Affinity Distribution Research Articles

Impact of PCLNPG Nanopolymeric Additive on the Surface and Structural Properties of PPSU Ultrafiltration Membranes for Enhanced Protein Rejection

This research explored the use of a partially cross-linked graft copolymer (PCLNPG) as an innovative nanopolymer pore-forming agent to enhance polyphenylsulfone (PPSU) membranes for protein separation applications. The study systematically examined the impact of incorporating PCLNPG at varying concentrations on the morphological and surface properties of PPSU membranes. A thorough characterization of the resulting PPSU-PCLNPG membranes was performed, focusing on changes in morphology, water affinity, porosity, pore size, and pore size distribution. The experimental findings demonstrated that the use of PCLNPG led to a significantly more porous structure, as confirmed by SEM analysis, with notable increases in porosity and pore size (nearly double). Additionally, the hydrophilicity of the PPSU membrane was remarkably enhanced. Performance evaluations revealed a substantial improvement in pure water flux, with the flux nearly tripling. The BSA retention was directly correlated with the concentration of the PCLNPG pore former for a loading range of 0.25–0.75 wt.%. The incorporation of PCLNPG also reduced the membrane fouling propensity by reducing both cake layer resistance (Rc) and pore plugging resistance (Rp). These results underscore the potential of PCLNPG-PPSU membranes for wastewater reclamation and nutrient recovery applications.

Optimization of garnet-type solid-state lithium batteries via synergistic integration of an advanced composite interface for elevated performance

Solid-state batteries (SSBs) represent a pivotal avenue of development owing to their superior energy density and enhanced safety profile. However, the widespread utilization about SSBs confronts challenges such as inadequate interfacial connectivity resulting in high resistance, dendrite formation, and volumetric fluctuations in the lithium metal anode during plating and stripping. In this study, we introduce an innovative and remarkably efficient approach, leveraging the transformative potential of TiN-induced conversion. This method yields a lithium-ion-conductive TiN material concurrently addressing pre-existing porosity. The LiTiN| LLZTO| LiTiN symmetric cell is particularly noteworthy for its remarkable long-term cycle stability, which exceeds 1000 h at 0.2 mA cm−2, and its remarkable critical current density of 1.4 mA cm−2 at 25 °C. By subjecting TiN, the formation of the Li-Ti-N phase is induced, thereby establishing an additional Li3N-conductive layer that significantly enhances battery performance. Of paramount significance is the validation of the exceptional attributes of the composite through the deployment of LiFePO4 (LFP) full cells. In this configuration, the LFP coupled full cell manifests a remarkable discharge rate capacity of about 147 mAh g−1 at 1C, along with a noteworthy discharge capacity retention rate of 90 % even following 1000 charge and discharge cycles. These outcomes underscore the material’s robust lithium affinity and uniform lithium-ion distribution, which together mitigate dendrite growth and enhance the cycle stability of lithium-metal batteries.

Revealing the Biophysics of Lamina-Associated Domain Formation by Integrating Theoretical Modeling and High-Resolution Imaging.

The interactions between chromatin and the nuclear lamina orchestrate cell type-specific gene activity by forming lamina-associated domains (LADs) which preserve cellular characteristics through gene repression. However, unlike the interactions between chromatin segments, the strength of chromatin-lamina interactions and their dependence on cellular environment are not well understood. Here, we develop a theory to predict the size and shape of peripheral heterochromatin domains by considering the energetics of chromatin-chromatin interactions, the affinity between chromatin and the nuclear lamina and the kinetics of methylation and acetylation9in human mesenchymal stem cells (hMSCs). Through the analysis of super-resolution images of peripheral heterochromatin domains using this theoretical framework, we determine the nuclear lamina-wide distribution of chromatin-lamina affinities. We find that the extracted affinity is highly spatially heterogeneous and shows a bimodal distribution, indicating regions along the lamina with strong chromatin binding and those exhibiting vanishing chromatin affinity interspersed with some regions exhibiting a relatively diminished chromatin interactions, in line with the presence of structures such as nuclear pores. Exploring the role of environmental cues on peripheral chromatin, we find that LAD thickness increases when hMSCs are cultured on a softer substrate, in correlation with contractility-dependent translocation of histone deacetylase 3 (HDAC3) from the cytosol to the nucleus. In soft microenvironments, chromatin becomes sequestered at the nuclear lamina, likely due to the interactions of HDAC3 with the chromatin anchoring protein LAP2 β ,increasing chromatin-lamina affinity, as well as elevated levels of the intranuclear histone methylation. Our findings are further corroborated by pharmacological interventions that inhibit contractility, as well as by manipulating methylation levels using epigenetic drugs. Notably, in the context of tendinosis, a chronic condition characterized by collagen degeneration, we observed a similar increase in the thickness of peripheral chromatin akin to that of cells cultured on soft substrates consistent with theoretical predictions. Our findings underscore the pivotal role of the microenvironment in shaping genome organization and highlight its relevance in pathological conditions.

