Metal Oxide Semiconductor Research Articles

Real-time, specific, and label-free transistor-based sensing of organophosphates in liquid

Organophosphates (OP), commonly used in agriculture and as chemical warfare agents, pose significant environmental risks, necessitating real-time, low-cost OP detection methods. In particular, liquid-phase OP sensing with minimal sample volumes is crucial. While several methods allow rapid detection of low concentrations of OP vapors, they are effective only in the short term, while vapors are still being produced. Many OP compounds are semi-volatile, leading to the contamination of water, soil, and surfaces, posing a risk of secondary, long-term exposure. Detecting this contamination requires methods that can be directly applied to droplets of the affected medium. Currently, no method provides the desired combination of ultra-sensitivity, quantitative detection, rapid response, and low-cost for detecting OPs in liquid samples. This study aims to demonstrate quantitative, low-cost, real-time, specific, and label-free OP sensing in ultra-small samples using a transistor-based approach. The current work employs the 2-(4-Aminophenyl)-1,1,1,3,3,3-hexafluoro-2-propanol (aminophenyl-HFIP) functionalized meta-nano-channel field-effect chemical sensor (MNChem sensor) to monitor the organophosphate, diethyl cyanophosphonate (DCNP), in liquid samples. The silicon component of the MNChem is fabricated using a complementary metal-oxide semiconductor (CMOS) process, and the amine-based chemical functionalization of the sensing area is performed post-fabrication. The MNChem sensor provides electrostatic control over the source-drain current (IDS), allowing an optimized channel configuration that efficiently transduces localized OP recognition events into significant IDS variations. Sensing is performed using 0.5 μL buffer solution to simulate a miniature field-deployable sensor for on-site liquid analysis. We report the sensing of DCNP with a limit-of-detection of 100 fg/mL, a dynamic range of 9 orders of magnitude, and excellent linearity (≥0.97) and sensitivity. Control measurements confirm the specificity and reliability of the sensor's response, validating its applicability. This study introduces a novel method for OP detection in contaminated droplets using a low-cost disposable transistor technology.

Taguchi Method Statistical Analysis on Characterization and Optimization of 18-nm Double Gate MOSFETs

A bi-layer graphene with a multigate structure was intensified and analysed on an 18-nm Metal Oxide Semiconductor Field-Effect Transistor (MOSFET) device to obtain an optimal performance parameter. The device has a gate structure made of Titanium Dioxide (TiO2) that serves as a high-k material and a metal gate made of Tungsten Silicide (WSix). The Silvaco TCAD Software which are ATHENA and ATLAS modules were used to enhance the fabrication process of virtual devices and to verify the electrical properties of a specific device. According to the International Technology Roadmap Semiconductor (ITRS) specifications of 0.179 V ± 12.7% for threshold voltage (VTH) and 20 nA/m for leakage current (ILEAK), the Taguchi L9 orthogonal array strategy was used to improve the device process parameters for optimum VTH and ILEAK. For the NMOS device, the process parameter of VTH Adjust Implant Dose was used as the dominant factor while Source/Drain (S/D) Implant Energy was used as the adjustment factor whereby for PMOS device, S/D Implant Energy was the dominant factor while S/D Implant Tilt was the adjustment factor in order to achieve a robust design through the Taguchi method implementation. The percentage affecting the process parameter is then applied to the results of the signal to noise ratio (SNR) of Nominal-the-best (NTB) for VTH and Smaller-the-better (STB) for ILEAK.

Humidity-independent NO2 gas sensors based on ZnO-NiOFx nanocomposites and the synergistic humidity-immune effect of fluorine doped NiO

Clean, alternative energy sources, especially fuel cells, are gradually attracting global attentions while the produced toxic nitrogen dioxide (NO2) is a greatly hazardous chemical impacting their energy efficiencies. Metal oxide semiconductors (MOS) hold significant promise as NO2 sensors. However, intensive humidity interaction intensifies signal drifts and reliable response inhibitions under variable humidity conditions. In this study, we present a novel approach to address this issue by engineering in-situ F-doped NiO nanocomposites (NiOFx) decorated on ZnO snowflakes achieved through decomposition modulation of ZnOHF precursors. The optimized NO2 sensor demonstrates unparalleled humidity-independence across a wide operating temperature range with prime sensitivity, low detection limit and rapid response/recovery. Matrix algorithm is also implemented in highly precise NO2 identification under complicated atmospheric and humid conditions. Mechanism studies based on temperature programmed desorption (TPD), quasi in-situ X-ray photoelectron spectroscopy (Quasi in-situ XPS) reveal that F− dopants facilitate interfacial electron transferring and inhibit oxygen activity. In-situ diffuse reflectance infrared Fourier transform spectroscopy (In-situ DRIFTS) demonstrates that hygroscopic NiO and electronegative F− synergistically obstruct hydroxyl adsorptions on sensing materials. The innovative approach offers a promising solution for enhancing moisture resistance of MOS sensors for real-time NO2 concentration monitoring in fuel cells and provides valuable insights into anti-humidity mechanisms.

