Search

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.

Consensus-oriented public relations, which is considered within the social theoretical approach, is a model developed by Roland Burkart. The basic point on which the model is based is the concept of "consensus" mentioned by Habermas in his communicative action theory. Achieving consensus in communicative action depends on the efforts of the parties to understand each other. However, it is important to ensure equal conditions in the communication process and to create a democratic discussion environment. Thus, it may be possible to reach an consensus between institutions and target audiences in terms of public relations. The consensus-oriented public relations approach emphasizes that conflict resolution can be achieved when both sides develop the potential to understand each other in the face of a problem to be experienced between the institution and the target audience. At this point, it can be said that symmetrical public relations will facilitate understanding. As Habermas emphasized, a rational discussion and dialogue is the most effective way to bring the parties to an consensus. Consensus-oriented public relations model is explained within the scope of the study as a compilation. It is thought that this approach can contribute to institutions, especially in conflict management. Keywords: Consensus-Oriented Public Relations, Burkart, Theory of Communicative Action, Habermas.

Understanding ion adsorption in porous carbons is critical for a wide range of technologies, including water desalination and energy storage. In this work, we combined density functional theory wit...

Capacitive deionization (CDI) is a promising water desalination technology that is applicable to the treatment of low-salinity brackish waters and the selective removal of ionic contaminants. In this work, we show that by making a small change in the synthetic procedure of hierarchical carbon aerogel monolith (HCAM) electrodes, we can adjust the pore-size distribution and tailor the selectivity, effectively switching between selective adsorption of calcium or sodium ions. Ion selectivity was measured for a mixture of 5 mM NaCl and 2.5 mM CaCl

Understanding ion transport in nanoporous materials is critical to a wide variety of energy and environmental technologies, ranging from ion-selective membranes, drug delivery, and biosensing, to ion batteries and supercapacitors. While nanoscale transport is often described by continuum models that rely on a point charge description for ions and a homogeneous dielectric medium for the solvent, here, we show that transport of aqueous solutions at a hydrophobic interface can be highly dependent on the size and hydration strength of the solvated ions. Specifically, measurements of ion current through single silicon nitride nanopores that contain a hydrophobic-hydrophilic junction show that transport properties are dependent not only on applied voltage but also on the type of anion. We find that in Cl--containing solutions the nanopores only conducted ionic current above a negative voltage threshold. On the other hand, introduction of large polarizable anions, such as Br- and I-, facilitated the pore wetting, making the pore conductive at all examined voltages. Molecular dynamics simulations revealed that the large anions, Br- and I-, have a weaker solvation shell compared to that of Cl- and consequently were prone to migrate from the aqueous solution to the hydrophobic surface, leading to the anion accumulation responsible for pore wetting. The results are essential for designing nanoporous systems that are selective to ions of the same charge, for realization of ion-induced wetting in hydrophobic pores, as well as for a fundamental understanding on the role of ion hydration shell on the properties of solid/liquid interfaces.

Understanding ion transport in porous carbons is critical for a wide range of technologies, including supercapacitors and capacitive deionization for water desalination, yet many details remain poorly understood. For instance, an atomistic understanding of how ion selectivity is influenced by the molecular shape of ions, morphology of the micropores and applied voltages is largely lacking. In this work, we combined molecular dynamics simulations with enhanced sampling methods to elucidate the mechanism of nitrate and chloride selectivity in subnanometer graphene slit-pores. We show that nitrate is preferentially adsorbed over chloride in the slit-like micropores. This preferential adsorption was found to stem from the weaker hydration energy and unique anisotropy of the ion solvation of nitrate. Beside the effects of ion dehydration, we found that applied potential plays an important role in determining the ion selectivity, leading to a lower selectivity of nitrate over chloride at a high applied potential. We conclude that the measured ion selectivity results from a complex interplay between voltage, confinement, and specific ion effects-including ion shape and local hydration structure.

