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1. Influence of protein charge patches on the structure of protein–polyelectrolyte complexes

   https://doi.org/10.1039/C8SM01535J  

   Samanta, Rituparna ; Ganesan, Venkat ( November 2018 , Soft Matter)

   We employ a combination of the single chain in mean field simulation approach with the solution of Poisson's equation to study the influence of charge heterogeneities on the structure of protein–polyelectrolyte complexes. By adopting a coarse-grained model of representing proteins as charged nanoparticles, we studied the influence of the pattern of charge heterogeneities, net charge, ratio of positive to negative charges on the patches, and the volume fraction of the particles on the structural and aggregation characteristics of proteins in polyelectrolyte solutions. Our results demonstrate that the pattern of charge heterogeneities can exert a significant influence on the resulting characteristics of the aggregates, in some cases leading to a transformation from polymer-bridged complexes into direct particle aggregates driven by the attraction between oppositely charged patches. 

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2. Modulation of Nanoparticle Diffusion by Surface Ligand Length and Charge: Analysis with Molecular Dynamics Simulations

   https://doi.org/10.1021/acs.jpcb.1c01189  

   Cui, Anthony Y. ; Cui, Qiang ( January 2021 , The Journal of Physical Chemistry B)

   null (Ed.)

   To help better interpret experimental measurement of nanoparticle size, it is important to understand how their diffusion depends on the physical and chemical features of surface ligands. In this study, explicit solvent molecular dynamics simulations are used to probe the effect of ligand charge and flexibility on the diffusion of small gold nanoparticles. The results suggest that despite a high bare charge (+18 e), cationic nanoparticles studied here have reduced diffusion constants compared to a hydrophobic gold nanoparticle by merely a modest amount. Increasing the ligand length by 10 CH2 units also has a limited impact on the diffusion constant. For the three particles studied here, the difference between estimated hydrodynamic radius and radius of gyration is on the order of one solvent layer (3–5 Å), confirming that the significant discrepancies found in the size of similar nanoparticles by recent transmission electron microscopy and dynamic light scattering measurements were due to aggregation under solution conditions. The limited impact of electrostatic friction on the diffusion of highly charged nanoparticles is found to be due to the strong anticorrelation between electrostatic and van der Waals forces between nanoparticle and environment, supporting the generality of recent observation for proteins by Matyushov and co-workers. Including the first shell of solvent molecules as part of the diffusing particle has a minor impact on the total force autocorrelation function but reduces the disparity in relaxation time between the total force and its electrostatic and van der Waals components. 

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3. Salt bridges govern the structural heterogeneity of heme protein interactions and porphyrin networks: microperoxidase-11

   https://doi.org/10.1039/d0ra04956e  

   Porter, J. ; Dit Fouque, K. Jeanne ; Miksovska, J. ; Fernandez-Lima, F. ( September 2020 , RSC Advances)

   null (Ed.)

   In this work, a proteolytic digest of cytochrome c (microperoxidase 11, MP-11) was used as a model to study the structural aspects of heme protein interactions and porphyrin networks. The MP-11 structural heterogeneity was studied as a function of the starting pH ( e.g. , pH 3.1–6.1) and concentration ( e.g. , 1–50 μM) conditions and adduct coordination. Trapped ion mobility spectrometry coupled to mass spectrometry (TIMS-MS) showed the MP-11 structural dependence of the charge state distribution and molecular ion forms with the starting pH conditions. The singly charged ( e.g. , [M] + , [M − 2H + NH 4 ] + , [M − H + Na] + and [M − H + K] + ) and doubly charged ( e.g. , [M + H] 2+ , [M − H + NH 4 ] 2+ , [M + Na] 2+ and [M + K] 2+ ) molecular ion forms were observed for all solvent conditions, although the structural heterogeneity ( e.g. , number of mobility bands) significantly varied with the pH value and ion form. The MP-11 dimer formation as a model for heme-protein protein interactions showed that dimer formation is favored toward more neutral pH and favored when assisted by salt bridges ( e.g. , NH 4 + , Na + and K + vs. H + ). Inspection of the dimer mobility profiles (2+ and 3+ charge states) showed a high degree of structural heterogeneity as a function of the solution pH and ion form; the observation of common mobility bands suggest that the different salt bridges can stabilize similar structural motifs. In addition, the salt bridge influence on the MP-11 dimer formations was measured using collision induced dissociation and showed a strong dependence with the type of salt bridge ( i.e. , a CE 50 of 10.0, 11.5, 11.8 and 13.0 eV was observed for [2M + H] 3+ , [2M − H + NH 4 ] 3+ , [2M + Na] 3+ and [2M + K] 3+ , respectively). Measurements of the dimer equilibrium constant showed that the salt bridge interactions increase the binding strength of the dimeric species. 

