Bin Li

Bio: Bin Li is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Ionic liquid & Ionic bonding. The author has an hindex of 13, co-authored 43 publications receiving 563 citations. Previous affiliations of Bin Li include Chinese Academy of Sciences & Jilin University.

Microstructural and Dynamical Heterogeneities in Ionic Liquids.

Abstract: Ionic liquids (ILs) are a special category of molten salts solely composed of ions with varied molecular symmetry and charge delocalization. The versatility in combining varied cation-anion moieties and in functionalizing ions with different atoms and molecular groups contributes to their peculiar interactions ranging from weak isotropic associations to strong, specific, and anisotropic forces. A delicate interplay among intra- and intermolecular interactions facilitates the formation of heterogeneous microstructures and liquid morphologies, which further contributes to their striking dynamical properties. Microstructural and dynamical heterogeneities of ILs lead to their multifaceted properties described by an inherent designer feature, which makes ILs important candidates for novel solvents, electrolytes, and functional materials in academia and industrial applications. Due to a massive number of combinations of ion pairs with ion species having distinct molecular structures and IL mixtures containing varied molecular solvents, a comprehensive understanding of their hierarchical structural and dynamical quantities is of great significance for a rational selection of ILs with appropriate properties and thereafter advancing their macroscopic functionalities in applications. In this review, we comprehensively trace recent advances in understanding delicate interplay of strong and weak interactions that underpin their complex phase behaviors with a particular emphasis on understanding heterogeneous microstructures and dynamics of ILs in bulk liquids, in mixtures with cosolvents, and in interfacial regions.

Chiral gold nanoparticles enantioselectively rescue memory deficits in a mouse model of Alzheimer's disease.

Abstract: Preventing aggregation of amyloid beta (Aβ) peptides is a promising strategy for the treatment of Alzheimer’s disease (AD), and gold nanoparticles have previously been explored as a potential anti-Aβ therapeutics. Here we design and prepare 3.3 nm L- and D-glutathione stabilized gold nanoparticles (denoted as L3.3 and D3.3, respectively). Both chiral nanoparticles are able to inhibit aggregation of Aβ42 and cross the blood-brain barrier (BBB) following intravenous administration without noticeable toxicity. D3.3 possesses a larger binding affinity to Aβ42 and higher brain biodistribution compared with its enantiomer L3.3, giving rise to stronger inhibition of Aβ42 fibrillation and better rescue of behavioral impairments in AD model mice. This conjugation of a small nanoparticle with chiral recognition moiety provides a potential therapeutic approach for AD. Nanoparticles are being explored as a potential method to target Aβ aggregation in Alzheimer’s disease. Here, the authors develop gold nanoparticles that were capped with chiral L or D-glutathione which has been shown to improve BBB permeability and demonstrate their ability to improve cognitive function in a mouse model of AD.

Enhanced Transport of Shape and Rigidity-Tuned α-Lactalbumin Nanotubes across Intestinal Mucus and Cellular Barriers.

Abstract: Mucus is a viscoelastic biological hydrogel that protects the epithelial surface from penetration by most nanoparticles, which limits the efficiency of oral drug delivery. Pursuing highly efficient...

Dissipative particle dynamics simulation study on the mechanisms of self-assembly of large multimolecular micelles from amphiphilic dendritic multiarm copolymers

