Semiconductor Process Research Articles

Fabrication and Characterization of Photovoltaic Microgenerators Using the Complementary Metal Oxide Semiconductor Process.

This study develops a photovoltaic microgenerator based on the complementary metal oxide semiconductor (CMOS) process. The photovoltaic microgenerator converts the absorbed light energy into electrical energy using the photovoltaic effect. The material for the photovoltaic microgenerator is silicon, and its structure consists of patterned p-n junctions. The design of the photovoltaic microgenerator utilizes a grid-like shape, forming a large-area p-n junction with a patterned p-doping and N-well structure to enhance the photocurrent and improve the device's performance. The photovoltaic microgenerator is fabricated employing the CMOS process with post-processing step. Post-processing is applied to enhance the microgenerator's light absorption and energy-conversion efficiency. This involves using wet etching with buffered-oxide etch (BOE) to remove the silicon dioxide layer above the p-n junctions, allowing direct illumination of the p-n junctions. The area of the photovoltaic microgenerator is 0.79 mm2. The experimental results show that under an illumination intensity of 1000 W/m2, the photovoltaic microgenerator exhibits an open-circuit voltage of 0.53 V, a short-circuit current of 233 µA, a maximum output power of 99 µW, a fill factor of 0.8, and an energy-conversion efficiency of 12.5%.

High-Speed Design with Separated Tapering for Reducing Cogging Torque and Torque Ripple of a 3 kW Dry Vacuum Pump Motor for the ETCH Process

This paper proposes a design method to reduce cogging torque and torque ripple in the concentrated winding of IPMSMs (Interior Permanent Magnet Synchronous Motors) used in motors for the semiconductor ETCH process. IPMSMs can utilize reluctance torque through the difference in inductance between the d axis and q axis, but they are at a disadvantage in terms of reducing cogging torque while tapering the rotor and stator to reduce torque ripple. In addition, the existing single tapering can push the permanent magnets into the rotor. If the rotor’s permanent magnets are embedded, the magnetic reluctance will increase, and the overall performance of the motor will decrease. However, an optimum design method was derived in which the magnets do not move during rotor tapering. This geometric design is an optimum design method that reduces cogging torque and torque ripple. This paper compares and analyzes four models, the concentrated winding model, distributed winding model, conventional tapering model, and separated tapering model, using 2D and 3D finite element analysis (FEA).

On the Application Potential of Chemically Tailored Metal Oxide and Higher Chalcogenide Nanoparticles for Nanoscale Resistive Switching Devices

Resistive switching (RS) for nonvolatile data storage is a highly relevant field of research. Up to now, RS devices are fabricated via semiconductor processing technologies. This poses the question of whether integration of chemically tailored nanoparticles, either consisting of valence change or phase change materials, can be integrated in nanoelectrode configurations in order to explore their functionality for RS applications. This review discusses the RS properties of such nanoparticles by means of selected examples of both nanoparticle assemblies as well as on the individual particle level. Although this field of research is rather unexplored, it becomes evident that chemically tailored nanoparticles bear great potential for RS applications.

One hundred fifty GHz folded dipole antenna‐on‐chip based on artificial magnetic conductor structure

AbstractA folded dipole antenna using an artificial magnetic conductor (AMC) structure is proposed to improve the frequency bandwidth and reduce the size of the antenna on a chip. To change the distribution of the electromagnetic (EM) field, the proposed AMC structure shaped with square‐in‐square rings (SSRs) is arranged along the radiating metal of the folded dipole antenna and implemented on the lowermost metal layer of the backend oxide layers (BEOLs) between the radiating metal of the top layer of the BEOL and the ground plane of the bottom of the substrate. The SSR of the proposed antenna‐on‐chip (AoC) widens the frequency bandwidth by varying the electrical length to the ground and reduces the physical size of the radiating metal by increasing the effective permittivity. The 3D EM‐wave simulation shows that the proposed AMC structure changes the distribution of EM‐wave in the BEOL and Si substrate such that more EM fields are condensed around the radiating metal and the electrical length to the ground is nonuniform and longer. The AoC with the proposed AMC structure was fabricated using a 65‐nm standard complementary metal‐oxide semiconductor process with one‐poly and nine‐metal. Compared with the conventional 150‐GHz antenna that was implemented on the same die, the proposed differential antenna was measured to be a −10 dB bandwidth of 46 GHz, with a 1.12‐times improvement, and a size reduction of 20.4%. The measured gain of the proposed antenna was −5.99 dBi including the passive balun with an insertion loss of −1.36 dB in simulation.

