Industrial Applications Research Articles

COCONUT PREDICTIVE ANALYSIS USING MACHINE LEARNING

“Coconut Predictive Analysis” focuses on leveraging advanced machine learning techniques to predict the suitability of coconuts for oil production. The project employs transfer learning with the Inception V3 model, a state-of-the-art convolutional neural network (CNN), to analyze complex patterns in coconut-related data, such as images of coconuts. Traditional methods for determining coconut suitability for oil production rely on manual inspection, which can be time-intensive, subjective, and inconsistent. By utilizing transfer learning, this project capitalizes on pre-trained Inception V3 models, which extract meaningful features from large-scale datasets like ImageNet, and fine-tunes them for the specific task of classifying dry coconuts based on their suitability for oil extraction. The fine-tuning process involves freezing initial layers to retain general features while optimizing later layers to improve prediction accuracy for coconut-specific characteristics such as texture, colour, and surface patterns. To ensure accessibility and usability, a Flask web application is developed. This application enables users to upload images of coconuts and receive real-time predictions on their suitability for oil production. The backend integrates the trained model to process inputs, extract features, and generate predictions, making it a scalable and practical solution for agricultural and industrial applications. This project demonstrates the potential of transfer learning in enhancing agricultural and processing efficiency by reducing training time and computational costs while providing accurate and actionable predictions. By combining cutting-edge deep learning with a user-friendly web interface, it bridges the gap between advanced AI models and practical applications, supporting decision-making for farmers, coconut processing units, and industry stakeholders. Key Words: Inception V3, fine-tuning, CNN, Flask, coconut analysis, oil production suitability

Using Digital Twins for Fault Detection and Root Cause Analysis in Mechanical Systems

The integration of Digital Twin (DT) technology into mechanical systems has shown significant potential for enhancing fault detection, diagnostics, and root cause analysis. By creating real-time virtual replicas of physical systems, DTs facilitate continuous monitoring and provide actionable insights into system behavior. This paper explores the application of DT technology in mechanical systems, focusing on its role in fault prevention, predictive maintenance, and root cause analysis. We investigate key aspects such as real-time data synchronization, predictive maintenance strategies, system optimization, and the use of multi-sensor integration to improve fault detection accuracy. The paper also examines the challenges associated with implementing DTs in complex mechanical systems and discusses future directions for research in this field. By leveraging machine learning and advanced data fusion techniques, Digital Twins enable predictive analytics, improving system reliability, efficiency, and overall performance. This work highlights how DTs can transform traditional maintenance strategies, leading to more proactive, data-driven approaches for fault detection and system recovery. Keywords: Digital Twin, fault detection, root cause analysis, mechanical systems, predictive maintenance, real- time data synchronization, system optimization, fault prevention, machine learning, predictive models, sensor data, system performance, anomaly detection, vibration analysis, remaining useful life (RUL), fault recovery, predictive analytics, system reliability, maintenance strategy, real-time monitoring, virtual model, operational efficiency, mechanical failure, sensor fusion, failure prediction, condition-based maintenance, fault detection algorithms, system behavior simulation, data-driven decision making, root cause identification, industrial applications.

Pleurotus spp: A cosmopolitan fungi of biotechnological importance

The genus Pleurotus presents a multivariate species diversity due to its ability to grow in different substrates and environments. Whether wild or cultivated, they are edible mushrooms, as they present a high nutritional value and are medicinal due to their bioactive compounds with positive health effects. The aim of this review is to highlight the importance of the genus Pleurotus, since it is a cosmopolitan mushroom, and its properties can be used in different industrial applications and be a functional alternative for our future. Due to their saprophytic nature, they produce enzymes that act on the substrate in which they grow, degrading lignocellulosic material such as wood, forest and agricultural residues, hardwoods, wood by-products, cereal straw, bagasse, etc., and thanks to this degradative capacity, their enzymes are used in a wide range of biotechnological and environmental applications. In order to increase their production and consumption not only for their nutritional qualities, but also for their nutraceutical and biotechnological qualities, ease of cultivation, low investment cost, etc., new ways are being sought to increase their performance in cultivation. Recently, research has expanded the search for alternative uses of the Pleurotus genus, which has led to an increase in its cultivation, as well as its application in different fields of biotechnology. The cultivation of Pleurotus mushrooms represents an opportunity to generate a sustainable process and incorporate the process into a circular economy, generating environmental, social and economic benefits. The use of agro-industrial substrates and the subsequent reuse of the spent substrate as compost or organic fertilizer reduces the amount of waste that ends up in landfills and minimizes methane production. This allows for a more sustainable and environmentally friendly production model. Therefore, it is necessary to develop strategies for the promotion, marketing and sustainable production of products derived from these fungi.

