Alzheimer's disease (AD) is the sixth leading cause of death worldwide and is characterized by progressive and irreversible neurodegeneration. By the time clinical symptoms become apparent, extensive neural damage has already occurred, highlighting the critical need for early and sensitive detection of AD biomarkers. This review summarizes recent advances in non‐enzymatic electrochemical biosensor materials for detecting AD‐associated biomarkers in biofluids for early diagnosis. Key biomarkers implicated in AD onset and progression, including amyloid‐beta (Aβ) and hyperphosphorylated Tau (p‐Tau), are discussed, as their pathological aggregation disrupts neuronal signaling pathways. Electrochemical sensors are valuable tools due to their ultra‐low detection limits (femtomolar to picomolar), broad linear dynamic ranges (nanomolar to micromolar), and high analytical sensitivity. Equally important is their selectivity toward clinically relevant concentrations of Aβ and p‐Tau in complex biofluids such as cerebrospinal fluid (CSF) and blood. This review provides a discussion of materials‐driven, non‐enzymatic electrochemical sensing approaches, offering a critical assessment of their performance, selectivity, and translational challenges in minimally invasive biofluids, an area that continues to be insufficiently addressed in current AD biosensing research. Despite significant progress, the development of low‐cost, non‐enzymatic electrochemical sensors compatible with alternative, minimally invasive biofluids, including urine and saliva, remains limited, underscoring a key challenge and opportunity for next‐generation AD diagnostics.

Glucose monitoring is essential for effective diabetes management and for reducing the risk of long-term complications. In this work, we present a low-cost, enzyme-free electrochemical platform for sweat glucose sensing, fabricated using rapid xurography and 3D printing. This portable benchtop sensing platform is constructed with a polydimethylsiloxane (PDMS) microfluidic chip, a PDMS encapsulation layer, a copper thin film electrode, and electrodeposited dendritic gold nanostructures, all embedded in a polylactic acid polymer holder. The two-inlet microfluidic configuration enables pump-free operation and provides in situ sweat pH regulation, ensuring stable glucose detection under physiologically relevant conditions. For the first time, copper oxide/copper thin film electrodes were functionalized with dendritic Au nanostructures via electrodeposition, significantly enhancing electrochemical performance. Under optimized conditions, the sensor achieved a wide linear range of 50 mu M-1 mM, high sensitivity of 2889.3 mu AmM(-1)cm(-2), excellent reproducibility (RSD % = 3.36 %), good reusability (similar to 91 % signal retention after four cyclic voltammetry cycles), and long-term stability (89.6 % retention after four weeks of storage). The sensor also demonstrated robust selectivity in artificial sweat, maintaining similar to 87-90 % of its glucose signal in the presence of common interferents such as ascorbic acid and sodium chloride. Moreover, the platform exhibited reusability, portability, easy scalability, and a high sensitivity of 2007.9 mu AmM(-1)cm(-2) in artificial sweat, highlighting its potential for real-time, non-invasive glucose monitoring. Given its affordability, simplicity, and strong analytical performance, this sensing system represents a promising point-of-care technology, particularly relevant for low- and middle-income countries, where accessible diabetes management tools are urgently needed.

Elevated methylglyoxal (MG) levels contribute to diabetes-related complications through accelerated formation of advanced glycation end products, highlighting the need for sensitive, portable, and non-invasive monitoring strategies. Here, we report a gold-carbon nanohybrid electrochemical MG sensor integrated into a three-dimensional printed microfluidic platform for point-of-care analysis. The sensing interface is engineered by sequential electrodeposition of carboxyl-functionalized multi-walled carbon nanotubes (fMWCNT) and gold nanoparticles (AuNPs) onto a screen-printed carbon electrode (SPCE). The fMWCNT provide a high-surface-area scaffold for MG adsorption, while AuNPs enhance electroactive surface area and electron transfer. The AuNPs/fMWCNT/SPCE sensor exhibits quasi-reversible electrochemical behavior suitable for sensitive MG detection. The optimized sensor achieves reliable MG detection across a wide dynamic range (50 nM-100 µM), with limits of detection of 40 nM in aqueous media and 400 nM in artificial sweat. Accurate MG quantification in human saliva and sweat, with recoveries exceeding 97%, demonstrates robustness in complex biological matrices. This work demonstrates the potential of this electrochemical sensing system for future wearable biosensors and personalized diabetes monitoring.