300 mm CMOS-compatible superconducting HfN and ZrN thin films for quantum applications

The rising interest in increased manufacturing maturity of quantum processing units is pushing the development of alternative superconducting materials for semiconductor fab process technology. However, these are often facing CMOS process incompatibility. In contrast to common CMOS materials, such as Al, TiN, and TaN, reports on the superconductivity of other suitable transition-metal nitrides are scarce, despite potential superiority. Here, we demonstrate fully CMOS-compatible fabrication of HfN and ZrN thin films on state-of-the-art 300 mm semiconductor process equipment, utilizing reactive DC magnetron sputtering on silicon wafers. Measurement of mechanical stress and surface roughness of the thin films demonstrates process compatibility. We investigated the materials phase and stoichiometry by structural analysis. The HfN and ZrN samples exhibit superconducting phase transitions with critical temperatures up to 5.84 and 7.32 K, critical fields of 1.73 and 6.40 T, and coherence lengths of 14 and 7 nm, respectively. A decrease in the critical temperature with decreasing film thickness indicates mesoscopic behavior due to geometric and grain-size limitations. The results promise a scalable application of HfN and ZrN in quantum computing and related fields.

Doping of molecular semiconductors through proton-coupled electron transfer.

The chemical doping of molecular semiconductors is based on electron-transfer reactions between the semiconductor and dopant molecules; here, the redox potential of the dopant is key to control the Fermi level of the semiconductor1,2. The tunability and reproducibility of chemical doping are limited by the availability of dopant materials and the effects of impurities such as water. Here we focused on proton-coupled electron-transfer (PCET) reactions, which are widely used in biochemical processes3,4; their redox potentials depend on an easily handled parameter, that is, proton activity. We immersed p-type organic semiconductor thin films in aqueous solutions with PCET-based redox pairs and hydrophobic molecular ions. Synergistic reactions of PCET and ion intercalation resulted in efficient chemical doping of crystalline organic semiconductor thin films under ambient conditions. In accordance with the Nernst equation, the Fermi levels of the semiconductors were controlled reproducibly with a high degree of precision-a thermal energy of about 25 millielectronvolts at room temperature and over a few hundred millielectronvolts around the band edge. A reference-electrode-free, resistive pH sensor based on this method is also proposed. A connection between semiconductor doping and proton activity, a widely used parameter in chemical and biochemical processes, may help create a platform for ambient semiconductor processes and biomolecular electronics.

Micro-Macro Simulation for Laser Processing of Semiconductor

Micro-Macro Simulation for Laser Processing of Semiconductor

A novel strategy of correntropy-based iterative neural networks for data reconciliation and gross error estimation in semiconductor industry

Data from sensors in the semiconductor industry are often contaminated by random or gross errors. To improve the precision and reliability of process data, data reconciliation and gross error detection (DRGED) carries out corrections to these measurements to alleviate the impact of the errors. Conventionally, data reconciliation methods rely heavily on specific process constraints, which are not readily available in some complex semiconductor processes. Thus, simultaneously capturing process correlations among the measurements and conducting DRGED are important for such an application. In this work, a novel correntropy estimator based iterative neural network (C-INN) for DRGED is developed. The robust correntropy estimator is incorporated to reduce the effect of gross errors. Even without given constraints, this strategy can effectively solve the DRGED problem using the process correlation extracted by C-INN. The performance of C-INN is demonstrated via a numerical example and semiconductor process data.