Significantly energy‐efficient ethanol sensor based on bougainvillea‐like Au/ZnO hierarchical nanostructured materials

AbstractThe energy consumption of MOS (metal oxide semiconductor) sensors has always been a challenge in improving their performance. In this study, bougainvillea‐like Au/ZnO nanostructures were successfully synthesized using the hydrothermal method and the sol fixation technique. The composition, crystallinity, crystal structure, and morphology of the materials were characterized using X‐ray diffraction, energy‐dispersive spectroscopy, and field emission scanning electron microscopy. The experimental results confirm the successful synthesis of a substantial quantity of bougainvillea‐like Au/ZnO nanostructures through nanoparticle self‐assembly. The sensitive performance of the bougainvillea‐like Au/ZnO sensor was evaluated using a CGS‐8 intelligent gas‐sensitive analysis system. Results demonstrate that modification of ZnO with Au in a bougainvillea‐like nanostructure significantly enhances sensitivity to ethanol vapor compared to those of unmodified material sensors. Specifically, the optimal work temperature was greatly reduced by 64%, whereas the sensitivity increased approximately 12 times and the response time decreased nearly 5 times. The significantly enhanced ethanol sensitivity can be attributed to the precious metal modification and unique three‐dimensional morphology. It provides the necessary experimental exploration for reducing energy consumption and improving the performance of MOS gas sensors.

Enhanced Threshold Voltage and Improved Subthreshold Swing Using NiOX/ITO Reverse Bias Gated Diamond pMOS

An increase in the device performance of diamond‐based p‐type metal–oxide–semiconductor (pMOS) transistors using a combination of p‐type nickel oxide and n‐type indium tin oxide (NiOX/ITO) reverse bias diode as the gate dielectric is reported. Negative threshold voltage pMOS transistors are desirable for digital circuits and power applications for fail‐safe operation. A Schottky gate‐based conventional diamond pMOS transistor suffers from many limitations, including a positive threshold voltage (VT). Herein, it is experimentally demonstrated that NiOX/ITO gate dielectric with Al gate contact circumvents many critical limitations, providing a negative threshold voltage of −1.2 V, improved subthreshold slope of 145 mV dec−1, current ON/OFF ratio >107, and peak gate leakage current reduction >103. An Al/NiOX‐based control gate structure shifts the VTH negative with improvements in crucial device performances. Adding a reverse bias junction through the Al/ITO/NiOX heterointerface with the Al metal gate further improves performance. The measured device characteristics are explained in a common framework of energy band diagram for all the devices.

Single feature to achieve gas recognition: humidity interference suppression strategy based on temperature modulation and principal component linear discriminant analysis

Metal oxide semiconductor (MOS) sensors have been broadly employed for gas detection. However, the distinctive chemical detection principle of MOS sensors renders them susceptible to interference by humidity. This paper proposes a novel method for suppressing humidity interference. This method possesses advantages, including rapid recognition, low power consumption, and the capability to achieve recognition using a single feature. Temperature modulation technology was used to record the sensor's resistance variation, and the response features of the obtained dynamic response signal are affected by both humidity and the measured gas. The suppression of humidity interference is achieved through the investigation of the response features of humidity and the measured gas. The response features of humidity and gas are amplified by column normalization. Principal Component Linear Discriminant Analysis (PC-LDA) is utilized to acquire humidity and gas information within data. Using ethanol as the primary experimental subject, suppression of humidity interference is achieved through a single feature (PC-LD2). Quantitative recognition of relative humidity (RH) can be achieved using PC-LD1. Multiple types of waveform and sensor were used to demonstrate the generalization of this method.