Bisphenol A (BPA), an endocrine-disrupting contaminant released from polymeric materials, requires ultrasensitive monitoring to safeguard water quality and public health. Here, we present a simple and low-cost electrochemical sensor based on cetrimonium bromide (CTAB) and beta-cyclodextrin-functionalized multi-walled carbon nanotubes (MWCNT -beta-CD) integrated onto a screen-printed carbon electrode (SPCE). BPA undergoes an adsorption-controlled, two-electron/two-proton oxidation process at the CTAB/MWCNT-beta-CD/SPCE interface. Linear sweep voltammetry enabled a detection limit of 7.82 pM and a broad dynamic range of 10 pM-10 & micro;m. The picomolar sensitivity arises from synergistic CTAB-mediated analyte preconcentration and the high surface area and conductivity provided by MWCNT-beta-CD. The sensor exhibited excellent stability, reproducibility, and selectivity in the presence of common inorganic, phenolic compounds, BPA analogues, and electroactive bimolecular species. Quantification in spiked bottled, tap, and lake water samples yielded recoveries of 90.36%-104.33%, consistent with LC-MS validation. These results demonstrate that CTAB/MWCNT-beta-CD-modified SPCEs provide a robust and practical platform for on-site ultratrace detection of BPA in environmental waters.

Excessive use of antibiotics can lead to antibiotic resistance, posing a significant threat to human health and the environment. Chloramphenicol (CAP), once widely used, has been banned in many regions for over 20 years due to its toxicity. Detecting CAP residues in food products is crucial for regulating safe use and preventing unnecessary antibiotic exposure. Electrochemical sensors are low-cost, sensitive, and easily detect CAP. This paper reviews recent research on electrochemical sensors for CAP detection, with a focus on the materials and fabrication techniques employed. The sensors are evaluated based on key performance parameters, including limit of detection, sensitivity, linear range, selectivity, and the ability to perform simultaneous detection. Specifically, we highlight the use of metal and carbon-based electrode modifications, including gold nanoparticles (AuNPs), nickel–cobalt (Ni-Co) hollow nano boxes, platinum–palladium (Pt-Pd), graphene (Gr), and covalent organic frameworks (COFs), as well as molecularly imprinted polymers (MIPs) such as polyaniline (PANI) and poly(o-phenylenediamine) (P(o-PD)). The mechanisms by which these modifications enhance CAP detection are discussed, including improved conductivity, increased surface-to-volume ratio, and enhanced binding site availability. The reviewed sensors demonstrated promising results, with some exhibiting high selectivity and sensitivity, and the effective detection of CAP in complex sample matrices. This review aims to support the development of next-generation sensors for antibiotic monitoring and contribute to global efforts to combat antibiotic resistance.

