Sustainable Synthesis Processes for Carbon Dots through Response Surface Methodology and Artificial Neural Network

Hemostatic bioactivity and mechanism of novel Rubia cordifolia L.-derived carbon dots

Background: Rubia cordifolia L. (RCL) Carbonisata is a typical calcined natural medicinal plant, which has been used for thousands of years for hemostasis. At present, some studies have shown that some components of processed RCL Carbonisata can enhance hemostasis, but the specific hemostatic material basis is still unclear. Novel carbon dots (CDs) were obtained from Rubia cordifolia L. and named RCL-CDs to explore the hemostatic effect and mechanism of RCL-CDs obtained from Rubia cordifolia L. Methods: RCL-CDs were characterized by transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FT-IR), ultraviolet visible spectroscopy (UV-Vis), fluorescence spectroscopy (FL), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The hemostatic effect of RCL-CDs was evaluated in a mouse tail amputation model and liver scratch model, and the hemostatic mechanism was explored using a capillary coagulation model and coagulation parameters. Results: The particle size distribution of RCL-CDs ranged from 1.74 nm to 9.78 nm, the maximum population was 3-4 nm, and the average particle size was 3.82 nm. The RCL-CDs were approximately spherical with a lattice spacing of 0.206 nm. The quantum yield (QY) of RCL-CDs is 1.09%, and there is a distinct diffraction peak at 2θ = 24.76°. The elemental composition of RCL-CDs was mainly C (65.28%), O (30.10%), and a small amount of N (4.62%). Pharmacological experiments showed that bleeding time and bleeding volume were reduced in mice treated with RCL-CDs. It is worth noting that the low-, medium- and high-dose RCL-CD groups can significantly reduce the blood loss, while the high-dose RCL-CD group can significantly reduce the bleeding time of the mouse tail amputation model and liver scratch model. Additionally, the fibrinogen level (FIB) and platelet counts (PLT) increased and prothrombin time (PT) decreased in rats after treatment with RCL-CDs. Conclusions: RCL-CDs have a significant hemostatic effect, and the mechanism may be exogenous coagulation and activation of fibrinogen. This explains the material basis of the hemostatic effect of RCLC and opens new avenues for more in-depth investigation. In addition, new insights into the potential biomedical applications of CDs in the field of nanohemostasis are provided and a solid foundation for the discovery of novel hemostatic agents is established.

Europium (III)-modified sunflower-derived carbon dots for fluorescent anti-counterfeiting inks and photocatalysis

A highly water-soluble and fluorescent N,S-doped carbon dots/europium (N,S-CDs/Eu) was successfully synthesized via a secondary hydrothermal method. This involved surface modification of N,S-CDs derived from sunflower stem pith (SSP) with europium ions (Eu3+) doping. When excited within the range of 400-470 nm, N,S-CDs/Eu exhibited a stable and broad optimal emission wavelength ranging from 505 to 540 nm. Notably, the photoluminescence quantum yield (PLQY) of N,S-CDs/Eu is 31.4%, significantly higher than the 19.5% observed for N,S-CDs. Additionally, by dissolving N,S-CDs/Eu into polyvinyl alcohol (PVA), a uniform fluorescent anti-counterfeiting ink can be prepared. The N,S-CDs/Eu/TiO2 composite demonstrates excellent photocatalytic degradation ability towards the organic dye methylene blue (MB). N,S-CDs/Eu has potential in the field of fluorescent inks and photocatalysis due to its simple and efficient preparation and excellent properties.

Recent advances in the metamaterial and metasurface-based biosensor in the gigahertz, terahertz, and optical frequency domains

Recently, metamaterials and metasurface have gained rapidly increasing attention from researchers due to their extraordinary optical and electrical properties. Metamaterials are described as artificially defined periodic structures exhibiting negative permittivity and permeability simultaneously. Whereas metasurfaces are the 2D analogue of metamaterials in the sense that they have a small but not insignificant depth. Because of their high optical confinement and adjustable optical resonances, these artificially engineered materials appear as a viable photonic platform for biosensing applications. This review paper discusses the recent development of metamaterial and metasurface in biosensing applications based on the gigahertz, terahertz, and optical frequency domains encompassing the whole electromagnetic spectrum. Overlapping features such as material selection, structure, and physical mechanisms were considered during the classification of our biosensing applications. Metamaterials and metasurfaces working in the GHz range provide prospects for better sensing of biological samples, THz frequencies, falling between GHz and optical frequencies, provide unique characteristics for biosensing permitting the exact characterization of molecular vibrations, with an emphasis on molecular identification, label-free analysis, and imaging of biological materials. Optical frequencies on the other hand cover the visible and near-infrared regions, allowing fine regulation of light-matter interactions enabling metamaterials and metasurfaces to offer excellent sensitivity and specificity in biosensing. The outcome of the sensor's sensitivity to an electric or magnetic field and the resonance frequency are, in theory, determined by the frequency domain and features. Finally, the challenges and possible future perspectives in biosensing application areas have been presented that use metamaterials and metasurfaces across diverse frequency domains to improve sensitivity, specificity, and selectivity in biosensing applications.

