forward transmittance of 0.88. The design is suitable for the current complementary metal-oxide semiconductor (CMOS) fabrication technique. Thus, it will find broad applications in integrated photonics, optical communication, and integrated temperature sensing.

Separable contextual graph neural networks to identify tailgating-oriented traffic congestion

Identifying largescale traffic congestion with thousands of robots is a complicated task involving structured-data graphical modeling, and it has recently gained more research attention. This study aims to model traffic metrics that exhibit negative correlations in specific spatiotemporal contexts of automated material handling systems in semiconductor manufacturing. Numerous studies have focused on detecting vehicle congestion using multivariate time-series data. However, they faced challenges regarding the understanding of the complex graph structural joint spatiotemporal dynamics of the traffic rails. Existing methods fail to distinguish between congestion caused by high traffic volumes and nondisruptive delivery robot operations, such as parking and hoisting. This study introduces a novel approach to detect tailgating-oriented congestion using separable contextual graph neural networks (SC-GNNs). The proposed method employs deviation-based anomaly detection with attentive GNNs to capture spatial correlations and temporal dependencies. SC-GNNs were proposed for dual metrics with distinct characteristics, and dynamic thresholds were applied for each GNN to ensure reliable and interpretable anomaly detection. To demonstrate the outperformance of the proposed method, we conducted simulation experiments via a high-fidelity simulator similar to actual semiconductor fabrication. The experimental results showed that our method achieved both a 36% reduction in the false positive rate and a 32% decrease in the equal error rate compared to the best performance of existing state-of-the-art anomaly detection models. Overall, the proposed approach significantly improved the accuracy and interpretability of anomaly detection in multivariate time series, particularly effective in the context of identifying anomalies related to traffic congestion tailgating.

3D-Printed SERS Chips for Highly Specific Detection of Denatured Type I and IV Collagens in Blood for Early Hepatic Fibrosis Diagnosis.

Hepatic fibrosis, the insidious progression of chronic liver scarring leading to life-threatening cirrhosis and hepatocellular carcinoma, necessitates the urgent development of noninvasive and precise diagnostic methodologies. Denatured collagen emerges as a critical biomarker in the pathogenesis of hepatic fibrosis. Herein, we have for the first time developed 3D-printed collagen capture chips for highly specific surface-enhanced Raman scattering (SERS) detection of denatured type I and type IV collagen in blood, facilitating the early diagnosis of hepatic fibrosis. Employing a novel blend of denatured collagen-targeting peptide-modified silver nanoparticle probes (Ag@DCTP) and polyethylene glycol diacrylate (PEGDA), we engineered a robust ink for the 3D fabrication of these collagen capture chips. The chips are further equipped with specialized SERS peptide probes, Ag@ICTP@R1 (S-I) and Ag@IVCTP@R2 (S-IV), tailored for the targeted detection of type I and IV collagen, respectively. The SERS chip platform demonstrated exceptional specificity and sensitivity in capturing and detecting denatured type I and IV collagen, achieving detection limits of 3.5 ng/mL for type I and 3.2 ng/mL for type IV collagen within a 10-400 ng/mL range. When tested on serum samples from hepatic fibrosis mouse models across a spectrum of fibrosis stages (S0-S4), the chips consistently measured denatured type I collagen and detected a progressive increase in type IV collagen concentration, which correlated with the severity of fibrosis. This novel strategy establishes a benchmark for the multiplexed detection of collagen biomarkers, enhancing our capacity to assess the stages of hepatic fibrosis.

Scaling up multispectral color filters with binary lithography and reflow (BLR).

Efforts to increase the number of filters are driven by the demand for miniaturized spectrometers and multispectral imaging. However, processes that rely on sequential fabrication of each filter are cost ineffective. Herein, we introduce an approach to produce at least 16 distinct filters based on a single low-resolution lithographic step with minimum feature size of 0.6 μm. Distinct from grayscale lithography, we employ standard binary lithography but achieve height variations in polymeric resist through a post-development reflow process. The resulting transparent polymeric films were incorporated in Fabry-Perot cavity structures with cavity thickness ranging from 90 to 230 nm to produce transmittance across the visible spectrum. This binary lithography and reflow (BLR) process demonstrates control of the dielectric layer thickness down to ∼15 nm. This new process provides a cost-effective alternative to traditional techniques in fabricating microscopic transmission filters, and other applications where precise thickness variation across the substrate is required.