Green nanomaterial-based electrochemical sensors have attracted considerable attention owing to their biocompatibility, cost-effectiveness, and reduced environmental impact. Hydrogen peroxide (H2O2), a key biomarker of oxidative stress associated with aging and various pathologies, requires sensitive and selective detection for reliable biomedical diagnostics. In this work, silver nanoparticles (AgNPs) were synthesized via a green route using orange peel extract (OPE) as both a natural reducing and stabilizing agent, and subsequently employed to fabricate a nonenzymatic H2O2 sensor based on AgNP-modified screen-printed carbon electrodes (AgNPs/SPCEs). Structural and spectroscopic characterization confirmed the formation of crystalline AgNPs with an average diameter of similar to 32 nm. Electrochemical analysis by cyclic voltammetry demonstrated excellent sensing performance, with dual linear ranges (0.5-10 mu M and 10-161.8 mu M), a high sensitivity of 20,160 mu A mM(-1) cm(-2), and a low detection limit of 0.3 mu M, S/N = 3. Amperometric studies demonstrated high selectivity against common interferents such as ascorbic acid, dopamine, glucose, glutamate, and uric acid. The sensor also achieved reliable detection of H2O2 in human urine, highlighting its potential for clinical applications. Furthermore, the versatility of the sensing platform was established by immobilizing glucose oxidase onto AgNPs/SPCEs, enabling enzymatic glucose sensing within a physiologically relevant range (3-18 mM). Collectively, these findings establish green-synthesized AgNP-based electrodes as a sustainable, cost-effective, and highperformance platform for the detection of oxidative stress biomarkers and glucose dysregulation in clinical diagnostics.

Health and environmental monitoring are essential for protecting ecosystems, ensuring public health, and promoting sustainable development. Nanomaterial-based electrochemical sensors have emerged as powerful tools for on-site monitoring of a wide range of analytes, including biomarkers, pharmaceuticals, heavy metals, toxic substances, and microplastics. These sensors offer rapid, reliable, and cost-effective measurements by leveraging the unique chemical and physical properties of nanomaterials, such as high effective surface area and catalytic activity, which enhance sensitivity and selectivity—critical features for effective health and environmental protection. However, traditional chemical synthesis methods for nanomaterials often involve high temperatures and hazardous chemicals, which contradict the principles of sustainability. To address these issues, green synthesis techniques have been developed, utilizing eco-friendly substances such as plant extracts, microorganisms, and other biological systems. Green synthesis not only promotes environmental sustainability and cost-efficiency but also produces nanomaterials with unique properties that can further enhance sensing performance. This chapter will review the methodologies employed in green synthesis, highlighting their distinct characteristics and the application of green nanomaterials in electrochemical sensors. It also addresses the challenges in this field and explores potential avenues for future advancements, including the integration of smart sensing technologies for real-time and remote monitoring.

Tryptophan (Trp) and tryptamine (Tryp), critical biomarkers in mood regulation, immune function, and metabolic homeostasis, are increasingly recognized for their roles in both oral and systemic pathologies, including neurodegenerative disorders, cancers, and inflammatory conditions. Their rapid, sensitive detection in biofluids such as saliva—a non-invasive, real-time diagnostic medium—offers transformative potential for early disease identification and personalized health monitoring. This review synthesizes advancements in electrochemical sensor technologies tailored for Trp and Tryp quantification, emphasizing their clinical relevance in diagnosing conditions like oral squamous cell carcinoma (OSCC), Alzheimer’s disease (AD), and breast cancer, where dysregulated Trp metabolism reflects immune dysfunction or tumor progression. Electrochemical platforms have overcome the limitations of conventional techniques (e.g., enzyme-linked immunosorbent assays (ELISA) and mass spectrometry) by integrating innovative nanomaterials and smart engineering strategies. Carbon-based architectures, such as graphene (Gr) and carbon nanotubes (CNTs) functionalized with metal nanoparticles (Ni and Co) or nitrogen dopants, amplify electron transfer kinetics and catalytic activity, achieving sub-nanomolar detection limits. Synergies between doping and advanced functionalization—via aptamers (Apt), molecularly imprinted polymers (MIPs), or metal-oxide hybrids—impart exceptional selectivity, enabling the precise discrimination of Trp and Tryp in complex matrices like saliva. Mechanistically, redox reactions at the indole ring are optimized through tailored electrode interfaces, which enhance reaction kinetics and stability over repeated cycles. Translational strides include 3D-printed microfluidics and wearable sensors for continuous intraoral health surveillance, demonstrating clinical utility in detecting elevated Trp levels in OSCC and breast cancer. These platforms align with point-of-care (POC) needs through rapid response times, minimal fouling, and compatibility with scalable fabrication. However, challenges persist in standardizing saliva collection, mitigating matrix interference, and validating biomarkers across diverse populations. Emerging solutions, such as AI-driven analytics and antifouling coatings, coupled with interdisciplinary efforts to refine device integration and manufacturing, are critical to bridging these gaps. By harmonizing material innovation with clinical insights, electrochemical sensors promise to revolutionize precision medicine, offering cost-effective, real-time diagnostics for both localized oral pathologies and systemic diseases. As the field advances, addressing stability and scalability barriers will unlock the full potential of these technologies, transforming them into indispensable tools for early intervention and tailored therapeutic monitoring in global healthcare.