Clinical and mechanistic insights into biomedical application of Se-enriched probiotics and biogenic selenium nanoparticles.

Selenium is an essential element with various industrial and medical applications, hence the current considerable attention towards the genesis and utilization of SeNPs. SeNPs and other nanoparticles could be achieved via physical and chemical methods, but these methods would not only require expensive equipment and specific reagents but are also not always environment friendly. Biogenesis of SeNPs could therefore be considered as a less troublesome alternative, which opens an excellent window to the selenium and nanoparticles' world. bSeNPs have proved to exert higher bioavailability, lower toxicity, and broader utility as compared to their non-bio counterparts. Many researchers have reported promising features of bSeNP such as anti-oxidant and anti-inflammatory, in vitro and in vivo. Considering this, bSeNPs have been tried as effective agents for health disorders, especially as constituents of probiotics. This article briefly reviews selenium, selenium nanoparticles, Se-enriched probiotics, and bSeNPs' usage in an array of health disorders. Obviously, there are very many articles on bSeNPs, but we wanted to summarize studies on prominent bSeNPs features published in the twenty-first century. This review is hoped to give an outlook to researchers for their future investigations, ultimately serving better care of health disorders.

Enhanced Mosquito Larvicidal Efficacy and Dehairing Properties of Bacillus thuringiensis Serovar israelensis Strain VCRC-B649 Isolated from Malabar Coast, India.

In recent years, there has been a global threat from emerging vector-borne diseases (VBD), despite the implementation of several vector control programs. Considering the benefits of bacterial pesticides, the present study aimed to isolate potential mosquitocidal bacteria from the various soil types collected from the Kasaragod (12.5°N, 75.0°E) district of Kerala, India. One bacterial strain was isolated from the coastal alluvium soil and showed promising mosquitocidal activity. The mosquitocidal isolate was identified as Bacillus thuringiensis serovar israelensis strain VCRC-B649 through phylogenetic analysis of whole genome sequence. LC50 values against Culex quinquefasciatus, Aedes aegypti, and Anopheles stephensi larvae were determined as 0.0064, 0.0072, and 0.0101mg/L, and LC90 values were 0.0127, 0.0140, and 0.019mg/L. Comparative analysis of larvicidal activity of this strain has revealed more efficacy than the WHO reference strain of B. thuringiensis var. israelensis (H14) The cry and cyt gene profile of this isolate is found to be similar to WHO reference strain of B. thuringiensis var. israelensis (H14). This new isolate has not shown any adverse effects against aquatic non-target organisms. Further evaluation of its morphological, biochemical characteristics and growth kinetics revealed similarities with already reported B. thuringiensis strains. Sporulated culture at 72h showed maximum (20.6 ± 1.5mm) proteolytic activity and animal skin (goat skin) dehairing property and revealed the industrial applications of this new strain. This is the first report on the isolation of mosquitocidal bacterial strain with enzyme-producing property from the Malabar coastal region and it was proven to be a more suitable alternative biocontrol agent for controlling the disease transmitting mosquito vectors with translational value.

Trivalent chromium ion removal from synthetic wastewater using graphene oxide nanocollector by various flotation mechanisms

ABSTRACT The scarcity of freshwater resources for industrial applications poses a significant global concern. Therefore, wastewater treatment is vital for industrial reuse and decreases environmental damage. Chromium, commonly encountered in industrial wastewater, is regarded as a highly toxic metal and a significant environmental pollutant. In this study, the ion removal of trivalent chromium was investigated by graphene oxide (GO) and sodium dodecyl sulfate (SDS) as collectors using various flotation methods including foam fractionation, ion flotation, and precipitation flotation. The effective parameters of the collector type and pH were studied to assess the chromium ion removal, water recovery during the process, and flotation mechanisms. Experimental results indicated that the highest ion removals, achieved with SDS and GO collectors, were 88.86% and 86.07%, respectively, at a pH of 6.3 using the ion flotation method. Notably, GO reduced water recovery by approximately 15% compared to optimal conditions using SDS. The results indicated the remarkably high efficacy of GO as a nanocollector in the ion flotation process for efficiently removing chromium ions with significantly lower collector consumption.