Enhanced photosynthetic efficiency by nitrogen-doped carbon dots via plastoquinone-involved electron transfer in apple

Artificially enhancing photosynthesis is critical for improving crop yields and fruit qualities. Nanomaterials have demonstrated great potential to enhance photosynthetic efficiency; however, the mechanisms underlying their effects are poorly understood. This study revealed that the electron transfer pathway participated in nitrogen-doped carbon dots (N-CDs)-induced photosynthetic efficiency enhancement (24.29%), resulting in the improvements of apple fruit qualities (soluble sugar content: 11.43%) in the orchard. We also found that N-CDs alleviated mterf5 mutant-modulated photosystem II (PSII) defects, but not psa3 mutant-modulated photosystem I (PSI) defects, suggesting that the N-CDs-targeting sites were located between PSII and PSI. Measurements of chlorophyll fluorescence parameters suggested that plastoquinone (PQ), the mobile electron carrier in the photosynthesis electron transfer chain (PETC), was the photosynthesis component that N-CDs targeted. In vitro experiments demonstrated that plastoquinone-9 (PQ-9) could accept electrons from light-excited N-CDs to produce the reduced plastoquinone 9 (PQH2-9). These findings suggested that N-CDs, as electron donors, offer a PQ-9-involved complement of PETC to improve photosynthesis and thereby fruit quality. Our study uncovered a mechanism by which nanomaterials enhanced plant photosynthesis and provided some insights that will be useful in the design of efficient nanomaterials for agricultural/horticultural applications.

Green tea waste-derived carbon dots: efficient degradation of RhB dye and selective sensing of Cu2+ ions

Herein, we have synthesized carbon dots (CDs) using a one-step hydrothermal method from green tea waste, a biomass-derived source with high fluorescent properties and excellent solubility in water. The synthesis of CDs was confirmed through a comprehensive range of characterization techniques, including HRTEM (high-resolution transmission electron microscopy), XPS (X-ray photoelectron spectroscopy), and EDX (energy-dispersive X-ray spectroscopy). The optical properties of the synthesized CDs were assessed using UV-Vis spectroscopy and fluorescence (FL) spectroscopy. The CDs displayed exceptional stability across a wide pH range and various concentrations. Moreover, these CDs exhibited a photoluminescence quantum yield (PLQY) of 21.6%, indicating their efficiency in emitting fluorescent light upon excitation. The CDs also showcased their prowess in fluorometrically detecting Cu2+ ions, displaying high sensitivity and selectivity. They presented two distinct linear ranges: 0.02 to 50 µM and 50 to 100 µM, with recovery rates ranging from 94.2 to 104.06%. Moreover, under visible light irradiation, the CDs exhibited significant efficiency in the photocatalytic removal of dyes. Specifically, the CDs achieved degradation rate of 97.89% for Rhodamine B (RhB) within a 30-min irradiation period. In the context of RhB adsorption, it is evident that the experimental data align more closely with the Freundlich isotherm than the Langmuir isotherm. This is substantiated by a higher R2 value (0.97) for the Freundlich isotherm model compared to the Langmuir adsorption isotherm model (0.93). Notably, the adsorption kinetics was effectively described by pseudo first-order kinetics models. Overall, these results highlight the promising potential of CDs in applications such as environmental remediation and waste treatment processes due to their photocatalytic and sensing capabilities.

The Flexural Strength Prediction of Carbon Fiber/Epoxy Composite Using Artificial Neural Network Approach

There is a developing demand for natural resources because of the growing population. Alternative materials have been developed to address these shortages, concentrating on characteristics such as durability and lightness. By researching composite materials, natural materials can be replaced. It is vital to consider the mechanical properties of composite materials when selecting them for a specific application. This study aims to measure the flexural strength of carbon fiber/epoxy composites. However, the cost of forming these composites is relatively high, given the expense of composite materials. Consequently, this study seeks to reduce molding costs by predicting flexural strength. Conducting many tests for each case is costly; therefore, it is necessary to discover an economical method. To accomplish this, the flexural strength of carbon fiber/epoxy composites was investigated using an artificial neural network (ANN) technique to reduce the expense of material testing. The output parameter investigated was flexural strength, while input parameters included ply orientation, manufacturing, width, thickness, and graphite filler percentage. The scope alternative was determined by identifying the values of variables that substantially affect the flexural strength. The prediction of flexural strength was deemed acceptable if the mean squared error (MSE) value was less than 0.001, and the coefficient of determination (R2) was greater than or equal to 0.95. The obtained results demonstrated an MSE of 0.003039 and an R2 value of 0.95274, indicating a low prediction error and high prediction accuracy for all flexural strength data. Thus, the outcomes of this study provide accurate predictions of flexural strength in the composite materials.