Gold nanoparticles (AuNPs) were synthesized using HAuCl 4 and orange peel extract. AuNPs and CuO modified screen printed carbon electrode (Au/CuO/SPCE) converts glucose to gluconolactone. This sensor was applied for detection of glucose in saliva.

Siemens LOGO PLC is a compact system for small automation projects, programmed via LOGO Soft Comfort. Its graphical interface enables easy circuit program creation, facilitating customized control systems swiftly. LOGO Soft Comfort allows offline and online testing, simulation, and program archiving. PLC timers, integral to the system, regulate input and output signals, functioning like relay timers without physical presence or wiring. This paper delves into PLC-based industrial timer controllers, designed to supersede traditional hard-wired relay and timer logic systems. Common PLC timers include Pulse, On-delay, Retentive On-delay, and Off-delay timers, pivotal for time delays and production monitoring in industries. They facilitate actions like turning machines off after set periods or initiating them after specific delays upon sensor activation or button press

Monitoring bovine serum albumin (BSA) at ultra-low levels is crucial for clinical and food safety applications, as it plays a significant role in identifying various health conditions and potential risks, necessitating fast, trace- level detection of BSA. This study proposes an approach to address these challenges by employing molecularly imprinted polymer (MIP) to develop an ultra-trace-level and cost-effective BSA sensing platform. The MIP electrochemical sensor was developed using polyaniline (PANI) combined with the protein crosslinker glutaraldehyde (GA) to optimize BSA surface imprinting in the MIP. As a result, the sensor achieves a sensitivity of 1.24 mu A/log(pg/mL), with a picomolar detectable limit of 2.3 pg/mL (0.035 pM) and a wide detection range from 20 pg/mL to 200,000 pg/mL (0.303 pM to 3030 pM), making it suitable for clinical and food safety applications. Additionally, the study explores the interaction between an acidic surfactant protein eluent (acetic acid with sodium dodecyl sulfate, AcOH-SDS) and BSA vacant sites, enhancing recognition and re-binding. The PANI-based MIP sensor demonstrates initial feasibility and practicality in commercial milk and real human serum, opening avenues for early disease detection and ensuring food safety in BSA-related immune responses.

Dopamine (DA) is the most prevalent neurotransmitter in the brain and plays a crucial role in several pathologies, such as Parkinson's disease and schizophrenia. Early diagnosis of these pathologies is crucial and requires the development of highly effective detection methods. In this review, we cover advances in the development and use of electrochemical DA sensors over the last five years and identify areas for improvement for their use in clinical applications. We focus on how the performance of these sensors can be improved by functionalizing a variety of materials, including metal, polymer, ionic liquid, and carbon, to detect low levels of DA from nanomoles to femtomoles. Although many of the sensors have a limit of detection in synthetic solutions that meets or exceeds the concentration range of DA in biofluids, they have yet to achieve these levels in real samples due to the presence of interferents with similar redox potentials. To detect DA simultaneously with other analytes such as uric acid and ascorbic acid, higher selectivity and lower limits of detection are necessary. We believe that this review will contribute to the future development of improved DA sensors for clinically relevant applications.