ABCD of IA: A multi-scale agent-based model of T cell activation in inflammatory arthritis.

Biomaterial-based agents have been demonstrated to regulate the function of immune cells in models of autoimmunity. However, the complexity of the kinetics of immune cell activation can present a challenge in optimizing the dose and frequency of administration. Here, we report a model of autoreactive T cell activation, which are key drivers in autoimmune inflammatory joint disease. The model is termed a multi-scale Agent-Based, Cell-Driven model of Inflammatory Arthritis (ABCD of IA). Using kinetic rate equations and statistical theory, ABCD of IA simulated the activation and presentation of autoantigens by dendritic cells, interactions with cognate T cells and subsequent T cell proliferation in the lymph node and IA-affected joints. The results, validated with in vivo data from the T cell driven SKG mouse model, showed that T cell proliferation strongly correlated with the T cell receptor (TCR) affinity distribution (TCR-ad), with a clear transition state from homeostasis to an inflammatory state. T cell proliferation was strongly dependent on the amount of antigen in antigenic stimulus event (ASE) at low concentrations. On the other hand, inflammation driven by Th17-inducing cytokine mediated T cell phenotype commitment was influenced by the initial level of Th17-inducing cytokines independent of the amount of arthritogenic antigen. The introduction of inhibitory artificial antigen presenting cells (iaAPCs), which locally suppress T cell activation, reduced T cell proliferation in a dose-dependent manner. The findings in this work set up a framework based on theory and modeling to simulate personalized therapeutic strategies in IA.

Assessing the Affinity Spectrum of the Antigen-Specific B Cell Repertoire via ImmunoSpot®.

The affinity distribution of the antigen-specific memory Bcell (Bmem) repertoire in the body is a critical variable that defines an individual's ability to rapidly generate high-affinity protective antibody specificities. Detailed measurement of antibody affinity so far has largely been confined to studies of monoclonal antibodies (mAbs) and are laborious since each individual mAb needs to be evaluated in isolation. Here, we introduce two variants of the Bcell ImmunoSpot® assay that are suitable for simultaneously assessing the affinity distribution of hundreds of individual B cells within a test sample at single-cell resolution using relatively little labor and with high-throughput capacity. First, we experimentally validated that both ImmunoSpot® assay variants are suitable for establishing functional affinity hierarchies using Bcell hybridoma lines as model antibody-secreting cells (ASC), each producing mAb with known affinity for a defined antigen. We then leveraged both ImmunoSpot® variants for characterizing the affinity distribution of SARS-CoV-2 Spike-specific ASC in PBMC following COVID-19 mRNA vaccination. Such ImmunoSpot® assays promise to offer tremendous value for future Bcell immune monitoring efforts, owing to their ease of implementation, applicability to essentially any antigenic system, economy of PBMC utilization, high-throughput capacity, and suitability for regulated testing.

Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays.

Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the antibodies that B cells secrete, inherently result in a broad range of spot sizes and intensities. The diversity of secretory footprint morphologies reflects the polyclonal nature of the antigen-specific B cell repertoire, with individual antibody-secreting B cells in the test sample differing in their affinity for the antigen, fine epitope specificity, and activation/secretion kinetics. To account for these heterogeneous spot morphologies, and to eliminate the need for setting up subjective counting parameters well-by-well, CTL introduces here its cutting-edge deep learning-based IntelliCount™ algorithm within the ImmunoSpot® Studio Software Suite, which integrates CTL's proprietary deep neural network. Here, we report detailed analyses of spots with a broad range of morphologies that were challenging to analyze using standard parameter-based counting approaches. IntelliCount™, especially in conjunction with high dynamic range (HDR) imaging, permits the extraction of accurate, high-content information of such spots, as required for assessing the affinity distribution of an antigen-specific memory B-cell repertoire ex vivo. IntelliCount™ also extends the range in which the number of antibody-secreting B cells plated and spots detected follow a linear function; that is, in which the frequencies of antigen-specific B cells can be accurately established. Introducing high-content analysis of secretory footprints in B-cell ELISPOT/FluoroSpot assays, therefore, fundamentally enhances the depth in which an antigen-specific B-cell repertoire can be studied using freshlyisolated or cryopreserved primary cell material, such as peripheral blood mononuclear cells.

Monitoring Memory B Cells by Next-Generation ImmunoSpot® Provides Insights into Humoral Immunity that Measurements of Circulating Antibodies Do Not Reveal.

Memory B cells (Bmem) provide the second wall of adaptive humoral host defense upon specific antigen rechallenge when the first wall, consisting of preformed antibodies originating from a preceding antibody response, fails. This is the case, as recently experienced with SARS-CoV-2 infections and previously with seasonal influenza, when levels of neutralizing antibodies decline or when variant viruses arise that evade such. While in these instances, reinfection can occur, in both scenarios, the rapid engagement of preexisting Bmem into the recall response can still confer immune protection. Bmem are known to play a critical role in host defense, yet their assessment has not become part of the standard immune monitoring repertoire. Here we describe a new generation of Bcell ELISPOT/FluoroSpot (collectively ImmunoSpot®) approaches suited to dissect, at single-cell resolution, the Bmem repertoire ex vivo, revealing its immunoglobulin class/subclass utilization, and its affinity distribution for the original, and for variant viruses/antigens. Because such comprehensive Bcell ImmunoSpot® tests can be performed with minimal cell material, are scalable, and robust, they promise to be well-suited for routine immune monitoring.

TiO2‐Induced Conversion Reaction Eliminating Li2CO3 and Pores/Voids Inside Garnet Electrolyte for Lithium–Metal Batteries

AbstractGarnet Li7La3Zr2O12 (LLZO) is regarded as a promising solid electrolyte due to its high Li+ conductivity and excellent chemical stability, but suffers from grain boundary resistance and porous structure which restrict its practical applications in lithium–metal batteries. Herein, a novel and highly efficient TiO2‐induced conversion strategy is proposed to generate Li ion‐conductive Li0.5La0.5TiO3, which can simultaneously eliminate the pre‐existing pores/voids and contamination Li2CO3. The Li/LLZTO‐5TiO2/Li symmetric cell exhibits a high critical current density of 1.1 mA cm−2 at 25°C, and the long‐term lithium cycling stability of over 1500 h at 0.1 mA cm−2. More importantly, the excellent performance of LLZTO‐5TiO2 electrolyte is verified by LiCoO2/LiFePO4 coupled full cells. For example, The LiCoO2 coupled full cell exhibits a significant discharge rate capacity of 108 mAh g−1 at 0.1 C, and a discharge capacity retention rate of 91.23% even after 150 cycles of charge and discharge. COMSOL Multiphysics and density functional theory calculation reveal that LLZTO‐5TiO2 electrolyte has a strong lithium affinity and uniform Li ions distribution, which can improve the cycle stability of Li–metal batteries by preventing dendrite growth.

Vector Affinity and Receptor Distribution Define Tissue-Specific Targeting in an Engineered AAV Capsid.