3D process simulation-assisted device failure analysis with virtual defect injection in IC layout

The development and use of nanotechnology has enabled the creation of submicron electronic devices with unprecedented levels of functionality, speed, and efficiency. While most of the semiconductor industry and its consumers are becoming increasingly dependent on nanoelectronics, these devices are becoming more susceptible to defects and transient faults. Non-Visual Defects (NVD) is a category of semiconductor material and process induced defect that cause electrical failures but are not detected with visual wafer inspection tools (Findlay et al., 2016 [1] and Kim et al., 2009 [10]) or with fault localization tools. Devices with NVD may fail at any stage of their life cycle and may benefit from complex Failure Analysis (FA) investigations including software support to analyze design and diagnostic data. For a higher FA success rate, these investigations can be further supplemented with Technology Computer-Aided Design (TCAD) Process Simulation software to simulate a failure prior to actual physical analysis on limited device samples. In this work, we will showcase an innovative technique for simulating NVD using a 3D process model to pinpoint the exact process step where the defect was introduced. By injecting a new virtual defect layer (which can be autonomously introduced by an FA engineer) in the original device data, we can emulate the failing device. We also present a real-life case study where defect simulation correlates well with the actual Transmission Electron Microscope (TEM) cross-section results.

Enhancing photodetection efficiency of CMOS SiPMs using virtual guard rings in a standard 0.35 µm process

AbstractIn this letter, a design of virtual guarded SiPMs fabricated in a standard 0.35μm standard complementary metal oxide semiconductor (CMOS) process is introduced. The performance of these virtual guarded cells (VGC) is compared to that of conventional cells with real guard rings, referred to as physical guarded cells (PGC). Specifically, the photon detection efficiency (PDE) of both types of SiPMs is evaluated. For this, PDE calculations are conducted at different overvoltages (OVs) and the PDE is compared depending on the wavelength before conducting measurements. The results demonstrate that the VGC SiPM outperforms the PGC SiPM, exhibiting a true PDE of (22.5 ± 0.5)%, which is significantly higher than the PDE of (10.9 ± 0.3)% obtained for the PGC SiPM. The superior PDE of the VGC SiPM is attributed to a larger active or photosensitive area due to the virtual guard rings and a thinner n‐layer in the photosensitive region.

Proposal of Atmospheric Heating Method for Recycling Silicon Sludge from Semiconductor Process

Proposal of Atmospheric Heating Method for Recycling Silicon Sludge from Semiconductor Process

Integration of Artificial Intelligence for Real-Time Fault Detection in Semiconductor Packaging

Semiconductor manufacturing involves a complex sequence of unit processes, where even a minor error can disrupt the entire production chain. Present-day manufacturing setups rely on continuous data monitoring of equipment health, wafer measurements, and inspections to identify any abnormalities that could impact the quality and performance of the final chip. The primary aim is fault detection and classification (FDC), for which a range of techniques including statistical analysis and machine learning algorithms are commonly employed. In this study, we introduce an innovative approach utilizing an artificial immune system (AIS), inspired by biological mechanisms, for FDC in semiconductor equipment. The main culprits behind process failures are shifts caused by the aging of parts and modules over time. Our methodology integrates state variable identification (SVID) data, reflecting current equipment conditions, and optical emission spectroscopy (OES) data, capturing plasma process information under faulty scenarios induced by deliberate gas flow rate adjustments in semiconductor fabrication. Our results demonstrate a modeling prediction accuracy of 94.69% when incorporating selected SVID and OES data, and 93.68% accuracy using OES data alone. In conclusion, we suggest the potential application of AIS in semiconductor process decision-making, offering promising avenues for enhancing fault detection in semiconductor equipment.

3D printing of bulk thermoelectric materials: Laser powder bed fusion of N-type silicon germanium

Among Additive Manufacturing (AM) methods, Laser Powder Bed Fusion (L-PBF), also called Selective Laser Melting (SLM), is prevalent to printing complex metal parts in small and medium series. Recent studies in L-PBF processing develops the manufacturing of new materials, including thermoelectric (TE) materials. This study presents manufacturing of an N type Si80Ge20 powder by L-PBF. Silicon germanium alloy is a TE material intended for high temperature applications. It is the first time that this semiconductor material is studied by AM technology. Dense samples of various shapes and sizes were produced, and a first process window was identified. Structural analyses have been performed, highlighting good densification. Unfortunately, mechanical cracking occurs in all samples. TE properties were investigated on as built samples, displaying low values (ZT = 0.11 at 600 °C), due to poor electrical conductivity. Overall, these results show that L-PBF of silicon germanium is possible, which could open up its scope of applications.© 2023 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Materials science in semiconductor processing.

