Magnetic nanoparticles for magnetic particle imaging (MPI): design and applications.

Recent advancements in medical imaging have brought forth various techniques such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound, each contributing to improved diagnostic capabilities. Most recently, magnetic particle imaging (MPI) has become a rapidly advancing imaging modality with profound implications for medical diagnostics and therapeutics. By directly detecting the magnetization response of magnetic tracers, MPI surpasses conventional imaging modalities in sensitivity and quantifiability, particularly in stem cell tracking applications. Herein, this comprehensive review explores the fundamental principles, instrumentation, magnetic nanoparticle tracer design, and applications of MPI, offering insights into recent advancements and future directions. Novel tracer designs, such as zinc-doped iron oxide nanoparticles (Zn-IONPs), exhibit enhanced performance, broadening MPI's utility. Spatial encoding strategies, scanning trajectories, and instrumentation innovations are elucidated, illuminating the technical underpinnings of MPI's evolution. Moreover, integrating machine learning and deep learning methods enhances MPI's image processing capabilities, paving the way for more efficient segmentation, quantification, and reconstruction. The potential of superferromagnetic iron oxide nanoparticle chains (SFMIOs) as new MPI tracers further advanced the imaging quality and expanded clinical applications, underscoring the promising future of this emerging imaging modality.

Integrated model of ozone mass transfer and oxidation kinetic: Construction, solving and analysis.

Ozone-based advanced oxidation process (O3-AOPs) is rapidly evolving, but the surge of emerging pollutants brings new challenges for ozone oxidation research. Herein, we proposed a state-of-the-art model for simultaneously analyzing both ozone mass transfer and oxidation kinetics during ozone oxidation of emerging organic contaminants. The numerical solution and graphical representations of the integrated model were utilized to analyze the dynamics of ozone and pollutant concentration. An in-depth analysis of the integrated model revealed that the reaction rate constants in this present study were higher than previously reported apparent reaction rate constants, and catalysts were not always necessary. Finally, we developed an installable mobile application (APP) that allowed the simulation of the dynamic process for ozone oxidizing organic pollutants in the laboratory, which offered theoretical support for the selection of experimental conditions. The results of model simulation not only provide scientific explanations for counter-intuitive experimental phenomena, but also optimized experimental conditions to enhance ozone utilization.

Ligand-Directed Shape Reconfiguration in Inorganic Materials.

Polymer elastomers with reversible shape-changing capability have led to significant development of artificial muscles, functional devices, and soft robots. By contrast, reversible shape transformation of inorganic nanoparticles is notoriously challenging due to their relatively rigid lattice structure. Here, the authors demonstrate the synthesis of shape-changing nanoparticles via an asymmetrical surface functionalization process. Various ligands are investigated, revealing the essential role of steric hindrance from the functional groups. By controlling the unbalanced structural hindrance on the surface, the as-prepared clay nanoparticles can transform their shape in a fast, facile, and reversible manner. In addition, such flexible morphology-controlled mechanism provides a platform for developing self-propelled shape-shifting nanocollectors. Owing to the ion-exchanging capability of clay, these self-propelled nanoswimmers (NS) are able to autonomously adsorb rare earth elements with ultralow concentration, indicating the feasibility of using naturally occurring materials for self-powered nanomachine.

Hybrid Data-Driven Discovery of High-Performance Silver Selenide-Based Thermoelectric Composites.

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m-1 K-2 , which is a 75% improvement from the baseline composite (nominal composition of Ag2 Se1 ). The success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

High-throughput printing of combinatorial materials from aerosols.

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces1. Whereas traditional combinatorial deposition methods can generate material libraries2,3, these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid-liquid or solid-solid phases4-6. We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

Pulsed Light Synthesis of High Entropy Nanocatalysts with Enhanced Catalytic Activity and Prolonged Stability for Oxygen Evolution Reaction.

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

Zwitterionic Graphene Quantum Dots to Stabilize Pickering Emulsions for Controlled-Release Applications.

Graphene quantum dots (GQDs) are a subset of the nanocarbon material family, which promise a wide spectrum of applications. Herein, we describe amphiphilic graphene quantum dots with zwitterionic features (ZGQDs), which are able to stabilize the oil/water interface. ZGQDs were fabricated by modifying GQDs with tertiary amine groups and alkyl groups. Moreover, the blocking and unblocking behavior of ZGQDs at the oil/water interface could be tuned by adjusting pH values in the aqueous phase. It would provide a flexible and adjustable method to manipulate interfacial properties of ZGQDs, which enabled a switchable molecular diffusion through a fluid-fluid interface. ZGQDs have shown well-controlled interfacial behavior under different pH conditions, indicating great potential for applications in controlled molecular diffusion based on nanoparticles demonstrated in this work.

