Optimization Of Nanomaterials Research Articles

Titanium Carbide (Ti3C2Tx) MXene for Sequestration of Aquatic Pollutants.

The rapid expansion of industrialization has resulted in the release of multiple ecological contaminants in gaseous, liquid, and solid forms, which pose significant environmental risks to many different ecosystems. The efficient and cost-effective removal of these environmental pollutants has attracted global attention. This growing concern has prompted the synthesis and optimization of nanomaterials and their application as potential pollutant removal. In this context, MXene is considered an outstanding photocatalytic candidate due to its unique physicochemical and mechanical properties, which include high specific surface area, physiological compatibility, and robust electrodynamics. This review highlights recent advances in shaping titanium carbide (Ti3C2Tx) MXenes, emphasizing the importance of termination groups to boost photoactivity and product selectivity, with a primary focus on engineering aspects. First, a broad overview of Ti3C2Tx MXene is provided, delving into its catalytic properties and the formation of surface termination groups to establish a comprehensive understanding of its fundamental catalytic structure. Subsequently, the effects of engineering the morphology of Ti3C2Tx MXene into different structures, such as two-dimensional (2D) accordion-like forms, monolayers, hierarchies, quantum dots, and nanotubes. Finally, a concise overview of the removal of different environmental pollutants is presented, and the forthcoming challenges, along with their prospective outlooks, are delineated.

An artificial intelligence enabled chemical synthesis robot for exploration and optimization of nanomaterials.

We present an autonomous chemical synthesis robot for the exploration, discovery, and optimization of nanostructures driven by real-time spectroscopic feedback, theory, and machine learning algorithms that control the reaction conditions and allow the selective templating of reactions. This approach allows the transfer of materials as seeds between cycles of exploration, opening the search space like gene transfer in biology. The open-ended exploration of the seed-mediated multistep synthesis of gold nanoparticles (AuNPs) via in-line ultraviolet-visible characterization led to the discovery of five categories of nanoparticles by only performing ca. 1000 experiments in three hierarchically linked chemical spaces. The platform optimized nanostructures with desired optical properties by combining experiments and extinction spectrum simulations to achieve a yield of up to 95%. The synthetic procedure is outputted in a universal format using the chemical description language (χDL) with analytical data to produce a unique digital signature to enable the reproducibility of the synthesis.

Tuning the Hydration Acceleration Efficiency of Calcium Carbonate by Pre-Seeding with Calcium Silicate Hydrate.

Nanomaterials are promising candidates for refined performance optimization of cementitious materials. In recent years, numerous studies about the performance improvement of nanomaterials using polymers have been conducted, but the modification of cement-oriented nanomaterials with inorganic modifiers is seldom assessed. In this study, we explored the performance tuning and optimization of nanomaterials by inorganic modification. In this work, hydration acceleration efficiency of calcium carbonate (CaCO3, CC) was tuned via surface deposition with calcium silicate hydrate (C–S–H) nanogel through seeding. Multiple calcium carbonate–calcium silicate hydrate (CC–CSH) samples with varying degrees of surface modification were prepared via dosage control. According to characterizations, the degree of C–S–H modification on the CaCO3 surface has a maximum that is controlled by available surface space. Once the available space is depleted, excessive C–S–H turns into free form and causes adhesion between CC–CSH particles. The resultant CC–CSH samples in this work showed enhanced hydration acceleration efficiency that is tuned by the actual degree of C–S–H modification. Elevated C–S–H modification causes CC–CSH’s acceleration behavior to shift to enhanced early-age acceleration. According to mortar strength tests, CC–CSH with 5% C–S–H modification showed the most balanced performance, while CC–CSH with higher C–S–H modification showed faster early-age strength development at the cost of lower later-age strength. The inferior later-age strength of highly C–S–H-modified CC–CSH samples may be due to the coarsening of hydration products and stiffening of their network, as well as agglomeration caused by C–S–H adhesion. This study may offer a novel route for performance tuning of cement-oriented nanomaterials.

Synthesis and characterization of Ag2O, CoFe2O4, GO, and their ternary composite for antibacterial activity.

Currently, nanomaterials with exceptional antibacterial activity have become an emerging domain in research. The optimization of nanomaterials against infection causing agents is the next step in dealing with the present-day problem of antibiotics. In this research work, Ag2O, CoFe2O4, and Ag2O/CoFe2O4/rGO are prepared by chemical methods. Ag2O was prepared by co-precipitation method, while solvothermal technique was utilized for the synthesis of CoFe2O4. The ternary nanocomposite was synthesized by a simple in situ reduction using a two-step approach. The structural and morphological properties were studied by UV-Vis spectroscopy, X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (SEM), dynamic light scattering (DLS), and Fourier-transform infrared spectroscopy (FTIR). From the X-ray diffraction analysis, the crystallite size is found to be 14nm, 5nm, and 6nm for Ag2O, CoFe2O4, and Ag2O/CoFe2O4/rGO respectively. The synthesized nanomaterials were investigated for antibacterial activities against gram-positive strain Staphylococcus aureus (S. aureus) and gram-negative strain Escherichia coli (E. coli) using Agar well diffusion method. Ag2O and CoFe2O4 showed zones of inhibition (ZOI) of 13mm and 11mm against gram positive bacteria while 12mm against gram negative bacteria respectively, while ternary nanocomposite showed 14mm and 13mm of ZOI. The antibacterial activity of nanomaterials showed a gradual increment with an increase in the concentration of the materials. Ag2O, CoFe2O4, and Ag2O/CoFe2O4/rGO showed minimum inhibitory concentration (MIC) values of 4.5, 6.5, and 4.5μg/mL for S. aureus and 6.5, 7.2, and 4.8μg/mL for E. coli respectively. Minimum bactericidal concentrations were found to be same as the MIC values. Additionally, a time-kill curve analysis was performed and for ternary nanocomposite; the killing response was most effective as the complete killing was achieved at 3h of incubation at 3-MIC (9.75μg/mL). These results demonstrate that all the nanomaterials, as a kind of antibacterial material, have a great potential for a wide range of biomedical applications.