The advancement of machine learning techniques and the heterogeneous architectures of most current supercomputers are propelling the demand for large multiscale simulations that can automatically and autonomously couple diverse components and map them to relevant resources to solve complex problems at multiple scales. Nevertheless, despite the recent progress in workflow technologies, current capabilities are limited to coupling two scales. In the first-ever demonstration of using three scales of resolution, we present a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback. We expand upon the massively parallel Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a recent, award-winning workflow, and generalize the framework beyond its original design. We discuss the challenges and learnings in executing a massive multiscale simulation campaign that utilized over 600,000 node hours on Summit and achieved more than 98% GPU occupancy for more than 83% of the time. We present innovations to enable several orders of magnitude scaling, including simultaneously coordinating 24,000 jobs, and managing several TBs of new data per day and over a billion files in total. Finally, we describe the generalizability of our framework and, with an upcoming open-source release, discuss how the presented framework may be used for new applications.

Similar to natural photosynthesis, Z-scheme photocatalytic water splitting relies on two different light absorbing components that are coupled by a redox active mediator that shuttles charge between them. Such a two-absorber system possesses several advantages over single absorber photocatalytic system, including higher theoretical solar-to-hydrogen conversion efficiency, relaxed band alignment requirements, and the potential for inherently safe operation whereby H2 and O2 evolution occur in separated compartments. However, a major disadvantage and challenge for Z-scheme photocatalysis is that the presence of a redox mediator introduces two undesirable back-reactions on top of parasitic H2 oxidation and O2 reduction reactions that can occur in a single absorber photocatalytic system. Previous research efforts have identified the use of semi-permeable oxide coatings as an attractive approach to suppress these thermodynamically favored redox reactions while still permitting the desired water splitting and mediator redox reactions to occur. Here, we present a combined experimental and computational approach based on model thin films that is used to (i) probe the performance limits of oxide-encapsulated photocatalysts, (ii) quantify the effects of coating defects on performance, and (iii) guide the rational design of coatings aimed at maximizing the solar-to-hydrogen conversion efficiency of a target photocatalytic system. This work specifically focusses on the development of silicon and titanium oxide coatings for Z-scheme water splitting based on a Fe(II)/Fe(III) mediator, showing that the best coatings can achieve selectivities > 90 % towards the H2 and O2 evolution reactions over undesired Fe(II)/Fe(III) back reactions. Another key finding from this work is that coating defects can have a significant influence on the performance of encapsulated electrodes, as revealed by scanning electrochemical microscopy (SECM) measurements that were used to locally quantify the parasitic back reaction rates around individual defects to determine their impact on the global selectivity of an encapsulated electrode.

Understanding sorption in porous carbon electrodes is crucial to many environmental and energy technologies, such as capacitive deionization (CDI), supercapacitor energy storage, and activated carbon filters. In each of these examples, a practical model that can describe ion electrosorption kinetics is highly desirable for accelerating material design. Here, we proposed a multiscale model to study the ion electrosorption kinetics in porous carbon electrodes by combining quantum mechanical simulations with continuum approaches. Our model integrates the Butler-Volmer (BV) equation for sorption kinetics and a continuously stirred tank reactor (CSTR) formulation with atomistic calculations of ion hydration and ion-pore interactions based on density functional theory (DFT). We validated our model experimentally by using ion mixtures in a flow-through electrode CDI device and developed an in-line UV absorption system to provide unprecedented resolution of individual ions in the separation process. We showed that the multiscale model captures unexpected experimental phenomena that cannot be explained by the traditional ion electrosorption theory. The proposed multiscale framework provides a viable approach for modeling separation processes in systems where pore sizes and ion hydration effects strongly influence the sorption kinetics, which can be leveraged to explore possible strategies for improving carbon-based and, more broadly, pore-based technologies.