Printing thermoelectric inks toward next-generation energy and thermal devices.

The ability of thermoelectric (TE) materials to convert thermal energy to electricity and vice versa highlights them as a promising candidate for sustainable energy applications. Despite considerable increases in the figure of merit zT of thermoelectric materials in the past two decades, there is still a prominent need to develop scalable synthesis and flexible manufacturing processes to convert high-efficiency materials into high-performance devices. Scalable printing techniques provide a versatile solution to not only fabricate both inorganic and organic TE materials with fine control over the compositions and microstructures, but also manufacture thermoelectric devices with optimized geometric and structural designs that lead to improved efficiency and system-level performances. In this review, we aim to provide a comprehensive framework of printing thermoelectric materials and devices by including recent breakthroughs and relevant discussions on TE materials chemistry, ink formulation, flexible or conformable device design, and processing strategies, with an emphasis on additive manufacturing techniques. In addition, we review recent innovations in the flexible, conformal, and stretchable device architectures and highlight state-of-the-art applications of these TE devices in energy harvesting and thermal management. Perspectives of emerging research opportunities and future directions are also discussed. While this review centers on thermoelectrics, the fundamental ink chemistry and printing processes possess the potential for applications to a broad range of energy, thermal and electronic devices.

Engineered two-dimensional nanomaterials: an emerging paradigm for water purification and monitoring.

Water scarcity has become an increasingly complex challenge with the growth of the global population, economic expansion, and climate change, highlighting the demand for advanced water treatment technologies that can provide clean water in a scalable, reliable, affordable, and sustainable manner. Recent advancements on 2D nanomaterials (2DM) open a new pathway for addressing the grand challenge of water treatment owing to their unique structures and superior properties. Emerging 2D nanostructures such as graphene, MoS2, MXene, h-BN, g-C3N4, and black phosphorus have demonstrated an unprecedented surface-to-volume ratio, which promises ultralow material use, ultrafast processing time, and ultrahigh treatment efficiency for water cleaning/monitoring. In this review, we provide a state-of-the-art account on engineered 2D nanomaterials and their applications in emerging water technologies, involving separation, adsorption, photocatalysis, and pollutant detection. The fundamental design strategies of 2DM are discussed with emphasis on their physicochemical properties, underlying mechanism and targeted applications in different scenarios. This review concludes with a perspective on the pressing challenges and emerging opportunities in 2DM-enabled wastewater treatment and water-quality monitoring. This review can help to elaborate the structure-processing-property relationship of 2DM, and aims to guide the design of next-generation 2DM systems for the development of selective, multifunctional, programmable, and even intelligent water technologies. The global significance of clean water for future generations sheds new light and much inspiration in this rising field to enhance the efficiency and affordability of water treatment and secure a global water supply in a growing portion of the world.

Atmospheric Pressure and Ambient Temperature Plasma Jet Sintering of Aerosol Jet Printed Silver Nanoparticles.

Atmospheric pressure nonthermal plasmas hold great promise for applications in environmental control, energy conversion, and material processing. Even at room temperature, nonthermal plasmas produce energetic and reactive species that can initiate surface modifications at a plasma-surface interface, including thin-film nanoparticle assemblies, in a nondestructive and effective way. Here, we present the plasma-activated sintering of aerosol jet printed silver thin films on substrates ranging from glass to delicate materials including blotting paper, fruits, and flexible plastic. We characterize the microstructural evolutions and electrical properties of printed films along with the electrical, thermal, and optical properties of an argon plasma jet. We demonstrate an electrical conductivity as high as 1.4 × 106 S/m for printed films sintered under atmospheric conditions in which the surface temperature stays below 50 °C. These results highlight a future direction where additive manufacturing of electronic devices can be achieved on flexible and low-melting-point materials under ambient conditions without requiring additional thermal processing by utilizing nonthermal plasmas.

Amphiphilicity-adaptable graphene quantum dots to stabilize pH-responsive pickering emulsions at a very low concentration.