Unbiased in vivo selections of diverse capsid libraries can yield engineered capsids that overcome gene therapy delivery challenges like traversing the blood-brain barrier (BBB), but little is known about the parameters of capsid-receptor interactions that govern their improved activity. This hampers broader efforts in precision capsid engineering and is a practical impediment to ensuring the translatability of capsid properties between preclinical animal models and human clinical trials. In this work, we utilize the adeno-associated virus (AAV)-PHP.B-Ly6a model system to better understand the targeted delivery and BBB penetration properties of AAV vectors. This model offers a defined capsid-receptor pair that can be used to systematically define relationships between target receptor affinity and in vivo activity of engineered AAV vectors. Here, we report a high-throughput method for quantifying capsid-receptor affinity and demonstrate that direct binding assays can be used to organize a vector library into families with varied affinity for their target receptor. Our data indicate that efficient central nervous system transduction requires high levels of target receptor expression at the BBB, but it is not a requirement for receptor expression to be limited to the target tissue. We observed that enhanced receptor affinity leads to reduced transduction of off-target tissues but can negatively impact on-target cellular transduction and penetration of endothelial barriers. Together, this work provides a set of tools for defining vector-receptor affinities and demonstrates how receptor expression and affinity interact to impact the performance of engineered AAV vectors in targeting the central nervous system. IMPORTANCE Novel methods for measuring adeno-associated virus (AAV)-receptor affinities, especially in relation to vector performance in vivo, would be useful to capsid engineers as they develop AAV vectors for gene therapy applications and characterize their interactions with native or engineered receptors. Here, we use the AAV-PHP.B-Ly6a model system to assess the impact of receptor affinity on the systemic delivery and endothelial penetration properties of AAV-PHP.B vectors. We discuss how receptor affinity analysis can be used to isolate vectors with optimized properties, improve the interpretation of library selections, and ultimately translate vector activities between preclinical animal models and humans.

Assembly and recognition mechanisms of glycosylated PEGylated polyallylamine phosphate nanoparticles: A fluorescence correlation spectroscopy and small angle X-ray scattering study

HypothesisModification of polyallylamine hydrochloride (PAH) with heterobifunctional low molecular weight polyethylene glycol (PEG) (600 and 1395 Da), and subsequent attachment of mannose, glucose, or lactose sugars to PEG, can lead to formation of polyamine phosphate nanoparticles (PANs) with lectin binding affinity and narrow size distribution. ExperimentsSize, polydispersity, and internal structure of glycosylated PEGylated PANs were characterized by transmission electron microscopy (TEM), dynamic light scattering (DLS) and small angle X-ray scattering (SAXS). Fluorescence correlation spectroscopy (FCS) was used to study the association of labelled glycol-PEGylated PANs. The number of polymer chains forming the nanoparticles was determined from the changes in amplitude of the cross-correlation function of the polymers after formation of the nanoparticles. SAXS and fluorescence cross-correlation spectroscopy were used to investigate the interaction of PANs with lectins: concanavalin A with mannose modified PANs, and jacalin with lactose modified ones. FindingsGlyco-PEGylated PANs are highly monodispersed, with diameters of a few tens of nanometers and low charge, and a structure corresponding to spheres with Gaussian chains. FCS shows that the PANs are single chain nanoparticles or formed by two polymer chains. Concanavalin A and jacalin show specific interactions for the glyco-PEGylated PANs with higher affinity than bovine serum albumin.

Constitutive modelling of fibre networks with stretch distributions, Part II: Alternative representation, affine distribution and anisotropy

In this paper, the concept for modelling materials with fibre network microstructures introduced in Part I of this series is reconsidered. At first, an alternative representation of the theory is provided that entails advantages in terms of numerical implementation. Next, the new constitutive approach is applied to affine networks, whose fibre stretches are distributed according to the affine distribution. Despite the tremendously widespread use of this model, it seems that the general form of the corresponding distribution has remained largely unexplored to date. The thus obtained reformulation of the affine full network model provides deep insight into this concept, and may help overcoming well-known numerical problems with the associated spherical integration, e.g. when highly non-linear or piece-wise defined fibre laws are used. The latter case is typical for applications in biomechanics, where fibres are frequently assumed to have negligible compressive resistance. While the developments of our theory thus far had focused on isotropic networks, we here showcase for the affine case how the anisotropy caused by non-uniform directional distributions of the fibres can be incorporated in the novel approach. Finally, it is shown that several earlier approaches to model networks of affinely deforming fibres or polymer chains result as special cases of our theory.