Nanotechnological Interventions in Agriculture.

Agriculture is an important sector that plays an important role in providing food to both humans and animals. In addition, this sector plays an important role in the world economy. Changes in climatic conditions and biotic and abiotic stresses cause significant damage to agricultural production around the world. Therefore, the development of sustainable agricultural techniques is becoming increasingly important keeping in view the growing population and its demands. Nanotechnology provides important tools to different industrial sectors, and nowadays, the use of nanotechnology is focused on achieving a sustainable agricultural system. Great attention has been given to the development and optimization of nanomaterials and their application in the agriculture sector to improve plant growth and development, plant health and protection and overall performance in terms of morphological and physiological activities. The present communication provides up-to-date information on nanotechnological interventions in the agriculture sector. The present review deals with nanoparticles, their types and the role of nanotechnology in plant growth, development, pathogen detection and crop protection, its role in the delivery of genetic material, plant growth regulators and agrochemicals and its role in genetic engineering. Moreover, the role of nanotechnology in stress management is also discussed. Our aim in this review is to aid researchers to learn quickly how to use plant nanotechnology for improving agricultural production.

Nanophotonics-enabled optical data storage in the age of machine learning

The growing data availability has accelerated the rise of data-driven and data-intensive technologies, such as machine learning, a subclass of artificial intelligence technology. Because the volume of data is expanding rapidly, new and improved data storage methods are necessary. Advances in nanophotonics have enabled the creation of disruptive optical data storage techniques and media capable of storing petabytes of data on a single optical disk. However, the needs for high-capacity, long-term, robust, and reliable optical data storage necessitate breakthrough advances in existing optical devices to enable future developments of artificial intelligence technology. Machine learning, which employs computer algorithms capable of self-improvement via experience and data usage, has proven an unrivaled tool to detect and forecast data patterns and decode and extract information from images. Furthermore, machine learning has been combined with physical and chemical sciences to build new fundamental principles and media. The integration of nanophotonics-enabled optical data storage with emerging machine learning technologies promises new methods for high-resolution, accurate, fast, and robust optical data writing and reading, as well as the discovery, design, and optimization of nanomaterials and nanostructures with new functionalities for next-generation nanophotonics-enabled optical data storage. In this Perspective, we review advances in nanophotonics-enabled optical data storage and discuss the role of machine learning in next-generation nanophotonics-enabled optical data storage.

Correlating Piezoelectric Polymer/Carbon Nanotubes Nanocomposite Strain Sensor with Reliability and Optimization Tools

Carbon nanotubes with polymers offers great advantages in improving material for both mechanical and electrical nanostructures. Design and fabrication have to consider that a local change in each compound accounts to the total change of physical properties in nanocomposite materials. This paper presents two parts of study. A model of strain nanosensor has been developed by using the polyvinylidne fluoride and trifluoroethylene P(VDF-TrFE) copolymer and carbon nanotubes in sandwich nanostructure [P(VDF-TrFE)/SWCNTs/ P(VDF-TrFE)] as a new application in nanotechnology domain. The experimental strain sensing was about 10-4. On the other hand, reliability-based optimization is assessed for an efficient tool to consider this nanosensors nanodevice. We put emphasis on the combination of physical modeling and reliability based design optimization of nanomaterials. After investigation, we could make suggestions such as how to improve the reliability of nanodevices and nanosystems, and how to reduce cost and economic rates.

Predicting the Reliability of Aligned Carbon Nanotube Bundles in Mechanical Structures

We report new experimental and theoretical study of mechanical property of aligned and nonaligned (entangled) single walled carbon nanotubes (SWCNTs), and their effect on nanostructures. Experimentally, the contact mode atomic force microscopy cantilever tip is used to measure the Young’s modulus of aligned and nonaligned SWCNTs. The measured Young's modulus of aligned SWCNT bundles ranged between 1100 GPa (1.1 TPa) and 1300 GPa (1.3 TPa) with a relative uncertainty of 5 % whereas that of the entangled SWCNT bundles ranged between 500 GPa and 700 GPa. Young’s modulus increase with aligned SWCNT bundles and then increase their performance in nanostructure comparing with entangled SWCNT bundles. We put emphasis on the combination of physical modeling and reliability based design optimization of nanomaterials. After investigation, we could make suggestions such as how to improve the reliability of nanodevices and nanosystems, and how to reduce cost and economic rates.

Development of combinatorial PLD-STM system for the quick nano-fabrication and evaluation

AbstractA combinatorial PLD-STM system has been developed for quick nano-fabrication and evaluation of epitaxial thin films and catalysts. Through a gate valve, a combinatorial nano-materials library fabricated in a PLD chamber can be transferred to a surface analysis chamber equipped with LEED and STM. The LEED pattern and atomically resolved STM image for systematically varied samples in the library are measured by locating one sample to another at the electron beam and STM probe position. In this way, we have quickly elucidated the initial growth process of SrO on SrTiO3(001) as well as surface structures of transition metal deposited TiO2 anatase. The combinatorial PLD-STM system has been verified to be very efficient technique for the exploration and optimization of nano-materials.