HYPOTHESIS: Stimuli-responsive Pickering emulsions have attracted considerable interest due to their widespread potential applications. Especially pH-responsive behavior could be easily implemented. In this work, we reported a pH-responsive Pickering emulsion based on amphiphilic graphene quantum dots at a low concentration which shows a great potential from the environmental and economic perspective. The stimuli responsive properties would make the smart Pickering emulsifiers recyclable and reusable. EXPERIMENTS: The amphiphilic-adaptable graphene quantum dots functionalized by alkyl groups (C-GQDs) were synthesized by a facile one-step pyrolysis method. The pH-responsive emulsion performances were investigated, and the mechanism of pH-responsive of C-GQDs was studied by dynamic light scattering. FINDINGS: The amphiphilicity of C-GQDs could be acquired controllably and effectively by this facile one-step pyrolysis method, which are able to stabilize Pickering emulsion at a very low concentration (0.001%). The amphiphilicity of C-GQDs are capable of changing in response to environmental stimuli. When the pH value of aqueous solution adjusts to 2, these C-GQDs aggregate in contrast to their stability in neutral condition due to the alternation of surface charges. The pH-responsive aggregation/ dispersion behavior of C-GQDs allows us to tune the interactions between oil-in-water emulsion droplets without introduction of destabilization agents. This will provide huge economic benefits in industrial applications in the future.

Colloidal Nanosurfactants for 3D Conformal Printing of 2D van der Waals Materials.

Printing techniques using nanomaterials have emerged as a versatile tool for fast prototyping and potentially large-scale manufacturing of functional devices. Surfactants play a significant role in many printing processes due to their ability to reduce interfacial tension between ink solvents and nanoparticles and thus improve ink colloidal stability. Here, a colloidal graphene quantum dot (GQD)-based nanosurfactant is reported to stabilize various types of 2D materials in aqueous inks. In particular, a graphene ink with superior colloidal stability is demonstrated by GQD nanosurfactants via the π-π stacking interaction, leading to the printing of multiple high-resolution patterns on various substrates using a single printing pass. It is found that nanosurfactants can significantly improve the mechanical stability of the printed graphene films compared with those of conventional molecular surfactant, as evidenced by 100 taping, 100 scratching, and 1000 bending cycles. Additionally, the printed composite film exhibits improved photoconductance using UV light with 400 nm wavelength, arising from excitation across the nanosurfactant bandgap. Taking advantage of the 3D conformal aerosol jet printing technique, a series of UV sensors of heterogeneous structures are directly printed on 2D flat and 3D spherical substrates, demonstrating the potential of manufacturing geometrically versatile devices based on nanosurfactant inks.

Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning.

The ability of self-propelled nanoparticles to convert environmental energy into locomotion has led to several nanomotor prototypes that are promising in numerous real-world applications. However, the vast variety of nanoparticle designs prevents rapid identification of the optimal composition for a given application. In this study, we applied machine learning methods to predict the self-propulsion speed and water-cleaning efficiency of micro/nanomotors (MNMs), where the quality of machine learning predictions was evaluated based on the statistical values. The average absolute error of predicted velocity and predicted efficiency are determined to be as low as 0.10 and 0.12, respectively. In addition, by comparing the prediction results based on 13 features using four different machine learning algorithms, we are able to identify several key features that are important to effectively environmental decontamination, such as particle size, catalyst type, and aspect ratio. Following the guidelines deduced from these models, a high-efficiency Pt-coated nanomotor was designed and synthesized, of which the experimental results were compared with the machine learning predictions, showing an accurate prediction with a less than 15% of prediction error. In the range of our theoretical/experimental conditions, we showed that a gradient boosting algorithm is the most promising method for predicting the environmental decontamination behavior of MNMs, a machine-learning algorithm rarely used in the nanomaterial field in current practice.

Growth of Colloidal Nanoplate Liquid Crystals Using Temperature Gradients.

Controlling colloidal self-assemblies using external forces is essential to develop modern electro-optical and biomedical devices. Importantly, shape anisotropic colloids can provide optical properties such as birefringence. Here we demonstrate that external temperature gradients can be effective in controlling nematic liquid crystalline (LC) order in suspensions of plate-like colloids also known as nanoplates. Nanoplates, in an isotropic suspension, wherein their orientations are random, could be effectively moved using a temperature gradient environment causing a phase transition to LC nematic phase. Such controllably formed nematic phase featured large nematic monodomains and enabled topologically more stable structures that were evident from the absence of hedgehog-type defects which are typically found in nematics formed spontaneously via nucleation and growth mechanism in a sufficiently high concentration suspension of nanoplates. Due to their high surface area-to-volume ratio and excellent thermophoretic properties, nanoplates can prove to be ideal candidates for transport of biomolecules through temperature varying environments.

Iridescence in nematics: Photonic liquid crystals of nanoplates in absence of long-range periodicity.

Photonic materials with positionally ordered structure can interact strongly with light to produce brilliant structural colors. Here, we found that the nonperiodic nematic liquid crystals of nanoplates can also display structural color with only significant orientational order. Owing to the loose stacking of the nematic nanodiscs, such colloidal dispersion is able to reflect a broad-spectrum wavelength, of which the reflection color can be further enhanced by adding carbon nanoparticles to reduce background scattering. Upon the addition of electrolytes, such vivid colors of nematic dispersion can be fine-tuned via electrostatic forces. Furthermore, we took advantage of the fluidity of the nematic structure to create a variety of colorful arts. It was expected that the concept of implanting nematic features in photonic structure of lyotropic nanoparticles may open opportunities for developing advanced photonic materials for display, sensing, and art applications.