A Complex Affine Distribution Power Flow Considering the Power Correlation of Distributed Photovoltaic Generations

As the development of distributed photovoltaic (PV), the power flow distribution and the voltage level of the distribution network change dramatically, which increases the difficulty and complexity of the distribution network regulation. In this paper, a complex affine distribution power flow considering the power correlation of distributed photovoltaic generations is proposed, which improves the accuracy and effectiveness of power flow calculation of the distribution network. Firstly, the k-means clustering algorithm is used to divide the distributed photovoltaic into several clusters, and the complex affine model of distributed generations (PVs) and energy storage system (ESS) is established. The forward-backward sweep power flow based on the complex affine arithmetic is used to solve the problem. Compared with other algorithms, the completeness and accuracy of the proposed algorithm are verified. Two different scenarios are formed by establishing the complex affine power model of the energy storage element before and after accessing ESS. By comparison, the effect of energy storage on the reduction of distributed PV fluctuations is verified.

Effective Approach by Computational Chemical Prediction and Experimental Verification to Elucidate SEI Formation Mechanism in LiPF6-, LiFSI-, and LiBF4-Containing Electrolyte Solutions

Solvation structures of ethylene carbonate-based electrolyte solutions containing 1 mol/L LiPF6, LiN(SO2F)2 (LiFSI), or LiBF4 are experimentally determined, and their electron affinity and lowest unoccupied molecular orbital (LUMO) distribution are calculated by density functional theory (DFT). The stability of the electrolyte solutions against reduction can be evaluated using electron affinity of the solvates, and the formation mechanism of the solid electrolyte interphase (SEI) can be predicted by their LUMO distributions. The calculation results suggest that 1 mol/L LiPF6 and LiFSI electrolyte solutions should form SEI consisting of carbonate and carboxylate which derives from solvent decomposition and LiF originating from anion decomposition. These predictions are verified experimentally by scanning electron microscopy–energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy measurements. On the other hand, intriguingly, the reductive decomposition of 1 mol/L LiBF4 electrolyte solution does not simply proceed as theoretically predicted, and the subsequent reactions of SEI need to be considered: further decomposition of the organic SEI and formation of inorganic particles containing lithium, fluoride, oxygen, and boron. These results are consistent with an increase in the resistance of SEI and interfacial lithium ion transfer at the graphite negative electrode. Thus, a combination of DFT prediction and experimental analysis is an effective approach to reveal SEI formation mechanisms and can be utilized as a versatile approach to develop new solvents, electrolyte salts, and additives and to design electrolyte solutions with an appropriate concentration.

Intrinsic protein disorder uncouples affinity from binding specificity.

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins often function by molecular recognition, in which they undergo induced folding. Based on prior generalizations, the idea prevails in the IDP field that due to the entropic penalty of induced folding, the major functional advantage associated with this binding mode is “uncoupling” specificity from binding strength. Nevertheless, both weaker binding and high specificity of IDPs/IDRs rest on limited experimental observations, making these assumptions more speculations than evidence‐supported facts. The issue is also complicated by the rather vague concept of specificity that lacks an exact measure, such as the K d for binding strength. We addressed these issues by creating and analyzing a comprehensive dataset of well‐characterized ID/globular protein complexes, for which both the atomic structure of the complex and free energy (ΔG, K d) of interaction is known. Through this analysis, we provide evidence that the affinity distributions of IDP/globular and globular/globular complexes show different trends, whereas specificity does not connote to weaker binding strength of IDPs/IDRs. Furthermore, protein disorder extends the spectrum in the direction of very weak interactions, which may have important regulatory consequences and suggest that, in a biological sense, strict correlation of specificity and binding strength are uncoupled by structural disorder.