An Adaptive Spatial-Terminal Iterative Learning Strategy in Roll-to-Roll Control Problems

Abstract Roll-to-Roll (R2R) systems, featuring motorized or idle rollers, are crucial for high-volume, continuous production of flexible substrates. A significant challenge in R2R printing processes is maintaining tight alignment tolerances for multi-layer printed electronics. This alignment, known as registration, is complicated by the deformability of flexible substrates and complex roller dynamics, leading to registration errors (RE) caused by variations in substrate tensions and speeds. Despite using real-time feedback controllers like PID or MPC for tension control, these systems struggle with transient and angle-periodic disturbances common in R2R systems. We introduce a Spatial-Terminal Iterative Learning Control (STILC) method with an adaptive basis function to eliminate RE in R2R gravure printing. This function, along with the registration error, updates the STILC compensation profile via a P-type Iterative Learning Control law. Our numerical experiments demonstrate that STILC with the adaptive basis function effectively eliminates RE caused by roller-motor axis mismatches and provides better convergence than STILC with an invariant basis function. This novel approach shows promise for various industrial applications involving spatially periodic disturbances, particularly those with unknown dynamics and without given state trajectories to track rigorously, which is common in engineering practice.

Boosting C-O Bond Cleavage and Reverse Water-Gas Shift Activity via Enriched in-plane Sulfur Vacancies in Single-Layer Molybdenum Disulfide.

The reduction of CO2 to CO provides a promising approach to the production of valuable chemicals through CO2 utilization. However, challenges persist with the rapid deactivation and insufficient activity of catalysts. Herein, we developed a soft-hard dual-template method to synthesize layered MoS2 using inexpensive and scalable templates, enabling facile regulation of sulfur vacancies by controlling the number of layers. The concentration of in-plane vacancies keeps increasing with the reduction of MoS2 layer number, contributing to 100% CO selectivity over single-layer MoS2 and a stable performance over 300-hour reaction at 600 °C. The space-time-yield of CO reached 35.7 gCO gcat-1 h-1, outperforming most current catalysts. Multiple characterizations and theoretical calculations revealed that in-plane sulfur vacancy sites endowed enhanced production of CO via direct dissociation of CO2, showing an intrinsic activity of above 5.8 times higher than that of edge sulfur vacancy sites. The rate-limiting step was shifted from C-O cleavage in edge to sulfur vacancy regeneration in plane with a lower energy barrier. Our findings exemplified the specified design and synthesis of MoS2 for high-temperature CO2 reduction through the effective manipulation of distinct vacancy sites, shedding light on their potential industrial application.

The comprehensive regulatory network in seed oil biosynthesis.

Plant oils play a crucial role in human nutrition, industrial applications and biofuel production. While the enzymes involved in fatty acid (FA) biosynthesis are well-studied, the regulatory networks governing these processes remain largely unexplored. This review explores the intricate regulatory networks modulating seed oil biosynthesis, focusing on key pathways and factors. Seed oil content is determined by the efficiency of de novo FA synthesis as well as influenced by sugar transport, lipid metabolism, FA synthesis inhibitors and fine-tuning mechanisms. At the center of this regulatory network is WRINKLED1 (WRI1), which plays a conserved role in promoting seed oil content across various plant species. WRI1 interacts with multiple proteins, and its expression level is regulated by upstream regulators, including members of the LAFL network. Beyond the LAFL network, we also discuss a potential nuclear factor-Y (NF-Y) regulatory network in soybean with an emphasis on NF-YA and NF-YB and their associated proteins. This NF-Y network represents a promising avenue for future efforts aimed at enhancing oil accumulation and improving stress tolerance in soybean. Additionally, the application of omics-based approaches is of great significance. Advances in omics technologies have greatly facilitated the identification of gene resources, opening new opportunities for genetic improvement. Importantly, several transcription factors involved in oil biosynthesis also participate in stress responses, highlighting a potential link between the two processes. This comprehensive review elucidates the complex mechanisms underlying the regulation of oil biosynthesis, offering insights into potential biotechnological strategies for improving oil production and stress tolerance in oil crops.