Experimental conditions for room temperature ferromagnetism in Fe-doped SnO2 via mechanochemical milling and thermal treatment

Identifying optimal experimental conditions, preferably through a simple and cost-effective method, for the fabrication of oxide-diluted magnetic semiconductors, such as Fe-doped SnO2, holds great significance in the quest for spintronic materials operating at room temperature (RT). While mechanochemical milling is a well-established technique meeting these requirements, its numerous milling variables necessitate careful consideration of restricted experimental conditions. In this study, we present some experimental mechanochemical milling conditions to prepare impurity-free iron-doped tin dioxide nanoparticles exhibiting RT ferromagnetic signal. To achieve this, we investigated the effects of milling time, the choice of the starting Sn reactant, and iron concentration on the purity of Sn1−xFexO2 (x = 0, 0.03, and 0.05) nanopowders obtained through mechanochemical milling followed by thermal treatment. Characterization through XRD, XANES, and EXAFS at the Fe K-edge, RT Raman spectroscopy, 119Sn and 57Fe Mössbauer spectroscopies, and magnetic measurements was conducted. Among the experimental techniques, micro-Raman spectroscopy proved the most effective in detecting the formation of hematite as an impurity phase. Our results indicate that extending the milling time to 12 h, as opposed to 3 h, employing anhydrous SnCl2, instead of SnCl2·2H2O and using the low iron concentration of x = 0.03, results in proper conditions for producing impurity-free samples with a robust RT ferromagnetic signal. The oxidation states for iron and tin ions were determined to be 3+ and 4+, respectively, with both occupying octahedral sites, suggesting iron’s replacement of tin. Our findings propose that both the bound magnetic polaron and RKKY models offer potential explanations for the origin of the ferromagnetic signal observed at room temperature in Sn0.97Fe0.03O2 sample milled for 12 h.

CMOS-compatible photonic integrated circuits on thin-film ScAlN

Scandium aluminum nitride (ScAlN) has recently emerged as an attractive material for integrated photonics due to its favorable nonlinear optical properties and compatibility with complementary metal–oxide semiconductor (CMOS) fabrication. Despite the promising and versatile material properties, it is still an outstanding challenge to realize low-loss photonic circuits on thin-film ScAlN-on-insulator wafers. Here, we present a systematic study on the material quality of sputtered thin-film Sc0.1Al0.9N produced in a CMOS-compatible 200 mm line, including its crystallinity, roughness, and second-order optical nonlinearity, and developed an optimized fabrication process to yield 400 nm thick, fully etched waveguides. With surface polishing and annealing, we achieve micro-ring resonators with an intrinsic quality factor as high as 1.47 × 105, corresponding to a propagation loss of 2.4 dB/cm. These results serve as a critical step toward developing future large-scale, low-loss photonic integrated circuits based on ScAlN.

Templated Growth of In2S3 in Ti3C2TX MXene with Enhanced Photocatalytic Properties

The growth of ultrathin semiconductors is advantageous for photocatalysis due to improved photophysical properties and reduced charge recombination. Along these lines, templating the growth of semiconductors in confined spaces can allow control over semiconductor growth while also conferring the properties of the template to provide composite nanomaterial hybrids. Herein, the semiconductor In2S3 is grown in the organically‐modified interlayer space of Ti3C2TX MXene, a versatile 2D material with metallic character and broadband light absorption. The growth of 1–2 nm thick layers of In2S3 in the interlayer of MXene leads to a drastic increase in photocatalytic properties and light‐induced charge generation due to decreased interfacial charge transfer resistance. Interestingly, the hydrothermal conditions of In2S3 growth lead to partial oxidation of Ti3C2TX MXene to form anatase TiO2 nanocrystals, although this effect is strongly limited by increased In2S3 precursors due to passivation of the MXene surface. MXenes serve as effective templates for the confined growth of semiconductors, emphasizing the potential of MXene as a template for 2D material heterostructures. Overall, this work further develops MXene‐based 2D material composites, offering insights into the origins of the enhanced photocatalytic and photoelectrochemical properties, toward improvements in energy production and aqueous phase catalysis.

Enhancing metasurface fabricability through minimum feature size enforcement.

The metasurfaces have shown great potential for miniaturizing conventional optics while offering extended flexibility. Recently, there has been considerable interest in using algorithms to generate meta-atom shapes for these metasurfaces, as they offer vast design freedom and not biased by the human intuition. However, these complex designs significantly increase the difficulty of fabrication. To address this, we introduce a design process that rigorously enforces the fabricability of both the material-filled (fill) and empty (void) regions in a metasurface design. This process takes into account specific constraints regarding the minimum feature size for each region. Additionally, it corrects any violations of these constraints across the entire device, ensuring only minimal impact on performance. Our method provides a practical way to create metasurface designs that are easy to fabricate, even with complex shapes, hence improving the overall production yield of these advanced meta-optical components.