The influence of poly(allylamine hydrochloride) hydrogel crosslinking density on its thermal and phosphate binding properties

Sevelamer hydrochloride (SH) or Renagel® is an effective phosphate binder prescribed to prevent the absorption of phosphate in end stage renal disease (ESRD) patients. The relationship between SH structure and binding capacity and affinity is very important and can be used in characterising the sensitivity of the hydrogel to binding conditions. Thus, a series of hydrogels were prepared by varying the amount of crosslinker, whilst the other hydrogel components were kept constant. Variation of this parameter influenced the hydrogel structure as shown by swelling data, differential scanning calorimetry and solid state nuclear magnetic resonance spectroscopy. The hydrogels’ physical characteristics were found to correlate with the number of phosphate binding sites and affinity obtained from the Langmuir–Freundlich Isotherm (L–FI) and affinity distribution spectra (AD). The hydrogels formed using lower amounts of crosslinker showed a slight increase in binding capacity but with lower affinity. However, the influence of the pH of the binding media on the binding parameters of sevelamer hydrochloride was significant. This is the first report on the use of AD spectra generated from L-FI binding parameters in hydrogels, which demonstrates the sensitivity of the affinity and binding site numbers to changes in hydrogel physical properties and the pH of the binding media.

89Zr-ImmunoPET Shows Therapeutic Efficacy of Anti-CD20-IFNα Fusion Protein in a Murine B-cell Lymphoma Model.

Antibody-mediated tumor delivery of cytokines can overcome limitations of systemic administration (toxicity, short half-lives). Previous work showed improved antitumor potency of anti-CD20-IFNα fusion proteins in preclinical mouse models of B-cell lymphoma. Although tumor targeting is mediated by the antibody part of the fusion protein, the cytokine component might strongly influence biodistribution and pharmacokinetics, as a result of its affinity, size, valency, and receptor distribution. Here, we used immunoPET to study the in vivo biodistribution and tumor targeting of the anti-CD20 rituximab-murine IFNα1 fusion protein (Rit-mIFNα) and compared it with the parental mAb (rituximab, Rit). Rit-mIFNα and Rit were radiolabeled with zirconium-89 (89Zr, t1/2 78.4 hours) and injected into C3H mice bearing syngeneic B-cell lymphomas (38C13-hCD20). Dynamic [(2 hours post injection (p.i.)] and static (4, 24, and 72 hours) PET scans were acquired. Ex vivo biodistribution was performed after the final scan. Both 89Zr-Rit-mIFNα and 89Zr-Rit specifically target hCD20-expressing B-cell lymphoma in vivo. 89Zr-Rit-mIFNα showed specific uptake in tumors (7.6 ± 1.0 %ID/g at 75 hours p.i.), which was significantly lower than 89Zr-Rit (38.4 ± 9.9 %ID/g, P < 0.0001). ImmunoPET studies also revealed differences in the biodistribution, 89Zr-Rit-mIFNα showed rapid blood clearance and high accumulation in the liver compared with 89Zr-Rit. Importantly, immunoPET clearly revealed a therapeutic effect of the single 89Zr-Rit-mIFNα dose, resulting in smaller tumors and fewer lymph node metastases compared with mice receiving 89Zr-Rit. Mice receiving 89Zr-Rit-mIFNα had enlarged spleens, suggesting that systemic immune activation contributes to therapeutic efficacy in addition to the direct antitumoral activity of IFNα. In conclusion, immunoPET allows the noninvasive tracking and quantification of the antibody-cytokine fusion protein and helps understand the in vivo behavior and therapeutic efficacy.

Proton binding to humic nano particles: electrostatic interaction and the condensation approximation.

