Machine Learning-Guided Synthesis of Room-Temperature Phosphorescent Carbon Dots for Enhanced Phosphorescence Lifetime and Information Encryption

Room-temperature phosphorescent (RTP) carbon dots (CDs) have been increasingly used in many applications, including anticounterfeiting and information encryption. However, synthesizing RTP CDs with a specific average lifetime of phosphorescence remains a formidable challenge. A breakthrough is needed in formulating the synthesis process to find a suitable synthesis formulation to produce CDs with an optimal lifetime of phosphorescence. Machine learning (ML) has recently been successfully used for guiding material synthesis and offering insight into the prediction, optimization, and acceleration of the CDs’ synthesis process. A regression ML model on microwave-assisted CD synthesis is established to reveal the relationship between various synthesis parameters and enhance the average lifetime of phosphorescence of CDs in the solid-state phase. RTP CDs exhibit a blue emission when irradiating with UV and a green emission afterglow after the UV is turned off. These green emissions can last for 7 s, are easily observed by the naked eye, and show an ultralong phosphorescence lifetime of up to 1.6 s. Moreover, designed and guided by ML, this afterglow feature was explored to achieve multilevel anticounterfeiting and information encryption to encrypt and decrypt secret information in dynamic time-dependent displays. Our results provide a strategy for synthesizing RTP CDs with a specific lifetime and extending their application scope to high-level information security

Machine Learning-Guided Synthesis of Room-Temperature Phosphorescent Carbon Dots for Enhanced Phosphorescence Lifetime and Information Encryption

Room-temperature phosphorescent (RTP) carbon dots (CDs) have been increasingly used in many applications, including anticounterfeiting and information encryption. However, synthesizing RTP CDs with a specific average lifetime of phosphorescence remains a formidable challenge. A breakthrough is needed in formulating the synthesis process to find a suitable synthesis formulation to produce CDs with an optimal lifetime of phosphorescence. Machine learning (ML) has recently been successfully used for guiding material synthesis and offering insight into the prediction, optimization, and acceleration of the CDs’ synthesis process. A regression ML model on microwave-assisted CD synthesis is established to reveal the relationship between various synthesis parameters and enhance the average lifetime of phosphorescence of CDs in the solid-state phase. RTP CDs exhibit a blue emission when irradiating with UV and a green emission afterglow after the UV is turned off. These green emissions can last for 7 s, are easily observed by the naked eye, and show an ultralong phosphorescence lifetime of up to 1.6 s. Moreover, designed and guided by ML, this afterglow feature was explored to achieve multilevel anticounterfeiting and information encryption to encrypt and decrypt secret information in dynamic time-dependent displays. Our results provide a strategy for synthesizing RTP CDs with a specific lifetime and extending their application scope to high-level information security

Synthesis of Submicron-Sized Spherical Silica-Coated Iron Nickel Particles with Adjustable Shell Thickness via Swirler Connector-Assisted Spray Pyrolysis

Silica-coated iron nickel (FeNi@SiO2) particles have attracted significant attention because of their potential applications in electronic devices. In this work, submicron-sized spherical FeNi@SiO2 particles with precisely controllable shell thickness were successfully synthesized for the first time using a swirler connector-assisted spray pyrolysis system, comprising a preheater, specific connector, and main heater. The results indicated that the thickness of the SiO2 shell can be tuned from 3 to 23 nm by adjusting the parameter conditions (i.e., preheater temperature, SiO2 supplied amount). Furthermore, our fabrication method consistently yielded a high coating ratio of more than 94%, indicating an excellent quality of the synthesized particles. Especially, to gain an in-depth understanding of the particle formation process of the FeNi@SiO2 particles, a plausible mechanism was also investigated. These findings highlight the importance of controlling the preheater and SiO2 supplied amount to obtain FeNi@SiO2 particles with desirable morphology and high coating quality

Controllable Synthesis of Porous and Hollow Nanostructured Catalyst Particles and Their Soot Oxidation

The introduction of macroporous structures into three-way catalysts (TWCs) through polymer template-assisted spray drying has attracted attention because of its enhanced gas diffusion and catalytic performance. However, the surface charge effect of polymeric template components has not been investigated to control the structure of the TWC particles during synthesis. Thus, this study investigated the effect of template surface charges on the self-assembly behavior of TWC nanoparticles (NPs) during drying. The self-assembly of TWC NPs and polymer particles with different charges produced a hollow structure, whereas using the same charges generated a porous one. Consequently, the mechanism of particle self-assembly during drying and final structure particle formation is proposed in this study. Here, porous TWC particles demonstrated a faster oxidation of soot particles than that of hollow-structured particles. This occurred as a result of the larger contact area between the catalyst surface and the solid reactant. Our findings propose a fundamental self-assembly mechanism for the formation of different TWC structures, thereby enhancing soot oxidation performance using macroporous structures

One-Step Aerosol Synthesis of SiO₂‑Coated FeNi Particles by Using Swirler Connector-Assisted Spray Pyrolysis

Silica-coated soft magnetic particles are essential for some powder magnetic cores consisting of primary (coarse particles) and secondary (fine particles) soft magnetic particles in the advancement of electric devices. Herein, we report the first investigation on the direct synthesis of submicron-sized silica-coated FeNi (FeNi@SiO2) particles as the secondary particle using a connector-assisted spray pyrolysis route. Provided by computational fluid dynamics calculation in applying different connector types, i.e., T-shaped and swirler, we found that the mixing performance between FeNi and HMDSO vapor in the swirler connector played an important role in resulting heterogeneous nucleation, which is crucial for obtaining the higher coating ratio (CR) and fewer undesired nanoparticles than that of the T-shaped connector. The as-prepared submicron-sized FeNi@SiO2 particles (353 nm) with the highest CR (95.9%) demonstrated a remarkable DC bias characteristic (Isat) and eddy current loss values on a powder magnetic core, promising the practical application in manufacturing soft magnetic components

Controlling the Magnetic Responsiveness of Cellulose Nanofiber Particles Embedded with Iron Oxide Nanoparticles

2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanofiber (TOCN) particles, an innovative biobased material derived from wood biomass, have garnered significant interest, particularly in the biomedical field, for their distinctive properties as biocompatible particle adsorbents. However, their microscopic size complicates their separation in liquid media, thereby impeding their application in various domains. In this study, superparamagnetic magnetite nanoparticles (NPs), specifically iron oxide Fe3O4 NPs with an average size of 15 nm, were used to enhance the collection efficiency of TOCN-Fe3O4 composite particles synthesized through spray drying. These composite particles exhibited a remarkable ζ-potential (approximately −50 mV), indicating their high stability in water, as well as impressive magnetization properties (up to 47 emu/g), and rapid magnetic responsiveness within 60 s in water (3 wt % Fe3O4 to TOCN, 1 T magnet). Furthermore, the influence of Fe3O4 NP concentrations on the measurement of the speed of magnetic separation was quantitatively discussed. Additionally, the binding affinity of the synthesized particles for proteins was assessed on a streptavidin–biotin binding system, offering crucial insights into their binding capabilities with specific proteins and underscoring their significant potential as functionalized biomedical materials