Introducing oxygen vacancies into WO3 thin film for improving hydrogen sensing performance of Pd/WO3-x/AAO sensors

Introducing oxygen vacancy into semiconducting metal oxides (SMOs) is a strategic approach to promote their gas sensing performances. In this paper, the WO3-x thin films were meticulously deposited onto an anodic aluminum oxide (AAO) substrate, and the oxygen vacancies concentrations of WO3-x thin films were changed by adjusting the ratio of flux of Ar to O2 in magnetron sputtering process. Sequentially, a layer of palladium (Pd) was deposited on the WO3-x/AAO films, creating a nano-mesh structured hydrogen sensor with Pd as the catalytic element. The resulted amorphous WO3-x samples with varying concentration of oxygen vacancies were thoroughly analyzed using XPS and ESR, which confirmed that the oxygen vacancies concentration escalated with an increase in the ratio of flux of Ar to O2. The hydrogen sensitivity of prepared Pd/WO3-x/AAO sensors were examined. Our findings revealed an enhancement in hydrogen sensitivity for the sensors with an optimal concentration of oxygen vacancies. However, an excess of these vacancies was found to deteriorate their hydrogen sensing performance. Notably, the optimized Pd/WO3-x/AAO sensor exhibited a marked response even at a hydrogen concentration as low as 100 ppb, demonstrating its high sensitivity and selectivity towards hydrogen detection.

Gas sensing performance regulating of ZIF-8 encapsulated WO3 nanosheets

Reasonably regulating the adsorption properties on the surface of metal oxide semiconductors (MOS) to enhance sensor selectivity remains a challenge, limiting their application in detecting diseases biomarkers in human exhaled gas. To address this, we proposed a metal-organic frameworks (MOFs) encapsulated strategy to provide a gas-selective permeable nano-filtration layer for MOS gas sensors. By adjusting the coating thickness of ZIF-8, we successfully modulate the sensing properties of WO₃ to different potential biomarkers. The optimized WO₃/ZIF-8 composite shows improved selectivity and response to various disease biomarkers compared to WO₃ alone. The unique porous structure of ZIF-8 and the heterojunction of WO3/ZIF-8 synergistically promote the gas adsorption performance. QCM test results confirm that ZIF-8 modification effectively regulates gas adsorption on the WO₃ surface. This study provides a valuable reference for designing exhaled gas sensor arrays for detecting serious diseases.

Scalable Atomic Arrays for Spin-Based Quantum Computers in Silicon.

Semiconductor spin qubits combine excellent quantum performance with the prospect of manufacturing quantum devices using industry-standard metal-oxide-semiconductor (MOS) processes. This applies also to ion-implanted donor spins, which further afford exceptional coherence times and large Hilbert space dimension in their nuclear spin. Here multiple strategies are demonstrated and integrated to manufacture scale-up donor-based quantum computers. 31PF2 molecule implants are used to triple the placement certainty compared to 31P ions, while attaining 99.99% confidence in detecting the implant. Similar confidence is retained by implanting heavier atoms such as 123Sb and 209Bi, which represent high-dimensional qudits for quantum information processing, while Sb2 molecules enable deterministic formation of closely-spaced qudits. The deterministic formation of regular arrays of donor atoms with 300nm spacing is demonstrated, using step-and-repeat implantation through a nano aperture. These methods cover the full gamut of technological requirements for the construction of donor-based quantum computers in silicon.

Wafer-Scale Atomic Layer-Deposited TeOx/Te Heterostructure P-Type Thin-Film Transistors.

There is an increasing demand for p-type semiconductors with scalable growth, excellent device performance, and back-end-of-line (BEOL) compatibility. Recently, tellurium (Te) has emerged as a promising candidate due to its appealing electrical properties and potential low-temperature production. So far, nearly all of the scalable production and integration of Te with complementary metal oxide semiconductor (CMOS) technology have been based on physical vapor deposition. Here we demonstrate wafer-scale atomic layer-deposited (ALD) TeOx/Te heterostructure thin-film transistors with high uniformity and integration compatibility. The wafer-scale uniformity of the film is evidenced by spatial Raman mappings and statistical electrical analysis. Furthermore, surface accumulation-induced good ohmic contact has been observed and explained by the unique band alignment of the charge neutrality level inside the Te valence band. These results demonstrate ALD TeOx/Te as a promising p-type semiconductor for monolithic three-dimensional integration in BEOL CMOS applications incorporated with well-established n-type ALD oxide semiconductors.