Glutamate is an important neurotransmitter due to its critical role in physiological and pathological processes. While enzymatic electrochemical sensors can selectively detect glutamate, enzymes cause instability of the sensors, thus necessitating the development of enzyme-free glutamate sensors. In this paper, we developed an ultrahigh sensitive nonenzymatic electrochemical glutamate sensor by synthesizing copper oxide (CuO) nanostructures and physically mixing them with multiwall carbon nanotubes (MWCNTs) onto a screen-printed carbon electrode. We comprehensively investigated the sensing mechanism of glutamate; the optimized sensor showed irreversible oxidation of glutamate involving one electron and one proton, and a linear response from 20 μM to 200 μM at pH 7. The limit of detection and sensitivity of the sensor were about 17.5 μM and 8500 μA·mM−1·cm−2, respectively. The enhanced sensing performance is attributed to the synergetic electrochemical activities of CuO nanostructures and MWCNTs. The sensor detected glutamate in whole blood and urine and had minimal interference with common interferents, suggesting its potential for healthcare applications.

Levels of lead (Pb) in tap water that are well below established guidelines are now considered harmful, so the detection of sub-parts-per-billion (ppb) Pb levels is crucial. In this work, we developed a two-step, facile, and inexpensive fabrication approach that involves direct bonding of copper (Cu) and liquid crystal polymer (LCP) followed by polyester resin printing for masking onto Cu/LCP to fabricate Cu thin-film-based Pb sensors. The oxygen plasma-treated surfaces resulted in strongly bonded Cu/LCP with a high peel strength of 500 N/m due to the highly hydrophilic nature of both surfaces. The bonded specimen can withstand wet etching of the electrode and can address delamination of the electrode for prolonged use in application environments. The Cu-foil-based electrochemical sensor showed sensitivity of ~11 nA/ppb/cm2 and a limit of detection (LOD) of 0.2 ppb (0.2 µg/L) Pb ions in water. The sensor required only 30 s and a 100 µL sample to detect Pb. To date, this is the most rapid detection of Pb performed using an all-Cu-based sensor. The selectivity test of Cu to Pb with interferences from cadmium and zinc showed that their peaks were separated by a few hundred millivolts. This approach has strong potential towards realizing low-cost, highly reliable integrated water quality monitoring systems.

This article presents a comprehensive analysis of a 16-FSK modulator and demodulator's performance over a Rician fading channel, which accurately models wireless communication channels with line-of-sight and non-line-of-sight components. The study investigates the impact of various parameters, including the Rician K-factor, Maximum Diffuse Doppler Shift, and Delay Vector, using the MATLAB Simulink communication blockset. The results indicate that increasing the K-factor and delay vector of the channel leads to an improvement in bit error rate. Additionally, it is observed that the maximum diffuse Doppler shift has minimal influence on the bit error rate. These findings provide valuable insights into optimizing the performance of 16-FSK modulation schemes in Rician fading channels, thereby enhancing the design and deployment of wireless communication systems.

