A green impedimetric aptasensor for non-invasive and high-selective detection of tramadol validated by molecular dynamic simulation.

Although the dosage controlling of tramadol (TRA) as a banned deadly drug in human biofluids is medicolegally important a biocompatible method for its high-selective detection with fewer false interferences has been scarcely reported. Herein, a new impedimetric aptasensor is introduced by utilizing the aptamer (Apt) sequence with high affinity to TRA for the first time to non-invasively measure it. An oriented nanolayer of Au nanoparticles (AuNPs) is easily formed on the surface by the electrodeposition technique to high-densely load the Apt and embed the novel aptasensing interface via a user-friendly methodology.

Applicability of a green nanocomposite consists of reduced graphene oxide and β-cyclodextrin for electrochemical tracing of methadone in human biofluids validated by international greenness indexes.

Background: Detecting methadone (MET) is crucial due to its severe side effects.

Method: Herein, a green nanocomposite based on reduced graphene (rGO) and β-cyclodextrin (β-CD) has been introduced to modify a glassy carbon electrode (GCE) for real-time measurement of MET. This eco-friendly sensing interface has synergistically benefited from both advantages of rGO and β-CD including excellent electron transfer tunneling and surface area enhancement to selectively trap MET based on its shape and size.

High-performance cellulose acetate fibers-loaded Alca layered double oxide adsorbents towards efficient elimination of anionic pollutants: Mechanism adsorption and RSM-CCD approach.

In the present research, we investigate Congo red (CR) removal by layered double hydroxide and oxide AlCa on cellulose acetate (CA) fiber as anion-adsorbents in aqueous solution. The as-prepared composite was characterized by FE-SEM, XRD, FTIR, EDS-mapping and BET-BJH analyses. The CR adsorption ability on AlCa LDH/CA and AlCa LDO/CA adsorbents was evaluated.

Central composite design-assisted visual and non-invasive detection of sertraline by sweet lemon waste-derived core-shell AuNPs@CDs.

This study reports a fast and visual detection method of antidepressant sertraline (SRT) drug by the core-shell AuNPs@CDs as the nanoprobes. The CDs has been eco-friendly synthesized from sweet lemon wastes to directly reduce Au to AuNPs without any external photoirradiation process or additional reductants. Optimizing key variables that impact the sensing process has been done using the central composite design (CCD) approach to simulate the assay condition before the analysis.

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches.

Buildings are rapidly becoming more digitized, largely due to developments in the internet of things (IoT). This provides both opportunities and challenges. One of the central challenges in the process of digitizing buildings is the ability to monitor these buildings' status effectively.