Design and Performance Enhancement of a Piezoelectric Micromachined Ultrasonic Transducer Based on NBBT Lead-Free Piezoelectric Single-Crystal Thin Film

Piezoelectric micromachined ultrasonic transducers (PMUTs) have attracted widespread attention due to their high performance, miniaturization, and easy integration with semiconductor processes. In this paper, a PMUT device based on high-performance and lead-free Na0.5Bi0.5TiO3-BaTiO3 (NBBT) piezoelectric single-crystal thin films was designed for the application of medical high-frequency ultrasonics. Three-dimensional modeling and analysis of PMUT elements on the proposed structure were performed via the finite element method. The relationship between structure configuration in terms of the top electrode and the cavity shape of the bottom was studied. The PMUT properties and its device performance, including resonant frequency, effective electromechanical coupling factor (keff2), and the static sensitivity of different device structures, were analyzed. In addition, by rotating the Euler Angle γ of the NBBT piezoelectric single-crystal film, the static sensitivity and keff2 of the model are improved to 1.34 when γ is rotated to 45 ± 5°. It was shown that the PMUT using rotated NBBT demonstrated an enhanced relative pulse-echo sensitivity of −46 dB and a bandwidth of 35% when the reflective surface was 200 μm. We conclude that the PMUT in accordance with an NBBT piezoelectric single-crystal film designed by simulation offers a high frequency, larger keff2, and high sensitivity, which provides application prospects in high-resolution and high-frequency medical ultrasonic imaging.

Polymer-insertion Effect on Urea Conversion Kinetics via Enzymes Immobilized on Magnetic Microparticles

Urease was covalently immobilized on the magnetic particles without and with polymer between the urease and the particle. The polymer insertion enhanced the conversion from urea to bicarbonate. The ureases were immobilized on the magnetic microparticles through covalent bonds. 150 μL of stock solution of 3 μm diameter particles was washed three times with 20 mM MES rubbing solution at pH 6.0. The results of this study seem to be useful in designing a reactor for recycling wastewater generated in the semiconductor process.

Side-jump scattering enhanced spin Hall effect in SrTiO3-implanted Pt

A spin Hall effect (SHE) enables the electrical generation and detection of spin currents for promising applications in spintronics, but heavy metals with low spin Hall angle θSH limit the development of SHE devices. In this work, we have introduced dielectric oxide material SrTiO3 into Pt by magnetron sputtering and measured the θSH on the NiCo/Pt1–x(STO)x heterostructure through spin-torque ferromagnetic resonance. Our results demonstrate that the maximum spin Hall angle in Pt0.98(STO)0.02 is 0.121 ± 0.003, which is approximately twice that of pure Pt (0.064 ± 0.003). Moreover, theoretical analysis has revealed that the spin Hall angle arises from a complementary interplay between intrinsic and extrinsic mechanisms, namely, the strong spin–orbit coupling in Pt for the intrinsic mechanism and side-jump scattering caused by scalar potential and lattice expansion at dielectric impurities for the extrinsic mechanism. This interplay significantly contributes to enhancing the spin Hall angle. This work demonstrates an effective strategy for fabricating high-performance spin Hall materials with low resistivity, large spin Hall angle, and excellent compatibility with semiconductor processes in low-power spin-torque devices.

Evaluation of etching performance of single etching gases for high-κ films

The continuous advancement of CMOS technology has put forward higher requirements for dielectric etching processes. However, conventional mixed etching gases fail to elucidate the contribution of each gas. The role of single etching gas in the etching process remains elusive. In this work, we investigated the etching characteristics of high-κ thin films using a variety of single fluorine-based or chlorine-based gases. We further analyzed the underlying reasons for the observed differences in etching behaviors with different gases. Our findings demonstrate that BCl3 is the optimal single etching gas for HfO2 and Al2O3 films with a fast and stable etching rate, while the films etched by Cl2, BCl3, CF4, CHF3, and C4F8 exhibited varying degrees of etching residuals. The outstanding etching performance of BCl3 is attributed to the interaction between physical bombardment and chemical reactions. Furthermore, we propose a set of evaluation methods for etching residues and mechanisms. These results provide valuable insights into the etching process and facilitate the selection of appropriate etching gases for high-κ films in advanced semiconductor process nodes.