Glutamate is the most abundant neurotransmitter in the central nervous system (CNS) and plays an important role in different physiological processes. Excess amounts of glutamate cause excitotoxicity resulting in different diseases such as Alzheimer’s and glioma, pain disorders, spinal cord injuries, and cancer1-4. The concentration of glutamate in body fluids such as saliva is associated with those diseases. Therefore, glutamate is a potential biomarker for pathologies. By measuring glutamate levels in biofluids these pathologies can be monitored. Lab-based techniques such as liquid chromatography and gas chromatography offer a low limit of detection, high sensitivity, and precise detection of biomarkers4-7. These techniques are expensive, bulky, time-consuming, and require skilled personnel to operate them and therefore are not suitable for wearable and personalized healthcare applications. In contrast, electrochemical sensors are simple, low-cost, handy, and offer rapid and high sensing performance of biomarkers/analytes8,9. In this work, we fabricated a very simple, low-cost, and reusable enzyme-free electrochemical sensor using copper oxide (CuO) nanomaterials for label-free detection of glutamate. CuO nanomaterials were synthesized by a low-cost wet chemical process. The CuO nanomaterials were dispersed in DI water and the working electrode was prepared by drop casting of CuO dispersion on a screen-printed carbon electrode (SPCE). Multiwall carbon nanotubes (MWCNTs) were used with CuO to enhance the electron transfer from CuO to SPCE (Figure a). Cyclic voltammetry (CV) and linear sweep voltammetry (LSV) were used to perform glutamate sensing in deionized (DI) water at pH 7.4. The peak oxidation current (I pa) is proportional to glutamate (G) presence in DI water (Figure b). The sensor showed good oxidation current event at a low concentration of glutamate (20 µM) in DI water. The normal concentrations of glutamate in body fluids such as plasma and saliva are about 5-100 µM, and 1-30 µM respectively 3. Therefore, CuO nanostructure-based nonenzymatic electrochemical sensor is very potential for low cost, portable, rapid detection of glutamate in those body fluids. We will further discuss details of CuO synthesis, electrode fabrication process, sensing mechanism, and challenges of the glutamate sensor. References Lewerenz and P. Maher, Frontiers in neuroscience. 9 (2015) 469. Takano et al., Nature medicine. 7 (2001) 1010-1015. H Jasim et al., Scientific reports 8.1 (2018): 1-9. Schultz, Z. Uddin, G. Singh, and M. M. Howlader, Analyst. 145 (2020) 321-347. Klimuntowski, M. M. Alam, G. Singh, and M. M. Howlader, ACS Sensor. 5(3) (2020) 620–636. Budczies et al., International journal of cancer. 136 (2015) 1619-1628. Xin et al, Chinese Journal of Analytical Chemistry. 35 (2007), 1151-1154. Hughes et al., Sensors and Actuators B: Chemical. 216 (2015) 614-621. Rocchitta et al., Sensors, 16 (2016) 780. X Zhang et al., The Journal of Physical Chemistry C 112.43 (2008): 16845-16849. Y Li et al., Materials Research Bulletin 43.8-9 (2008): 2380-2385. RP Allaker, and Z Yuan, Nanobiomaterials in clinical dentistry. Elsevier, 2019. 243-275. Figure 1

Moringa oleifera, a perennial tree of Indian origin, is cultivated in several tropical and sub-tropical countries because of its ability to grow under unfavourable conditions such as poor soil, lower requirement of water and managemental practices. The leaves and pods of the plant are highly rich in essential nutrients such as protein, vitamin, essential amino acids, macro and micro elements in addition to the presence of diverse nutraceutical molecules such as antioxidant, flavonoids, isothiocyanates, phenolics etc. The presence of bioactive principles in different parts of the Moringa plant prompted the people to use it as part of traditional medicines for the cure of several human ailments such as diabetes, intestinal worms, hyperlipidaemia, high blood pressure, muscle spasm, constipation, ringworm, etc. With the growing health consciousness coupled with phobia against modern chemical based therapeutic, there is increasing demands for plant sourced nutraceuticals. Evidently, this gives opportunity for development of Moringa based product for welfare of human society. The current review made an effort to summarize the research advancement on different aspects of Moringa oleifera focussing on taxonomy, cultivation, nutritional attributes, therapeutic values, and value-added products of this divine tree. SAARC J. Agric., 20(2): 1-15 (2022)