Violuric acid carbon dots as a highly fluorescence probe for ultrasensitive determination of Zn (II) in tomato paste

Zinc is an essential metal since it plays an important role in biological systems, therefore, determination of zinc in food samples is important. Violuric acid was used to prepare highly fluorescent carbon dots (CDs), when it irradiated with ultraviolet radiation at 365 nm, a strong violet fluorescence was observed which caused by the increased amount of nitrogen in the CD structure, which were then successfully used for sensing zinc ion based on quenching of fluorescence. Violuric acid's hydrothermal carbonization reaction's temperature and time were simply optimized for better-quality performance of the CDs as-synthesized. The probe was characterized by HRTEM, SEM, XRD, EDX, fluorescence, UV-Visible absorption spectrophotometry, and FTIR. With a lower LOD 0.32 nM, the developed approach demonstrates an exceptional sensitivity and good selective response to the Zn²⁺ at 25℃. Compared to the results from ICP, the sensor was successfully used for determination of Zn²⁺ ions in tomato paste samples.

Carbon-Based Fluorescent Nano-Biosensors for the Detection of Cell-Free Circulating MicroRNAs

Currently, non-communicable diseases (NCDs) have emerged as potential risks for humans due to adopting a sedentary lifestyle and inaccurate diagnoses. The early detection of NCDs using point-of-care technologies significantly decreases the burden and will be poised to transform clinical intervention and healthcare provision. An imbalance in the levels of circulating cell-free microRNAs (ccf-miRNA) has manifested in NCDs, which are passively released into the bloodstream or actively produced from cells, improving the efficacy of disease screening and providing enormous sensing potential. The effective sensing of ccf-miRNA continues to be a significant technical challenge, even though sophisticated equipment is needed to analyze readouts and expression patterns. Nanomaterials have come to light as a potential solution as they provide significant advantages over other widely used diagnostic techniques to measure miRNAs. Particularly, CNDs-based fluorescence nano-biosensors are of great interest. Owing to the excellent fluorescence characteristics of CNDs, developing such sensors for ccf-microRNAs has been much more accessible. Here, we have critically examined recent advancements in fluorescence-based CNDs biosensors, including tools and techniques used for manufacturing these biosensors. Green synthesis methods for scaling up high-quality, fluorescent CNDs from a natural source are discussed. The various surface modifications that help attach biomolecules to CNDs utilizing covalent conjugation techniques for multiple applications, including self-assembly, sensing, and imaging, are analyzed. The current review will be of particular interest to researchers interested in fluorescence-based biosensors, materials chemistry, nanomedicine, and related fields, as we focus on CNDs-based nano-biosensors for ccf-miRNAs detection applications in the medical field.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

Improved production of titanate nanotubes by hydrothermal method for adsorption of organic dyes

Background

Increasing the yield of nanomaterials using the same reactor size and fixing most of the reactants and conditions will greatly improve the production process by saving time, energy and efforts. Titanate nanotubes are mainly prepared by hydrothermal process, in which TiO2 powder reacts with NaOH at certain conditions to form the desired nanotubes. It was reported that it is a must to use high concentrations of NaOH (10 N) to enable the tubular form formation, and the amount of NaOH from the stoichiometry point of view is much higher than that of TiO2; this means excess amounts of NaOH are not used and washed off. This work was designed to improve the production yield by making use of this excess amount of NaOH.

Results

More than 60 g of sodium titanate nanotubes was prepared using simple hydrothermal method. The prepared nanotubes were characterized by X-ray powder diffraction, high-resolution transmission electron microscopy, Fourier-transform infrared spectroscopy and BET surface area analysis. The adsorption capacity of these nanotubes was tested against three commonly used dyes: methyl orange, crystal violet and thymol blue. The samples showed great affinity toward crystal violet and lower activity toward methyl orange and thymol blue, where they achieved more than 90% removal efficiency under different experimental conditions.