Effect of internal structure of a batch-processing wet-etch reactor on fluid flow and heat transfer

Batch-processing wet-etch reactors are the key equipment widely used in chip fabrication, and their performance is largely affected by the internal structure. This work develops a three-dimensional computational fluid dynamics (CFD) model considering heat generation of wet-etching reactions to investigate the fluid flow and heat transfer in the wet-etch reactor. The backflow is observed below and above the wafer region, as the flow resistance in this region is high. The temperature on the upper part of a wafer is higher due to the accumulation of reaction heat, and the average temperature of the side wafer is highest as its convective heat transfer is weakest. Narrowing the gap between wafer and reactor wall can force the etchant to flow in the wafer region and then facilitate the convective heat transfer, leading to better within-wafer and wafer-to-wafer etch uniformities. An inlet angle of 60° balances fluid by-pass and mechanical energy loss, and it yields the best temperature and etch uniformities. The batch with 25 wafers has much wider flow channels and much lower flow resistance compared with that with 50 wafers, and thus it shows better temperature and etch uniformities. These results and the CFD model should serve to guide the optimal design of batch-processing wet-etch reactors.

Visualization and Analysis of Mapping Knowledge Domain of Fluid Flow Related to Microfluidic Chip.

Microfluidic chips are important tools to study the microscopic flow of fluid. To better understand the research clues and development trends related to microfluidic chips, a bibliometric analysis of microfluidic chips was conducted based on 1115 paper records retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to analyze the distribution of annual paper quantity, country/region distribution, subject distribution, institution distribution, major source journals distribution, highly cited papers, coauthor cooperation relationship, research knowledge domain, research focuses, and research frontiers, and a knowledge domain map was drawn. The results show that the number of papers published on microfluidic chips increased from 2010 to 2023, among which China, the United States, Iran, Canada, and Japan were the most active countries in this field. The United States was the most influential country. Nanoscience, energy, and chemical industry and multidisciplinary materials science were the main fields of microfluidic chip research. Lab on a Chip, Microfluidics and Nanofluidics, and Journal of Petroleum Science and Engineering were the main sources of papers published. The fabrication of chips, as well as their applications in porous media flow and multiphase flow, is the main knowledge domain of microfluidic chips. Micromodeling, fluid displacement, wettability, and multiphase flow are the research focuses in this field currently. The research frontiers in this field are enhanced oil recovery, interfacial tension, and stability.

High-Resolution and Low-Noise Single-Molecule Sensing with Bio-Inspired Solid-State Nanopores.

Solid-state nanopores have been extensively explored as single-molecule sensors, bearing the potential for the sequencing of DNA. Although they offer advantages in terms of high mechanical robustness, tunable geometry, and compatibility with existing semiconductor fabrication techniques in comparison with their biological counterparts, efforts to sequence DNA with these nanopores have been hampered by insufficient spatial resolution and high noise in the measured ionic current signal. Here we show that these limitations can be overcome by the use of solid-state nanopores featuring a thin, narrow constriction as the sensing region, inspired by biological protein nanopores that have achieved notable success in DNA sequencing. Our extensive molecular dynamics simulations show that these bio-inspired nanopores can provide high spatial resolution equivalent to 2D material nanopores and, meanwhile, significantly inhibit noise levels. A theoretical model is also provided to assess the performance of the bio-inspired nanopore, which could guide its design and optimization.

Exploring tunable single-wavelength detection schemes for guided-mode resonance sensors

We explore guided-mode resonant (GMR) structures in an unconventional way for low-cost yet effective bio-sensing applications. In contrast to regular broadband source-based wavelength interrogation techniques, single wavelength-based measurements can successfully eliminate the requirement of a costly spectrometer for rapid label-free detection and analysis. We have fabricated a silicon–nitride grating-waveguide structure and investigated it theoretically as well as experimentally under normal, angular, and conical incidences following an all-in-one transmission geometry. Such studies avoid unnecessary fabrication of multiple chips and promote a wide operational range of the GMR sensor. To validate the proposed cost-effective intensity-based sensing, we have analyzed our fabricated single GMR chip under different combinations of two-axis rotation to confirm its suitability under commonly available laser sources. Finally, using a He-Ne laser, a sensitivity of ∼ 166 mW/RIU is recorded experimentally on an average for the fabricated GMR device, operating at the resonant wavelength of 632.8 nm. The current study provides an in-depth investigation to promote possibilities for utilizing GMR structures in an inexpensive intensity-based bio-detection scheme through the demonstrated proof-of-concept.