Enhancing the Mechanical and Adhesive Properties of Polyurethane Adhesives with Propylene Oxide-Modified Ethylenediamine (PPO-EDA)

This study explores the use of propylene oxide-modified ethylenediamine (PPO-EDA) as a novel crosslinker and chain extender in polyurethane (PU) adhesives. PPO-EDA was synthesized and compared with N,N’-dimethylethylenediamine (DMEDA) to assess its impact on mechanical properties and adhesion performance. Key parameters such as NCO conversion, tensile strength, and lap shear strength were thoroughly evaluated. The results demonstrated that incorporating PPO-EDA significantly improved NCO conversion and crosslink density, leading to notable enhancements in tensile strength and elastic modulus compared to DMEDA. Lap shear tests further revealed superior adhesion performance in PPO-EDA-modified PU adhesives, particularly on amine silane-treated steel substrates, where lap shear strength consistently outperformed other samples. This improved performance was attributed to PPO-EDA’s dual role as a chain extender and crosslinker, which strengthened the adhesive’s structural integrity. This study underscores the effectiveness of PPO-EDA as a modifier for enhancing both mechanical and adhesive properties in PU-based adhesives, offering a promising solution for optimizing high-performance adhesives in automotive and industrial applications.

Thermoelectrics in alkaline earth metal tellurides of ATe2 type - A first-principles study

Abstract We report an extensive study on the structural and thermoelectric performance of the novel semiconducting binary type ATe2 (A=Mg,Be,Ca,Sr,Ba) earth abundant materials using Density Functional Theory (DFT) and semi-classical Boltzmann transport theory. The PBE-GGA exchange correlation potential method was used for electronic structure calculations within the framework of density functional theory. The structural stability of the materials was confirmed by ground state energy, formation energy and mechanical responses. The calculated lattice constants, energy band structures and density of states explain the nature of the materials and are agreed with previous experimental and theoretical works. According to our calculated results, we revealed a high figure of merit materials are CaTe2 and SrTe2 due to high Seebeck and electrical conductivity and low thermal conductivity values. Additionally, Slack's equation was utilized to obtain low lattice thermal conductivity values. Our findings will serve as theoretical guidelines for future experimental and industrial applications both in cooling and heating

Machine learning approach for prediction of hole oversize using acoustic emission signal features in ultrasonic machining of inconel 718

ABSTRACT The material removal in the ultrasonic machining process is due to the fracture of the workpiece material. The fracture is owing to the energy transfer by vibrating abrasive particles. The vibrating particles impact the workpiece surface and machining takes place, leading to the size of the machining hole, which is of interest to understand to guarantee efficient machining with accuracy and precision. In the current investigation, the hole oversize (HOS) during the ultrasonic machining of Inconel 718 super alloy is attempted. An acoustic emission sensor is integrated with the machining setup, and signal information is extracted in the time and time-frequency domain. The features and process parameters are input to a support vector regression model to estimate HOS. The model developed for HOS prediction yields an accuracy of 97.87%. The developed model can be beneficial for the real-time monitoring of HOS during the ultrasonic machining process for industrial and remote applications.

Evaluating Oil Palm Trunk Biochar and Palm Oil as Environmentally Friendly Sustainable Additives in Green Natural Rubber Composites

This research examines the possibility of palm oil and oil palm trunk biochar (OPTB) from pyrolysis effectively serving as alternative processing oils and fillers, substituting petroleum-based counterparts in natural rubber (NR) composites. Chemical, elemental, surface and morphological analyses were used to characterize both carbon black (CB) and OPTB, by using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) gas porosimetry, and scanning electron microscopy (SEM). The influences of OPTB contents from 0 to 100 parts per hundred rubber (phr) on thermal, dielectric, dynamic mechanical, and cure characteristics, and the key mechanical properties of particulate NR-composites were investigated. OPTB enhanced the characteristics of the composites, as demonstrated by a rise in dielectric constant, thermal stability, storage modulus, glass transition temperature (Tg), hardness and modulus at 300% elongation, along with a decrease in the loss tangent (tan δ). Tear strength exhibited an increase with OPTB content up to a specific threshold, whereas tensile strength and elongation at break declined. This implies a compromise between the various mechanical properties when incorporating OPTB as a filler. This work supports the potential application of OPTB as a renewable substitute for CB in the rubber industry, particularly in tire production and other industrial rubber applications, which would also bring environmental, sustainability, and economic benefits for the palm oil-related industry.

Effect of Ph on the Physicochemical Properties of a Cassava Peel Starch Biopolymer.

