Hofmeister Effects Shine in Nanoscience.

Hofmeister effects play a crucial role in nanoscience by affecting the physicochemical and biochemical processes. Thus far, numerous wonderful applications from various aspects of nanoscience have been developed based on the mechanism of Hofmeister effects, such as hydrogel/aerogel engineering, battery design, nanosynthesis, nanomotors, ion sensors, supramolecular chemistry, colloid and interface science, nanomedicine, and transport behaviors, etc. In this review, for the first time, the progress of applying Hofmeister effects is systematically introduced and summarized in nanoscience. It is aimed to provide a comprehensive guideline for future researchers to design more useful Hofmeister effects-based nanosystems.

Diagnostics and theranostics of central nervous system diseases based on aggregation-induced emission luminogens.

Central nervous system (CNS) diseases include Alzheimer's disease (AD), Parkinson's disease (PD), brain tumors, strokes, and other important diseases that are harmful and fatal to human beings. CNS diseases have the characteristics of high fatality rates, difficult diagnosis, and costly treatment. The diagnosis and treatment of CNS diseases by molecular imaging are usually limited by the depth of tissue penetration and the blood-brain barrier (BBB). Therefore, it is still a huge challenge to distinguish between the lesion and the surrounding parenchymal boundary with high sensitivity and specificity. Compared with traditional fluorophores with aggregation-caused quenching effect, luminogens with aggregation-induced emission (AIE) characteristics have strong near-infrared deep penetration, large Stokes shift, excellent biocompatibility, light stability, and desirable BBB permeability. In view of this, developing novel AIE-based materials for diagnostics and theranostics of CNS diseases is promising and of great significance. Herein, we highlight the recent research progress in this field with a special focus on near-infrared imaging and AIE nanorobots for CNS diseases. The design principle of AIE probes is discussed in detail, and the outlook is presented as well.

Nanopore Sensing Technique for Studying the Hofmeister Effect.

The nanopore sensing technique is an emerging method of detecting single molecules, and extensive research has gone into various fields, including nanopore sequencing and other applications of single-molecule studies. Recently, several researchers have explored the specific ion effects in nanopore channels, enabling a unique understanding of the Hofmeister effect at the single-molecule level. Herein, the recent advances of using nanopore sensing techniques are reviewed to study the Hofmeister effect and the physicochemical mechanism of this process is attempted. The challenges and goals are also discussed for the future in this field.

On the Sensing and Calibration of Residual Stresses Measurements in the Incremental Hole-Drilling Method.

The current study presents three calibration approaches for the hole-drilling method (HDM). A total of 72 finite element models and 144 simulations were established to calibrate the measurements of the strain sensors. The first approach assumed the stresses acted on the boundaries of the drilled hole and thus analyzed the surrounding displacements field. The second analysis considered the loads on the outer surfaces of the specimen while measuring the strains' differences between the model with and without the drilled hole. The third approach was more comprehensive as it considered the mechanical and thermal effects of the drilling operations. The proposed approaches were applied to two different materials (AISI 1045 and CFRP). The steel specimens were machined using a CNC lathe while the composite laminates were manufactured using the robotic fiber placement (RFP) process. Subsequently, the residual stresses (RSs) were measured using the HDM. The obtained data were compared with X-ray diffraction measurements for validation. The results showed better estimation of the RSs when utilizing the third approach and clear underestimation of the stresses using the second approach. A divergence in RSs values between the three approaches was also detected when measuring the stresses in the internal layers of the composite laminates.

Graphene-Based Electrode Materials for Neural Activity Detection.

The neural electrode technique is a powerful tool for monitoring and regulating neural activity, which has a wide range of applications in basic neuroscience and the treatment of neurological diseases. Constructing a high-performance electrode-nerve interface is required for the long-term stable detection of neural signals by electrodes. However, conventional neural electrodes are mainly fabricated from rigid materials that do not match the mechanical properties of soft neural tissues, thus limiting the high-quality recording of neuroelectric signals. Meanwhile, graphene-based nanomaterials can form stable electrode-nerve interfaces due to their high conductivity, excellent flexibility, and biocompatibility. In this literature review, we describe various graphene-based electrodes and their potential application in neural activity detection. We also discuss the biological safety of graphene neural electrodes, related challenges, and their prospects.