An analytical I-V model of SiC double-gate junctionless MOSFETs

Silicon carbide(SiC) double gate junctionless metal oxide semiconductor field-effect transistors(DG JL MOSFETs) have attracted significant attention due to their ideal high temperature characteristics and radiation resistance. Therefore, it is meaningful to exploit an I-V model for SiC DG JL MOSFETs. In this article, we make a linear approximation to describe the relationship between the surface mobile charge density and the surface electron concentration of the device. Based on this approximation and using the one-dimensional Poisson’s equation, we solve for the potential distribution of a SiC DG JL MOSFET in the subthreshold region. From this solution, we derived a functional relationship between the surface mobile charge density in the channel and the channel quasi-Fermi potential. Then we successfully developed a unified I-V model for the SiC DG JL MOSFETs. Based on the drain to source current calculation formula, the calculation expressions for the device’s transconductance and output conductance are derived. By comparing our model with the results from the two-dimensional numerical simulation software Silvaco Atlas, our model’s calculations closely match the two-dimensional numerical simulation results from the subthreshold region to the accumulation region. This model has reference significance for SiC DG JL MOSFETs in the high temperature electronic circuit application field.

Ion-migration-induced synaptic plasticity in high ion-storable fluorine graphdiyne for information processing

Neuromorphic devices encounter constraints associated with complementary metal–oxide–semiconductor technology, such as intricate electronics and high power consumption. Recently, solid polymer electrolytes (SPE) have gained attraction in electronic devices for constructing artificial synapses, primarily due to their low-voltage operation enabled by ion-assisted signal transmission. This study presents a two-terminal artificial synapse fabricated using fluorine graphdiyne (F-GDY) synthesized through chemical vapor deposition and ion-doped SPE. The device architecture consists of Au/SPE/F-GDY/Si, which operates by ion migration induced by external potential pulses. Electrical measurements are conducted to depict the synaptic plasticity of the devices. Among devices employing different ion-doped SPEs (Li-SPE, Na-SPE, K-SPE, and Ca-SPE), the one utilizing Li-SPE demonstrates the highest synaptic weight. This is attributed to the superior Li+ ion storage capacity of F-GDY; hence, Li-SPE/F-GDY was chosen for in-depth examinations of synaptic activity presenting long-term potentiation, short-term depression, and pair-pulse facilitation. The device has good durability and stability and can respond to low action potential with power consumption at the pJ level. Furthermore, Modified National Institute of Standards and Technology simulations reveal its learning and pattern recognition capability with 91.3 % accuracy after 10 training epochs. Finally, flexible substrate-based SPE/F-GDY devices integrated with gate electrodes were fabricated to record physiological signals, showing promise for in-sensing applications. This work shows the potential of F-GDY/Li-SPE devices for low-power neuromorphic computing, though real-time parallel processing and multimodal integration (e.g., visual, auditory) remain unexplored. However, the biocompatibility and efficient ion-assisted transmission of F-GDY suggest promising future applications in these areas.

Dielectric Material and Thermal Optimization in Sidewall Spacer Design for Junctionless Nanosheet FETs at Sub- 5 nm Technology Node: An Insight into Device and Circuit Performance

This study focuses on the design and analysis of Junctionless (JL) NSFETs, with an emphasis on the influence of spacer materials and temperature variations. A different number of materials such as Air, SiO2, Si3N4, HfO2, and TiO2 are examined for sidewall spacer compatibility in the JL-NSFET. The same materials are used for dual material spacers with combinations of: Air+HfO2, Air+TiO2, SiO2+HfO2, and SiO2+TiO2. The investigations revealed that the usage of TiO2 material gives better digital and analog performance with reduced leakage currents and subthreshold swing (SS), higher on/off ratio, voltage gain of ∼79.7 dB. Exploring the dual-k spacers produced better analog performance, gate control and reduced leakages for SiO2+TiO2 owing to the usage of higher dielectric material towards the gate. Further, the reduction of temperature from 400 K to 250 K for all the single-k and dual-k spacer materials revealed that the designed JL-NSFET is a suitable candidate at lower temperatures to improve the digital and analog performance whereas not recommended for RF performance improvement. Moreover, the SiO2+HfO2 spacer-based CMOS inverter is noticed to have better gain (∼15 V/V), noise margin, and lower delays (∼5.1 ps) when compared to TiO2 spacer-based complementary metal oxide semiconductor inverter making it suitable for digital IC applications.