Facile one-step microwave-assisted modification of kaolinite and performance evaluation of pickering emulsion stabilization for oil recovery application.

A facile one-step microwave-assisted method was proposed for kaolinite intercalation and grafting. The structure, morphology, composition, and size distribution of kaolinite sheets were investigated using various methods, including X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and thermogravimetric (TG) analysis. The potential application of the modified kaolinite as an oil/water emulsion stabilizer was studied. The results verified that intact kaolinite sheets were obtained. The dodecane/water emulsion stabilized by the modified kaolinite remained stable for more than 60 days. The effective performance suggests that the effectiveness of the proposed kaolinite modification method may be useful for Pickering emulsion stabilization in oil recovery applications.

Natural Halloysites-Based Janus Platelet Surfactants for the Formation of Pickering Emulsion and Enhanced Oil Recovery.

Janus colloidal surfactants with opposing wettabilities are receiving attention for their practical application in industry. Combining the advantages of molecular surfactants and particle-stabilized Pickering emulsions, Janus colloidal surfactants generate remarkably stable emulsions. Here we report a straightforward and cost-efficient strategy to develop Janus nanoplate surfactants (JNPS) from an aluminosilicate nanoclay, halloysite, by stepwise surface modification, including an innovative selective surface modification step. Such colloidal surfactants are found to be able to stabilize Pickering emulsions of different oil/water systems. The microstructural characterization of solidified polystyrene emulsions indicates that the emulsion interface is evenly covered by JNPS. The phase behaviors of water/oil emulsion generated by these novel platelet surfactants were also investigated. Furthermore, we demonstrate the application of JNPS for enhanced oil recovery with a microfluidic flooding test, showing a dramatic increase of oil recovery ratio. This research provides important insights for the design and synthesis of two-dimensional Janus colloidal surfactants, which could be utilized in biomedical, food and mining industries, especially for circumstances where high salinity and high temperature are involved.

Assembly and Chiral Memory Effects of Dynamic Macroscopic Supramolecular Helices.

Macroscopic enantiomerically pure helical supramolecular fibers are bottom-up assembled in aqueous media from a chiral π-electron donor template and an achiral π-electron acceptor. The helices can be assembled to the sub-millimeter scale with controlled handedness. These dynamic supramolecular architectures allow for a quantitative exchange of the chiral donor template with achiral analogues. During this process, a chiral memory effect was observed, affording enantiomerically pure helices composed entirely of achiral components.

Electrostatic-Driven Dynamic Jamming of 2D Nanoparticles at Interfaces for Controlled Molecular Diffusion.

Dynamically engineering the interfacial interaction of nanoparticles has emerged as a new approach for bottom-up fabrication of smart systems to tailor molecular diffusion and controlled release. Janus zwitterionic nanoplates are reported that can be switched between a locked and unlocked state at interfaces upon changing surface charge, allowing manipulation of interfacial properties in a fast, flexible, and switchable manner. Combining experimental and modeling studies, an unambiguous correlation is established among the electrostatic energy, the interface geometry, and the interfacial jamming states. As a proof-of-concept, the well-controlled interfacial jamming of nanoplates enabled the switchable molecular diffusion through liquid-liquid interfaces, confirming the feasibility of using nanoparticle-based surfactants for advanced controlled release.

Hierarchical, Self-Healing and Superhydrophobic Zirconium Phosphate Hybrid Membrane Based on the Interfacial Crystal Growth of Lyotropic Two-Dimensional Nanoplatelets.

We demonstrate a facile route to in situ growth of lyotropic zirconium phosphate (ZrP) nanoplates on textiles via an interfacial crystal growing process. The as-prepared hybrid membrane shows a hierarchical architecture of textile fibers (porous platform for fluid transport), ZrP nanoplatelets (layered scaffolds for chemical barriers), and octadecylamine (organic species for superhydrophobic functionalization). Interestingly, such a hybrid membrane is able to separate the oily wastewater with a high separation efficiency of 99.9%, even at in harsh environments. After being chemically etched, the hybrid membrane is able to restore its hydrophobicity autonomously and repeatedly, owing to the hierarchical structure that enables facile loading of healing agent. We anticipate that the concept of implanting superhydrophobic self-healing features in anisotropic structure of lyotropic nanoparticles will open up new opportunities for developing advanced multifunctional materials for wastewater treatment, fuel purification, and oil spill mitigation.