Enhancing Solid State LiDAR Mapping with a 2D Spinning LiDAR in Urban Scenario SLAM on Ground Vehicles.

Solid-State LiDAR (SSL) takes an increasing share of the LiDAR market. Compared with traditional spinning LiDAR, SSLs are more compact, energy-efficient and cost-effective. Generally, the current study of SSL mapping is limited to adapting existing SLAM algorithms to an SSL sensor. However, compared with spinning LiDARs, SSLs are different in terms of their irregular scan patterns and limited FOV. Directly applying existing SLAM approaches on them often increase the instability of a mapping process. This study proposes a systematic design, which consists of a dual-LiDAR mapping system and a three DOF interpolated six DOF odometry. For dual-LiDAR mapping, this work uses a 2D LiDAR to enhance a 3D SSL performance on a ground vehicle platform. The proposed system takes a 2D LiDAR to preprocess the scanning field into a number of feature sections according to the curvatures on the 2D fraction. Subsequently, this section information is passed to 3D SSL for direction feature selection. Additionally, this work proposes an odometry interpolation method which uses both LiDARs to generate two separated odometries. The proposed odometry interpolation method selectively determines the appropriate odometry information to update the system state under challenging conditions. Experiments are conducted in different scenarios. The results proves that the proposed approach is able to utilise 12 times more corner features from the environment than the comparied method, thus results in a demonstrable improvement in its absolute position error.

In†Situ Thermal Atomization To Convert Supported Nickel Nanoparticles into Surface-Bound Nickel Single-Atom Catalysts.

The arrangement of the active sites on the surface of a catalysts can reduce the problem of mass transfer and enhance the atom economy. Herein, supported Ni metal nanoparticles can be transformed to thermal stable Ni single atoms, mostly located on the surface of the support. Assisted by N-doped carbon with abundant defects, this synthetic process not only transform the nanoparticles to single atoms, but also creates numerous pores to facilitate the contact of dissolved CO2 and single Ni sites. The proposed mechanism is that the Ni nanoparticles could break surface C-C bonds drill into the carbon matrix, leaving pores on the surface. When Ni nanoparticles are exposed to N-doped carbon, the strong coordination splits Ni atoms from Ni NPs. The Ni atoms are stabilized within the surface of carbon substrate. The continuous loss of atomic Ni species from the NPs would finally result in atomization of Ni NPs. CO2 electroreduction testing shows that the surface enriched with Ni single atoms delivers better performance than supported Ni NPs and other similar catalysts.

Intracellular Peptide Self-Assembly: A Biomimetic Approach for in Situ Nanodrug Preparation.

Most nanodrugs are preprepared by encapsulating or loading the drugs with nanocarriers (e.g., dendrimers, liposomes, micelles, and polymeric nanoparticles). However, besides the low bioavailability and fast excretion of the nanodrugs in vivo, nanocarriers often exhibit in vitro and in vivo cytotoxicity, oxidative stress, and inflammation. Self-assembly is a ubiquitous process in biology where it plays important roles and underlies the formation of a wide variety of complex biological structures. Inspired by some cellular nanostructures (e.g., actin filaments, microtubules, vesicles, and micelles) in biological systems which are formed via molecular self-assembly, in recent decades, scientists have utilized self-assembly of oligomeric peptide under specific physiological or pathological environments to in situ construct nanodrugs for lesion-targeted therapies. On one hand, peptide-based nanodrugs always have some excellent intrinsic chemical (specificity, intrinsic bioactivity, biodegradability) and physical (small size, conformation) properties. On the other hand, stimuli-regulated intracellular self-assembly of nanodrugs is quite an efficient way to accumulate the drugs in lesion location and can realize an in situ slow release of the drugs. In this review article, we provided an overview on recent design principles for intracellular peptide self-assembly and illustrate how these principles have been applied for the in situ preparation of nanodrugs at the lesion location. In the last part, we list some challenges underlying this strategy and their possible solutions. Moreover, we envision the future possible theranostic applications of this strategy.