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4. Nonlinear electrophoretic velocity of a spherical colloidal particle

   https://doi.org/10.1017/jfm.2023.537  

   Cobos, Richard ; Khair, Aditya S. ( August 2023 , Journal of Fluid Mechanics)

   Electrophoresis is the motion of a charged colloidal particle in an electrolyte under an applied electric field. The electrophoretic velocity of a spherical particle depends on the dimensionless electric field strength$\beta =a^*e^*E_\infty ^*/k_B^*T^*$, defined as the ratio of the product of the applied electric field magnitude$E_\infty ^*$and particle radius$a^*$, to the thermal voltage$k_B^*T^*/e^*$, where$k_B^*$is Boltzmann's constant,$T^*$is the absolute temperature, and$e^*$is the charge on a proton. In this paper, we develop a spectral element algorithm to compute the electrophoretic velocity of a spherical, rigid, dielectric particle, of fixed dimensionless surface charge density$\sigma$over a wide range of$\beta$. Here,$\sigma =(e^*a^*/\epsilon ^*k_B^*T^*)\sigma ^*$, where$\sigma ^*$is the dimensional surface charge density, and$\epsilon ^*$is the permittivity of the electrolyte. For moderately charged particles ($\sigma ={O}(1)$), the electrophoretic velocity is linear in$\beta$when$\beta \ll 1$, and its dependence on the ratio of the Debye length ($1/\kappa ^*$) to particle radius (denoted by$\delta =1/(\kappa ^*a^*)$) agrees with Henry's formula. As$\beta$increases, the nonlinear contribution to the electrophoretic velocity becomes prominent, and the onset of this behaviour is$\delta$-dependent. For$\beta \gg 1$, the electrophoretic velocity again becomes linear in field strength, approaching the Hückel limit of electrophoresis in a dielectric medium, for all$\delta$. For highly charged particles ($\sigma \gg 1$) in the thin-Debye-layer limit ($\delta \ll 1$), our computations are in good agreement with recent experimental and asymptotic results.

    

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5. Multi-Objective Optimization of Predicted Magnetic Properties From Multifield Processing Conditions in Polymer Matrix Particle Composites

   https://doi.org/10.1115/SMASIS2022-91175  

   Widdowson, Denise ; Erol, Anil ; Papula, Dashiell ; Ounaies, Zoubeida ; von Lockette, Paris ( September 2022 , Proceedings of the ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Dearborn, Michigan, USA. September 12–14, 2022. V001T02A008. ASME.)

   Additive manufacturing, no longer reserved exclusively for prototyping components, can create parts with complex geometries and locally tailored properties. For example, multiple homogenous material sources can be used in different regions of a print or be mixed during printing to define properties locally. Additionally, heterogeneous composites provide an opportunity for another level of tuning properties through processing. For example, within particulate-filled polymer matrix composites before curing, the presence of an applied electric and/or magnetic fields can reorient filler particles and form hierarchical structures depending on the fields applied. Control of particle organization is important because effective material properties are highly dependent on the distribution of filler material within composites once cured. While previous work in homogenization and effective medium theories have determined properties based upon ideal analytic distributions of particle orientations and spatial location, this work expands upon these methods generating discrete distributions from quasi-Monte Carlo simulations of the electromagnetic processing event. Results of simulations provide predicted microarchitectures from which effective properties are determined via computational homogenization.

   These particle dynamics simulations account for dielectric and magnetic forces and torques in addition to hydrodynamic forces and hard particle separation. As such, the distributions generated are processing field dependent. The effective properties for a composite represented by this distribution are determined via computational homogenization using finite element analysis (FEA). This provides a path from constituents, through processing parameters to effective material properties. In this work, we use these simulations in conjunction with a multi-objective optimization scheme to resolve the relationships between processing conditions and effective properties, to inform field-assisted additive manufacturing processes.

   The constituent set providing the largest range of properties can be found using optimization techniques applied to the aforementioned simulation framework. This key information provides a recipe for tailoring properties for additive manufacturing design and production. For example, our simulation results show that stiffness for a 10% filler volume fraction can increase by 34% when aligned by an electric field as compared to a randomly distributed composite. The stiffness of this aligned sample is also 29% higher in the direction of the alignment than perpendicular to it, which only differs by 5% from the random case [1]. Understanding this behavior and accurately predicting composite properties is key to producing field processed composites and prints. Material property predictions compare favorably to effective medium theory and experimentation with trends in elastic and magnetic effective properties demonstrating the same anisotropic behavior as a result of applied field processing. This work will address the high computational expense of physics simulation based objective functions by using efficient algorithms and data structures. We will present an optimization framework using nested gradient searches for micro barium hexaferrite particles in a PDMS matrix, optimizing on composite magnetization to determine the volume fraction of filler that will provide the largest range of properties by varying the applied electric and magnetic fields.

    

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