Nitrogen (N) is the prime nutrient for crop production and carbon-based functions associated with soil quality. The objective of our study (2012 to 2019) was to evaluate the impact of variable rates of N fertilization on soil organic carbon (C) pools and their stocks, stratification, and lability in subtropical wheat (Triticum aestivum)-mungbean (Vigna radiata)-rice (Oryza sativa L) agroecosystems. The field experiment was conducted in a randomized complete block design (RCB) with N fertilization at 60, 80, 100, 120, and 140% of the recommended rates of wheat (100 kg/ha), mungbean (20 kg/ha), and rice (80 kg/ha), respectively. Composite soils were collected at 0-15 and 15-30 cm depths from each replicated plot and analyzed for microbial biomass (MBC), basal respiration (BR), total organic C (TOC), particulate organic C (POC), permanganate oxidizable C (POXC), carbon lability indices, and stratification. N fertilization (120 and 140%) significantly increased the POC at both depths; however, the effect was more pronounced in the surface layer. Moreover, N fertilization (at 120% and 140%) significantly increased the TOC and labile C pools when compared to the control (100%) and the lower rates (60 and 80%). N fertilization significantly increased MBC, C pool (CPI), lability (CLI), and management indices (CMI), indicating improved and efficient soil biological activities in such systems. The MBC and POC stocks were significantly higher with higher rates of N fertilization (120% and 140%) than the control. Likewise, higher rates of N fertilization significantly increased the stocks of labile C pools. Equally, the stratification values for POC, MBC, and POXC show evidence of improved soil quality because of optimum N fertilization (120-140%) to maintain and/or improve soil quality under rice-based systems in subtropical climates.

Water quality depends on many factors. Some of them are essential for maintaining the minimum sustainability of water. Because of the great dependence of fishes on the condition of the aquatic environment, the water quality can directly affect their activity. Therefore monitoring water quality is a very important issue to consider, especially in the fish farming industry. In this paper a digital fish farm monitoring system is introduced and a collection of experimental data of water quality monitoring was presented, which were directly collected from a fish pond. As the quality factor of water affects its aquatic life form sustainability, therefore the quality factors of the water were measured using digital sensors. Temperature, pH factor and Turbidity were selected as the basic quality factors to measure. The dataset contains data recorded from two different water levels to analyze the aquatic environment more efficiently. Each level has 9623 sets of data of the selected parameters. Collection was continued all day long for several days. Later collected sensor data were analyzed as short period time series to find its properties. Machine Learning regression method was used to predict near future conditions. Moreover data were processed to find any repetitive patterns in its properties. This dataset represents the exact condition of the environment of the fish pond. Therefore it can be used to develop a system to monitor fish farms digitally. Using these data in machine learning, predicting the future is possible for advance monitoring of a fish farm. The dataset is available in Mendeley Data [1].

Bisphenol A (BPA), one of the most extensively used plasticizers, is an endocrine disrupting chemical (EDC). Leaching of BPA in food, and water sources causes adverse health effects, therefore, it requires monitoring. In this work, we developed a simple, low-cost electrochemical sensor for detecting a very low level of BPA in water using chemically modified multiwall carbon nanotubes (MWCNTs) with beta-cyclodextrin (beta CD) on screen-printed carbon electrode (SPCE). The electrochemical sensing of BPA showed a completely irreversible process with diffusion-controlled oxidation involving two electrons and two protons. At an optimized condition, the sensor showed a two-step linear response from 125 nM to 2 mu M and 2 to 30 mu M, with correlation coefficients of 0.997 and 0.995, respectively. The limit of detection for BPA was determined to be 13.76 nM (SNR = 3). The improved sensing performance is attributed to host-guest interaction ability of MWCNTs- beta CD with BPA due to the combined effect of hydrophilic behavior of beta CD and large surface area of MWCNTs. The sensors exhibited an excellent reproducibility (RSD = 4.7 %) and stable response over five weeks and negligible interference with common chemical species in water. The sensor's reliability test in lake and tap water showed an excellent recovery of BPA ranging from 96.05 %-108.70 %. These favorable results can enable the development of simple and cheap portable sensors for monitoring a wide range of BPA levels in the water.