Development of smart molecularly imprinted tetrahedral amorphous carbon thin films for in vitro dopamine sensing

This study investigates how varying the thickness of tetrahedral amorphous carbon (ta-C) thin films and incorporating a titanium adhesion layer influences the structural and electrochemical properties of molecularly imprinted ta-C thin film-based sensing platforms, aiming to develop a molecularly imprinted ta-C electrochemical sensor for dopamine (DA) detection with physiologically relevant sensitivity. This electrochemical sensing platform was designed by integrating ta-C with molecularly imprinted polymers (MIPs). The process involved depositing a ta-C thin film onto boron-doped p-type silicon wafers through a filtered cathodic vacuum arc (FCVA) system. Subsequently, the ta-C sensing platforms were electrochemically coated with the MIP layer (DA-imprinted polypyrrole). We evaluated three configurations: (i) a 15 nm ta-C layer, (ii) a 7 nm ta-C layer with a 20 nm titanium adhesion layer, and (iii) a 15 nm ta-C layer with a 20 nm titanium adhesion layer. Comprehensive structural and electrochemical characterization was performed to understand how these modifications affect sensor performance. The optimized MIP/ta-C sensor demonstrated a sensitivity of 0.16 μA μM−1 cm−2 and a limit of detection (LOD) of 48.6 nM, suitable for detecting DA at physiological levels. Leveraging the synergistic effects of ta-C coatings and molecular imprinting, as well as its compatibility with common complementary metal–oxide–semiconductor (CMOS) processes underlines its potential for integration into microanalytical systems, paving the way for miniaturized and high-throughput sensing platforms.

Recent trends in neuromorphic systems for non-von Neumann in materia computing and cognitive functionalities

In the era of artificial intelligence and smart automated systems, the quest for efficient data processing has driven exploration into neuromorphic systems, aiming to replicate brain functionality and complex cognitive actions. This review assesses, based on recent literature, the challenges and progress in developing basic neuromorphic systems, focusing on “material-neuron” concepts, that integrate structural similarities, analog memory, retention, and Hebbian learning of the brain, contrasting with conventional von Neumann architecture and spiking circuits. We categorize these devices into filamentary and non-filamentary types, highlighting their ability to mimic synaptic plasticity through external stimuli manipulation. Additionally, we emphasize the importance of heterogeneous neural content to support conductance linearity, plasticity, and volatility, enabling effective processing and storage of various types of information. Our comprehensive approach categorizes fundamentally different devices under a generalized pattern dictated by the driving parameters, namely, the pulse number, amplitude, duration, interval, as well as the current compliance employed to contain the conducting pathways. We also discuss the importance of hybridization protocols in fabricating neuromorphic systems making use of existing complementary metal oxide semiconductor technologies being practiced in the silicon foundries, which perhaps ensures a smooth translation and user interfacing of these new generation devices. The review concludes by outlining insights into developing cognitive systems, current challenges, and future directions in realizing deployable neuromorphic systems in the field of artificial intelligence.

Low-pressure oxidation for improving interface properties and voltage instability of SiO2/4H-SiC MOS capacitor

The impact of high-temperature sub-atmospheric oxidation pressure on the interface properties of n-type 4H-SiC metal–oxide–semiconductor capacitors has been systematically investigated in this report. The bias temperature instability measurement was used to calculate the mobile ions and near-interface trap density that led to device instability at high temperatures. The density of near interface traps decreased from 88.3 × 1011 cm−2 to 10.2 × 1011 cm−2 when the growth pressure of SiO2 was reduced from 1 atm to 0.1 atm, while the mobile ions density decreased from 83.5 × 1011 to 4.18 × 1011 cm−2. The results show that SiO2 growing under lower oxidation pressure has better interfacial quality. The underlying mechanism was explored by secondary ion mass spectrometry (SIMS) and x-ray photoelectron spectroscopy (XPS). It is speculated that the SiO2/SiC interface was reconstructed under low-pressure oxidation: the excess Si-related defects near the interface, such as SiOxCy, were released while O atoms were accumulated to promote a complete oxidation reaction, thereby effectively reducing the number of defects in the SiO2 film and improving device performance.