Conclusions

Sodium titanate nanotubes were prepared in large amounts using modified hydrothermal method. The obtained nanotubes efficiently removed crystal violet from water. This improved synthesis of titanate nanotubes will reduce the total cost of nanomaterials production, and subsequently the treatment process, since titanate nanotubes are used in adsorption and photocatalysis processes.

Improved Sugar Recovery from Orange Peel by Statistical Optimization of Thermo-Alkaline Pretreatment

Orange peel, which is a by-product of oranges, contains carbohydrates that can be converted into sugars and used in the fermentation process. In this study, the thermal alkaline pretreatment process was chosen because of its simplicity and lesser reaction time. In addition, the reaction factors were optimized using response surface methodology. The determined optimal conditions were as follows: 60.1 g/L orange peels loading, 3% KOH and 30 min. Under the optimal conditions, glucan content (GC) and enzymatic digestibility (ED) were found to be 32.8% and 87.8%, respectively. Enzymatic hydrolysis was performed with pretreated and non-pretreated orange peels using three types of enzyme complex (cellulase, cellobiase and xylanase). The minimum concentrations of enzyme complex required to obtain maximum ED were 30 FPU (filter paper unit), 15 CBU (cellobiase unit), and 30 XNU (xylanase unit) based on 1 g-biomass. Additionally, ED of the treated group was approximately 3.7-fold higher than that of the control group. In conclusion, the use of orange peel as a feedstock for biorefinery can be a strategic solution to reduce wastage of resources and produce sustainable bioproducts.

Using Neural Networks to Obtain Indirect Information about the State Variables in an Alcoholic Fermentation Process

This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg–Marquardt). The simulation results show that the feedback neural network outperformed the feed-forward neural network. The NN configuration is relatively flexible (with hidden layers and a number of nodes on each of them), but the number of input and output nodes depends on the fermentation process parameters. After laborious simulations, we determined that using pH and CO2 as inputs reduces the prediction errors of the NN. Thus, besides the most commonly used process parameters like fermentation temperature, time, the initial concentration of the substrate, the substrate concentration, and the biomass concentration, by adding pH and CO2, we obtained the optimum number of input nodes for the network. The optimal configuration in our case was obtained after 1500 iterations using a NN with one hidden layer and 12 neurons on it, seven neurons on the input layer, and one neuron as the output. If properly trained and validated, this model can be used in future research to accurately predict steady-state and dynamic alcoholic fermentation process behaviour and thereby improve process control performance.

Special Issue on “Chemical Process Design, Simulation and Optimization”

Since humanity has been able to transform materials, such as raw minerals, and produce food or beverages, a central question was the type of operation and how and where it should be performed [...]

Selective and simultaneous detection of cadmium, lead and copper by tapioca-derived carbon dot-modified electrode

The need for the sensing of environmental pollutants cannot be overemphasized in the twenty-first century. Herein, a sensor has been developed for the sensitive and selective detection of copper (Cu²⁺), lead (Pb²⁺) and cadmium (Cd²⁺) as major heavy metals polluting water environment. A screen-printed carbon electrode (SPCE) modified by fluorescent carbon dots (CDs) and gold nanoparticles (AuNPs) was successfully fabricated for sensing Cu²⁺, Pb²⁺ and Cd²⁺. Differential pulse voltammetry (DPV) and cyclic voltammetry (CV) were deployed for the analysis of ternary analytes. CV was set at a potential range of - 0.8 to + 0.2 V at a scan rate of 100 mV/s, and DPV at a potential range of - 0.8 to + 0.1 V, scan rate of 50 mV/s, pulse rate of 0.2 V and pulse width of 50 ms. DPV technique was applied through the modified electrode for sensitive and selective determination of Cu²⁺, Pb²⁺ and Cd²⁺ at a concentration range of 0.01 to 0.27 ppm for Cu²⁺, Pb²⁺ and Cd²⁺. Tolerance for the highest possible concentration of foreign substances such as Mg²⁺, K⁺, Na⁺, NO₃^-, and SO₄^2- was observed with a relative error less than ± 3%. The sensitivity of the modified electrode was at 0.17, 0.42 and 0.18 ppm for Cd²⁺, Pb²⁺ and Cu²⁺, respectively, while the limits of detection (LOD) achieved for cadmium, lead and copper were 0.0028, 0.0042 and 0.014 ppm, respectively. The quality of the modified electrode for sensing Cu²⁺, Pb²⁺ and Cd²⁺ at trace levels is in accordance with the World Health Organization (WHO) and Environmental Protection Agency (EPA) water regulation standard. The modified SPCE provides a cost-effective, dependable and stable means of detecting heavy metal ions (Cu²⁺, Pb²⁺ and Cd²⁺) in an aqueous solution. Graphical abstract .