This study investigates how pH levels affect the characteristics of biopolymer films manufactured from cassava peel starch. Cassava peel starch's abundance and biodegradability make it a promising candidate for sustainable packaging. The study seeks to improve film qualities such as thickness, density, moisture content, solubility, and optical properties by altering pH levels. Understanding these effects is critical for increasing the acceptability of cassava peel starch biopolymers in a variety of industrial applications, notably environmentally friendly packaging solutions. Starch extracted from cassava peel was used to produce films using the casting method at specified pH levels. The films were evaluated for thickness and density using classical methods. Moisture content was determined following the AOAC 930.15 (2000) protocol. Color analysis was conducted using the CIELab color space technique. Water solubility and solubility in acidic (HCl) and alkaline (NaOH) solutions were assessed through chemical solubility tests performed by gravimetry. The study investigated how pH impacts biopolymer films manufactured from cassava peel starch. The film thickness varied greatly across pH levels, with pH 10.5 creating the thickest films (0.158 ± 0.012 mm) and pH 6.5 providing the thinnest (0.118 ± 0.015 mm). Density varied slightly, from 1.393 ± 0.122 g/cc to 1.551 ± 0.153 g/cc. Moisture content fluctuated significantly, affecting biodegradability. Color study indicated pH-dependent variations in transparency and opacity, with higher pH values resulting in larger color deviations (∆E). Water solubility remained constant, but NaOH solubility dropped with increasing pH, peaking at pH 7.5 (23.44 ± 2.82%). This work investigates the use of cassava peel starch for biopolymer synthesis at controlled pH levels. The findings demonstrate the material's practicality and provide critical insights for enhancing film qualities, particularly in a variety of industrial applications and environmentally friendly packaging solutions.

Construction of Escherichia coli cell factory for efficient synthesis of indigo.

Indigo is widely used in dyes, medicines and semiconductors materials due to its excellent dyeing efficiency, antibacterial, antiviral, anticancer, anti-corrosion, and thermostability properties. Here, a biosynthetic pathway for indigo was designed, integrating two enzymes (EcTnaA, MaFMO) into a higher L-tryptophan-producing the strain Escherichia coli TRP. However, the lower catalytic activity of MaFMO was a bottleneck for increasing indigo titers. To overcome this limitation, the enzyme activity of MaFMO was enhanced through mechanism-guided rational design. The optimal mutant obtained in this study, MaFMOD197E, whose kcat/Km was 1.34 times that of the wild type, and its specific activity was 2.36 times that of the wild type. In addition, the expression levels of EcTnaA and MaFMOD197E were regulated by optimizing the promoters and increasing the copy number to generate the strain E. coli IND-13. Finally, in the optimal fermentation conditions (220 rpm, 0.05% Tween-80), the strain E. coli IND-13 achieved the indigo titer of 568.52 mg/L in a 5-L bioreactor, with the yield and productivity of 2.62 mg/g and 12.96 mg/L/h (the highest to date), respectively. The results presented here can lay a foundation for further construction of cell factories for indigo and its derivatives with industrial application potential.

A Systematic Study of the Structural Properties of Technical Lignins

Technical lignins are globally available and a sustainable feedstock. The unique properties of technical lignins suggest that these materials should have several industrial applications. The main proposal of this study is to evaluate the relationship between the structure and properties of two technical lignins. Morphological, chemical, physical, and thermal properties of sodium lignosulfonate (LGNa) and magnesium lignosulfonate (LGMg) were investigated. The results showed that a higher formation of intramolecular hydrogen bonds may occur in lignins with a higher content of phenolic hydroxyl groups, such as LGMg. As a result, an increase in the energy of hydrogen bonds in the lignosulfonate structure was observed, without significant change in the hydrogen bond distances. In addition, higher content of phenolic hydroxyl groups might also reduce lignosulfonates thermal stability. The combustion index value was three times higher for LGMg than for LGNa. The characterization study also revealed that phenolic hydroxyl groups influence the main properties of technical lignins and can be a determining factor when these lignosulfonates are used in industrial applications.

A Review of Worldwide Strategies for Promoting High-Temperature Heat Pumps

This paper provides a comprehensive overview of policies and incentives aimed at promoting high-temperature heat pumps (HTHPs) globally. It examines the various strategies employed by different countries to encourage the adoption of HTHPs, highlighting both the opportunities and the barriers encountered in these efforts. The analysis includes a review of financial incentives, regulatory measures, and technological initiatives designed to facilitate the integration of HTHPs into industrial applications. By describing different approaches across regions, this paper identifies best practices and potential pitfalls, offering a nuanced understanding of how different policy frameworks impact the deployment of HTHPs. Additionally, this paper explores the technological challenges that influence the effectiveness of these policies. The findings underscore the critical role of supportive policies in overcoming technical and economic barriers, ultimately fostering the widespread use of HTHPs as a viable solution for reducing industrial emissions and advancing global decarbonization goals. Furthermore, utilizing electricity from renewable energy sources (RESs), HTHPs can also contribute to grid stability by reducing electricity peaks. This aspect enhances the integration of RESs into the energy mix, creating a more resilient grid and optimizing energy consumption patterns in industrial applications.