Proton binding to "carboxylic" and "phenolic" sites of humic nano particles (HNPs) is determined by the total proton affinity that is due to a specific and an electrostatic affinity. Both affinities are accounted for in the bi-modal Langmuir-Freundlich (bi-LF)-equation extended with a Boltzmann factor that includes the electrostatic site potential(s), y. For y → 0 the equation reduces to the bi-LF Master Curve (MC). Commonly, an electrical double layer model is used to obtain y, e.g., the bi-LF-Donnan-Vapp (monocomponent NICA-Donnan) model and bi-LF-soft-particle-Poison-Boltzmann-Theory (SPBT). A new method is presented that combines the "condensation approximation" (CA) with the MC concept (CA-MC). With the CA, the proton binding curve and MC can be transformed in, respectively, the total and specific affinity distribution. The difference at a given charge density provides the electrostatic affinity and CA-potentials vs. charge density. The MC can be obtained theoretically or by using the convention that the electrostatic interaction is negligible at 1 M salt concentration. For five HNPs CA-potentials corresponding with the bi-LF-SPBT are compared with results of the bi-LF-Donnan-Vapp model using the MC(SPBT). The bi-LF-Donnan-Vapp model fails when the Debye length > hydrated particle radius. The CA-MC(1M) method does not require characteristics of the HNPs. Combination of the bi-LF-eq. with the CA-MC(1 M) method gives the bi-LF-CA-MC(1 M) model. The CA-MC(1 M) differs from the MC(SPBT); therefore, resulting parameters can only be compared when the same method is used.

A new magnetic composite with potential application in boron adsorption: Development, characterization, and removal tests

In this work, a new magnetic composite, with good performance in the adsorption of boron from aqueous solutions, is proposed. The composite was prepared from CoFe2O4 and MgO precursors, which were produced by the sol-gel method using orange juice residues. X-ray diffraction, scanning electron microscopy, infrared spectroscopy, 57Fe Mössbauer spectroscopy, and magnetization measurements have indicated that the ferrimagnetic CoFe2O4 nanocrystalline phase is immersed in the MgO matrix. The magnetic composite was applied to boron compounds removal from synthetic effluents (with boron concentrations up to 20 mg L−1), showing up to 92% removal capacity. After the boron adsorption process on the MgO surface, X-ray diffraction, scanning electron microscopy, and infrared spectroscopy results have shown the formation of crystalline Mg(OH)2 (with needle-like structures), and 57Fe Mössbauer spectroscopy has indicated that the fraction of Fe+3 ions in the nanograin surfaces was changed in comparison with the pristine adsorbents. Three possible boron adsorption mechanisms are suggested: adsorption at the Mg(OH)2 crystallite surface, adsorption through the formation of Fe–O–B bonds, and adsorption by an amorphous Mg(OH)2 gel. The pseudo-first order model was successfully used to fit the kinetic adsorption curves, whereas the Freundlich model has described the isotherms, thus indicating a heterogeneous distribution of adsorption heat and affinities. The composite was found to adsorb about 6% more boron than pure MgO and can be recoverable with a permanent magnet.

Solvent-assisted encapsulation of boron nitride in polystyrene for high-efficient heat dissipation

The actual application of polymer-based composites is obstructed by low thermal conductivity (TC) due to the weaker interfacial affinity and unordered distribution of filler. Herein, we report a breakthrough of heat transfer enabled by sulfonated polystyrene nanospheres-coated hydroxylated boron nitride (BN–OH/SPS) microrods with highly ordered structures via inorganic acid-assisted assembly and following a hot press process. Benefiting from the ordered structure, accumulated heat can rapidly dissipate from the continuous BN–BN thermal conduction pathway in the PS matrix. The in-plane TC of BN-OH/SPS composite with 10 wt% BN reaches up to 8.512 W/mK, which is nearly 45 times larger than that of neat PS. Additionally, BN-OH/SPS composite exhibits excellent mechanical properties. Remarkably, this appealing strategy can be used as a general fabrication method to overcome the challenge of low TC for polymer-based composites.

A note on the distributions in quantum mechanical systems

In this paper, we study the distributions and the affine distributions of the quantum mechanical system. Also, we discuss the controllability of the quantum mechanical system with the related question concerning the minimum time needed to steer a quantum system from a unitary evolution U(0) = I of the unitary propagator to a desired unitary propagator Uf . Furthermore, the paper introduces a description of a k⊕p sub-Finsler manifold with its geodesics, which equivalents to the problem of driving the quantum mechanical system from an arbitrary initial state U(0) = I to the target state Uf , some illustrative examples are included. We prove that the Lie group G on a Finsler symmetric manifold G/K can be decomposed into KAK.