Design and Fabrication of a Thin and Micro-Optical Sensor for Rapid Prototyping.

Optical sensing offers several advantages owing to its non-invasiveness and high sensitivity. The miniaturization of optical sensors will mitigate spatial and weight constraints, expanding their applications and extending the principal advantages of optical sensing to different fields, such as healthcare, Internet of Things, artificial intelligence, and other aspects of society. In this study, we present the development of a miniature optical sensor for monitoring thrombi in extracorporeal membrane oxygenation (ECMO). The sensor, based on a complementary metal-oxide semiconductor integrated circuit (CMOS-IC), also serves as a photodiode, amplifier, and light-emitting diode (LED)-mounting substrate. It is sized 3.8 × 4.8 × 0.75 mm3 and provides reflectance spectroscopy at three wavelengths. Based on semiconductor and microelectromechanical system (MEMS) processes, the design of the sensor achieves ultra-compact millimeter size, customizability, prototyping, and scalability for mass production, facilitating the development of miniature optical sensors for a variety of applications.

Method for improving dry etching end point detection based on change in time accumulation correlation of plasma emitting wavelengths

This study proposes an optical emission spectroscopy (OES) analysis methodology to improve the ability to detect etching endpoints during high-level semiconductor plasma etching processes. Representative etching endpoint detection methods using single wavelength intensity or multiple wavelength intensity ratio changes include a low signal-to-noise ratio, high plasma instability, a small etching open area, and weak by-product emission signal problems due to deep etching under high-level process conditions such as high aspect ratio contact etching (HARC). As a result, it is difficult to detect the etching endpoint due to the very small or noisy change in the intensity over time due to the process progress of the wavelength selected by OES to detect the etching endpoint. In this study, a method of deriving an accumulative time correlation value according to process progress between selected wavelengths was developed by selecting all wavelengths observed in a specific wavelength region such as ultraviolet region in a spectrum emitted from plasma during a plasma etching process. After classifying the entire correlation signal groups derived as a pair of two intensity peak wavelengths into a dynamic time wrapping algorithm, the intensity change rate of the signal according to the process time was observed by selecting the signal with the most sensitive time change rate during the process. During the vertical nand flash memory manufacturing process, a test wafer for the purpose of detecting the etching endpoint was manufactured and evaluated under the conditions of the cell metal contact etching process, which is a high-level HARC etching process. As a result, it was confirmed that the signal selected by deriving the time accumulative correlation method had a high intensity change rate and a signal-to-noise ratio over time compared to a single wavelength or a plurality of wavelength ratio signals. The method proposed in this study is expected to contribute to process optimization by contributing to improving the ability to detect etching endpoints in high-level plasma etching processes in the future.

In-Memory Transposable Multibit Multiplication Based on Diagonal Symmetry Weight Block

A possible approach to overcome the von Neumann bottleneck and meet the increasing demand for better computing performance is to computing in-memory (CIM). The results of the in-memory calculations are primarily reflected in the vertical bitline (BL) analog voltage. However, the nonlinearity of the BL discharge deteriorates with the increase in discharge voltage. In this study, we propose a diagonal symmetry weight block (DSWB) based on an eight-transistor (8T) static random access memory (SRAM) that can achieve multibit transposable operations. In addition, to guarantee linearity and complete multibit multiplication operations, we propose a cascode current mirror (CCM)-based multiplier. To achieve low-overhead and more efficient quantification, our proposed CIM macro uses a counter-type quantization circuit to read out the analog calculation results. We simulated the performance of the proposed 8T SRAM in a 28-nm complementary metal–oxide–semiconductor process. The integral nonlinearity (INL) of the proposed CCM-based CIM decreased by approximately 54.4% compared with the traditional CIM. Furthermore, the proposed in-memory multibit multiplication throughput density was 6.74 GOPS/kb; this throughput density improvement is approximately 3.3–10.5 times higher than the existing CIM works.