Elemental Germanium Activation and Catalysis Enabled by Mechanical Force

In the realm of materials science and chemical industry, germanium emerges as a strategic resource with distinctive properties that extend its applicability beyond traditional electronics and optics into the promising field of chemical catalysis. Despite its significant role in advanced technological applications, the potential of elemental germanium as a catalyst remains unexplored. Leveraging recent developments in mechanochemistry, this study introduces a groundbreaking approach to activate elemental germanium via mechanical force, facilitating the Reformatsky reaction without the reliance on external reducing agents. Meanwhile, we have also demonstrated, for the first time, the catalytic activity of elemental germanium, successfully achieving this through the bromoalkylation of alkenes. These achievements mark a significant advancement in the field of catalysis and open up a new promising avenue for both academic research and industrial applications.

Screen-Printing vs Additive Manufacturing Approaches: Recent Aspects and Trends Involving the Fabrication of Electrochemical Sensors.

A few decades ago, the technological boom revolutionized access to information, ushering in a new era of research possibilities. Electrochemical devices have recently emerged as a key scientific advancement utilizing electrochemistry principles to detect various chemical species. These versatile electrodes find applications in diverse fields, such as healthcare diagnostics and environmental monitoring. Modern designs have given rise to innovative manufacturing protocols, including screen and additive printing methods, for creating sophisticated 2D and 3D electrochemical devices. This perspective provides a comprehensive overview of the screen-printing and additive-printing protocols for constructing electrochemical devices. It is also informed that screen-printed sensors offer cost-effectiveness and ease of fabrication, although they may pose challenges due to the use of toxic volatile inks and limited design flexibility. On the other hand, additive manufacturing, especially the fused filament fabrication (or fused deposition modeling) strategies, allows for intricate three-dimensional sensor designs and rapid prototyping of customized equipment. However, the post-treatment processes and material selection can affect production costs. Despite their unique advantages and limitations, both printing techniques show promise for various applications, driving innovation in the field toward more advanced sensor designs. Finally, these advancements pave the way for improved sensor performance and expand possibilities for academic, environmental, and industrial applications. The future is full of exciting opportunities for state-of-the-art sensor technologies that will further improve our ability to detect and determine various substances in a wide range of environments as researchers continue to explore the many possibilities of electrochemical devices.

Dual-Emissive Iridium(III) Complex with Aggregation-Induced Emission: Mechanistic Insights into Electron Transfer for Enhanced Hypoxia Detection in 3D Tumor Models.

Accurate oxygen detection and measurement of its concentration is vital in biological and industrial applications, necessitating highly sensitive and reliable sensors. Optical sensors, valued for their real-time monitoring, nondestructive analysis, and exceptional sensitivity, are particularly suited for precise oxygen measurements. Here, we report a dual-emissive iridium(III) complex, IrNPh2, featuring "aggregation-induced emission" (AIE) properties and used for sensitive oxygen sensing. IrNPh2 exhibits dual emissions at 450 and 515 nm, with 515 nm triplet-state emission demonstrating remarkable oxygen sensitivity due to its long-lived excited state (12.12 μs) and high quantum yield (68%). Stern-Volmer analysis reveals a notable quenching constant (Ksv = 12.44%-1) and an ultralow detection limit of 0.0397%, emphasizing its superior performance. The oxygen quenching mechanism is driven by electron transfer (ET), supported by computational studies showing the lowest-unoccupied molecular orbital (LUMO) alignment of IrNPh2 with the πg* orbitals of triplet oxygen, leading to superoxide radical (O2•-) formation. Electron paramagnetic resonance (EPR) studies further confirm this pathway. Biological evaluations using a three-dimensional (3D) U87-MG glioma spheroid model highlight the ability of IrNPh2 to detect hypoxic regions, with significant fluorescence enhancement under hypoxia and minimal cytotoxicity (>80% viability at 100 μM). With high sensitivity, low detection limits, and biocompatibility, IrNPh2 emerges as a promising candidate for oxygen sensing in environmental and biomedical applications, especially tumor hypoxia detection.