Design of a Portable Spectrophotometer Based on Raspberry Pi for Tea Type Classification Using Machine Learning

Abstract The use of spectrophotometers in food and beverage quality analysis has become common. However, portability and high cost have long been a problem for food industry players and small-scale laboratories. In this study, a more compact and low-cost spectrophotometer has been developed using raspberry pi. To validate its performance, the prototype was used to classify green tea, black tea, and oolong tea types. The research started with designing and assembling the hardware using a raspberry pi camera with Complementary Metal Oxide Semiconductor (CMOS) sensor, Digital Versatile Disk (DVD) as diffraction grating, white LED as light source and 3D printer as casing. The prototype was then used to acquire data from green tea, black tea and oolong tea solutions. In the tea type identification process, Principal Component Analysis (PCA) was applied to the data obtained. The experiment involved 30 solution samples of each of the three types of tea. The light source was directed past the sample towards the slit and DVD, then the spectrum image of the light source was displayed through a user interface built using python programming. This research resulted in a spectrophotometer with dimensions of 260 mm x 120 mm x 63 mm that is capable of capturing light spectra in the range of 400 - 700 nm. Based on the experimental results, the classification accuracy of the three types of tea using CNN and Decision Tree reached 100%.

Impact of Deposition Temperature on Structural and Electrical Properties of Sputtered AlN/ Si (111) for CMOS compatible MEMS

Aluminium nitride (AlN) thin films are grown by reactive sputtering on Silicon (Si) with (111) orientation at low temperature (< 450 °C) for piezoelectric-based micro-electromechanical systems (MEMS). The grown AlN thin films were polycrystalline wurtzite hexagonal structure with a high texture coefficient for the (002) plane of orientation. The leakage current density by the current-voltage (I-V) measurement was found to be as low as 1.6 ×10-6Acm−2 in the grown films. The trapped charges are crucial in controlling these electrical characteristics, and low interface trap density (6.72 ×1010cm−2 eV) was observed for the sputtered AlN grown at a substrate temperature of 300 °C. This study on the structural and electrical properties of AlN/Si (111) at low substrate temperature is compatible with the complementary metal oxide semiconductor (CMOS) process for constructing piezoelectric-based MEMS devices for various applications.

Fabrication and evaluation of a CMOS-based energy harvesting chip integrating photovoltaic and thermoelectric energy harvesters

This study explores the development of an energy harvesting chip (EHC) using a complementary metal oxide semiconductor (CMOS) process, addressing the need for efficient micro-scale energy harvesters in modern electronics. The EHC integrates a thermoelectric energy harvester (TEH) and a photovoltaic energy harvester (PEH) to maximize energy conversion efficiency. A key challenge in TEH design is enhancing power output, which is addressed by suspending the cold ends of 41 thermocouples within the TEH structure through post-processing. Experimental methods were employed to assess the performance of the TEH, revealing an output voltage of 21.4 mV and a maximum output power of 9.32 nW under a 3 K temperature difference. The TEH demonstrated a voltage factor of 8.9 mV/(mm2·K) and a power factor of 1.3 nW/(mm2·K2). The PEH was designed with novel patterned p-n junctions, integrating lightly doped n-type regions with interdigitated p-type doping to increase junction density, resulting in high conversion efficiency. The experimental results confirm the effectiveness of the EHC design, showcasing its potential in energy harvesting applications.

Constructing a Z-scheme heterojunction of oxygen-deficient WO3-x and g-C3N4 for superior photocatalytic evolution of H2

Semiconductor-based photocatalytic water splitting enables the conversion of abundant solar energy to green and renewable hydrogen energy. Graphitic carbon nitride (g-C3N4) is synthesized using a straightforward method, demonstrating stable physicochemical properties and possessing an optimal bandgap, thus positioning it as a promising photocatalyst in the realm of environmental sustainability. Oxygen vacancies are extensively employed to modulate light absorption and surface properties of metal-oxide semiconductors. In this study, g-C3N4 nanosheets were coupled with oxygen-deficient tungsten trioxide (WO3-x) to form heterojunction photocatalysts (X-WOCN). Comprehensive material characterization results demonstrated that the constructed heterojunction extended the visible light absorption range, improved photogenerated electron-hole separation efficiency, and thus augmented photocatalytic activity. Notably, the optimum hydrogen evolution rate of 6%-WOCN was enhanced by 5.4-fold compared to that of g-C3N4. Furthermore, we propose a Z-scheme heterojunction charge separation mechanism mediated by oxygen defects and support this mechanism through detection of surface-active substances •O2− and •OH. This study offers novel propositions into the function of oxygen defects in facilitating charge separation within Z-scheme heterojunction.