Hybrid Semiconductor Wafer Inspection Framework via Autonomous Data Annotation

Abstract In smart manufacturing, semiconductors play an indispensable role in collecting, processing, and analyzing data, ultimately enabling more agile and productive operations. Given the foundational importance of wafers, the purity of a wafer is essential to maintain the integrity of the overall semiconductor fabrication. This study proposes a novel automated visual inspection (AVI) framework for scrutinizing semiconductor wafers from scratch, capable of identifying defective wafers and pinpointing the location of defects through autonomous data annotation. Initially, this proposed methodology leveraged a texture analysis method known as gray-level co-occurrence matrix (GLCM) that categorized wafer images—captured via a stroboscopic imaging system—into distinct scenarios for high- and low-resolution wafer images. GLCM approaches further allowed for a complete separation of low-resolution wafer images into defective and normal wafer images, as well as the extraction of defect images from defective low-resolution wafer images, which were used for training a convolutional neural network (CNN) model. Consequently, the CNN model excelled in localizing defects on defective low-resolution wafer images, achieving an F1 score—the harmonic mean of precision and recall metrics—exceeding 90.1%. In high-resolution wafer images, a background subtraction technique represented defects as clusters of white points. The quantity of these white points determined the defectiveness and pinpointed locations of defects on high-resolution wafer images. Lastly, the CNN implementation further enhanced performance, robustness, and consistency irrespective of variations in the ratio of white point clusters. This technique demonstrated accuracy in localizing defects on high-resolution wafer images, yielding an F1 score greater than 99.3%.

In-line imaging and recognition of flip chip fabrication defects by real-time photoacoustic remote sensing system

Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication. We first propose a real-time PARS imaging method based on continuous acquisition combined with parallel processing image reconstruction to achieve real-time imaging during the scanning of flip-chip samples, reducing reconstruction time from an average of approximately 1134 ms to 38 ms. Subsequently, we propose improved YOLOv7 with space-to-depth block (IYOLOv7-SPD), an enhanced deep learning defect recognition method, for accurate in-line recognition and localization of microscopic defects during the PARS real-time imaging process. The experimental results validate the viability of the proposed system for enhancing the lifespan and yield of flip-chip products in chip manufacturing facilities.

On-chip ultra-high rejection and narrow bandwidth filter based on coherency-broken cascaded cladding-modulated gratings

Bragg filters are of essential importance for chip-scale photonic systems. However, the implementation of filters with sub-nanometer bandwidth and rejection beyond 70 dB is hindered by the high index contrast of the silicon-on-insulator platform, which makes filters prone to fabrication imperfections. In this paper, we propose to combine coherency-broken cascading architecture and cladding modulation to circumvent the intrinsic limitation. The cascading architecture effectively prevents the accumulation of phase errors, while the cladding modulation offers additional design freedom to reduce the coupling coefficient. A bimodal Bragg filter with a testing-equipment-limited rejection level of 74 dB and a 40 dB bandwidth of 0.44 nm is experimentally demonstrated. The minimum feature size is 90 nm, which significantly relieves the fabrication constraints.

Optimizing MMIC performance: The synergy of AI models and heterogeneous integration process

AbstractThis study presents a novel approach for optimizing the parameters of monolithic microwave integrated circuit (MMIC) functional units using machine‐learning techniques and multi‐objective optimization algorithms. We utilize advanced machine‐learning methods, including random forest, artificial neural networks (ANNs), and recurrent neural networks (RNNs), to construct highly accurate models that predict the performance of these units. These models are subsequently integrated with a multi‐objective optimization algorithm, specifically the multi‐objective particle swarm optimization (MOPSO), to generate inverse design solutions for both the geometric designs of the units and the fabrication parameters of the heterogeneous integration process. Our approach, which has been validated through chip fabrication and testing, has demonstrated its robustness as a tool for achieving optimal MMIC designs. It not only reduces the design time but also enhances the manufacturability of MMICs, thereby opening new avenues in microwave and RF circuit design.

Subtractive manufacturing of polymer-derived ceramic composite thick film sensor based on ultrafast laser etching

Polymer-derived ceramics (PDCs) are increasingly recognized as promising materials for high-temperature thin/thick film sensors (HTTFSs). However, a large linewidth and poor dimensional accuracy have severely restricted the practical application of PDCs HTTFSs. Our study employed a picosecond laser to precisely pattern the polymer-derived ceramic (PDC) thick film while applying no obvious damage to the interface between ceramic and substrate. Through parameters optimization, the laser-affected area was minimized to 6 μm wide, and a minimum feature size of about 30 μm was achieved. Furthermore, 7 rounds of high-temperature tests of the patterned film revealed good temperature-resistance repeatability within a temperature range of up to 800 °C. To demonstrate practical application potential, we successfully fabricated a heat flux sensor, and it exhibited a sensitivity of 1.32 mV/(kW/m2), a response time of 600 ms, and excellent repeatability over a range of 0–75.4 kW/m2. In summary, this paper proposes a novel approach toward miniaturizing the linewidth of the polymer-derived ceramics thick film sensor, showing significant potential for precise measurements in extreme environments.