Abstract: Dendritic multiarm copolymers, including dendrimer multiarm copolymers and hyperbranched multiarm copolymers, have shown great potential to be excellent precursors in self-assembly, and many impressive supramolecular structures have been prepared through the solution self-assembly of them. However, the corresponding theoretical studies on the self-assembly mechanism have been greatly lagging behind. Herein, we report the micellization behaviors of amphiphilic dendritic multiarm copolymers with a hydrophobic dendritic core and many hydrophilic arms by dissipative particle dynamics simulations. Both the self-assembly mechanisms and the dynamic self-assembly processes for the formation of unimolecular micelles, microphase-separated small micelles, and large multimolecular micelles have been disclosed through the simulations. Most importantly, the work has proved the large multimolecular micelles are a kind of multimicelle aggregate (MMA) with two formation mechanisms. One is called the unimolecular micelle aggregate (UMA) mechanism, which describes the formation of large multimolecular micelles from direct aggregation of unimolecular micelles; the other is called the small micelle aggregate (SMA) mechanism, which shows that the dendritic multiarm copolymers first self-assemble into small micelles and then the small micelles further aggregate into large multimolecular micelles. In addition, the microphase separation model of the dendritic multiarm copolymers as well as the effects on the formations of UMAs and SMAs are also discussed. These simulation results agree well with experimental observations, and have extended the understanding of the micellization process of dendritic multiarm copolymers.

Glycyrrhizic Acid Nanoparticles as Antiviral and Anti-inflammatory Agents for COVID-19 Treatment.

Abstract: COVID-19 has been diffusely pandemic around the world, characterized by massive morbidity and mortality. One of the remarkable threats associated with mortality may be the uncontrolled inflammatory processes, which were induced by SARS-CoV-2 in infected patients. As there are no specific drugs, exploiting safe and effective treatment strategies is an instant requirement to dwindle viral damage and relieve extreme inflammation simultaneously. Here, highly biocompatible glycyrrhizic acid (GA) nanoparticles (GANPs) were synthesized based on GA. In vitro investigations revealed that GANPs inhibit the proliferation of the murine coronavirus MHV-A59 and reduce proinflammatory cytokine production caused by MHV-A59 or the N protein of SARS-CoV-2. In an MHV-A59-induced surrogate mouse model of COVID-19, GANPs specifically target areas with severe inflammation, such as the lungs, which appeared to improve the accumulation of GANPs and enhance the effectiveness of the treatment. Further, GANPs also exert antiviral and anti-inflammatory effects, relieving organ damage and conferring a significant survival advantage to infected mice. Such a novel therapeutic agent can be readily manufactured into feasible treatment for COVID-19.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Combination of small molecule prodrug and nanodrug delivery: amphiphilic drug-drug conjugate for cancer therapy.

Abstract: All drugs for cancer therapy face several transportation barriers on their tortuous journey to the action sites. To overcome these barriers, an effective drug delivery system for cancer therapy is imperative. Here, we develop a drug self-delivery system for cancer therapy, in which anticancer drugs can be delivered by themselves without any carriers. To demonstrate this unique approach, an amphiphilic drug–drug conjugate (ADDC) has been synthesized from the hydrophilic anticancer drug irinotecan (Ir) and the hydrophobic anticancer drug chlorambucil (Cb) via a hydrolyzable ester linkage. The amphiphilic Ir–Cb conjugate self-assembles into nanoparticles in water and exhibits longer blood retention half-life compared with the free drugs, which facilitates the accumulation of drugs in tumor tissues and promotes their cellular uptake. A benefit of the nanoscale characteristics of the Ir–Cb ADDC nanoparticles is that the multidrug resistance (MDR) of tumor cells can be overcome efficiently. After cellular inter...

Multiscale Studies on Ionic Liquids

Abstract: Ionic liquids (ILs) offer a wide range of promising applications because of their much enhanced properties. However, further development of such materials depends on the fundamental understanding of their hierarchical structures and behaviors, which requires multiscale strategies to provide coupling among various length scales. In this review, we first introduce the structures and properties of these typical ILs. Then, we introduce the multiscale modeling methods that have been applied to the ILs, covering from molecular scale (QM/MM), to mesoscale (CG, DPD), to macroscale (CFD for unit scale and thermodynamics COSMO-RS model and environmental assessment GD method for process scale). In the following section, we discuss in some detail their applications to the four scales of ILs, including molecular scale structures, mesoscale aggregates and dynamics, and unit scale reactor design and process design and optimization of typical IL applications. Finally, we address the concluding remarks of multiscale strat...

Ionic Liquids In Synthesis

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