Confinement plays an important role in determining ion transport in porous materials, which, in turn, may influence the performance of many energy storage and desalination devices. In this work, we combined density functional theory (DFT) with an implicit solvation model and ab initio molecular dynamics (AIMD) to investigate the effects of nanoconfinement on several solvated alkaline metal cations in a single-digit 1T-MoS

Understanding ion solvation and transport under confinement is critical for a wide range of emerging technologies, including water desalination and energy storage. While molecular dynamics (MD) simulations have been widely used to study the behavior of confined ions, considerable deviations between simulation results depending on the specific treatment of intermolecular interactions remain. In the following, we present a systematic investigation of the structure and dynamics of two representative solutions, that is, KCl and LiCl, confined in narrow carbon nanotubes (CNTs) with a diameter of 1.1 and 1.5 nm, using a combination of first-principles and classical MD simulations. Our simulations show that the inclusion of both polarization and cation-π interactions is essential for the description of ion solvation under confinement, particularly for large ions with weak hydration energies. Beyond the variation in ion solvation, we find that cation-π interactions can significantly influence the transport properties of ions in CNTs, particularly for KCl, where our simulations point to a strong correlation between ion dehydration and diffusion. Our study highlights the complex interplay between nanoconfinement and specific intermolecular interactions that strongly control the solvation and transport properties of ions.

Small diameter carbon nanotubes show high water-salt permselectivity and low activation barrier for water transport., Carbon nanotube (CNT) pores, which mimic the structure of the aquaporin channels, support extremely high water transport rates that make them strong candidates for building artificial water channels and high-performance membranes. Here, we measure water and ion permeation through 0.8-nm-diameter CNT porins (CNTPs)—short CNT segments embedded in lipid membranes—under optimized experimental conditions. Measured activation energy of water transport through the CNTPs agrees with the barrier values typical for single-file water transport. Well-tempered metadynamics simulations of water transport in CNTPs also report similar activation energy values and provide molecular-scale details of the mechanism for water entry into these channels. CNTPs strongly reject chloride ions and show water-salt permselectivity values comparable to those of commercial desalination membranes.

Tarih boyunca farklı amaçlarla yanlış bilgiler ve söylentiler ortaya çıkmış olsa da internetin ortaya çıkmasıyla birlikte yalan haberlerin daha hızlı bir şekilde yayılmaya başladığı görülmektedir. Özellikle politik alanda gerçeklerin çarpıtılması ve yeniden üretilmesiyle birlikte hakikatin değersizleştiği post-truth (hakikat ötesi) döneme girilmiştir. Bu dönemde bilhassa sosyal medya, sahte haberlerin daha hızlı yayılmasına ve geniş kitlelere ulaşmasına neden olmaktadır. Bu durum ise sosyal medyadaki dezenformasyonun daha çok artmasına ve olumsuz sonuçlar doğurmasına yol açabilmektedir. Özellikle Covid-19 (yeni koronavirüs) pandemi sürecinde bu meselenin çok ciddi boyutlara ulaştığı görülmüştür. Neredeyse her gün üretilen sahte haberler Facebook, Twitter gibi sosyal ağlarda ve Whatsapp gruplarında dolaşıma sokulmuştur. Çoğu kişi bu haberlerin doğru olduğuna inanmış ve sosyal medyada daha hızlı yayılmasına sebep olmuştur. Bununla birlikte Sağlık Bakanı ve bakanlık bünyesinde kurulan Koronavirüs Bilim Kurulu üyelerinin adına açılan sahte sosyal medya hesaplarla insanlar yanlış yönlendirilmiştir. Hatta Dünya Sağlık Örgütü bu dezenformasyonun en az virüs kadar tehlikeli olduğunu vurgulamıştır.Betimsel analizin kullanıldığı bu çalışmada, Türkiye’de faaliyet gösteren teyit.org doğrulama platformunun Covid-19 pandemi sürecinde sosyal medyada dolaşıma sokulan iddialar hakkında yaptığı inceleme sonuçlarına ilişkin verilerin ne olduğu ortaya konmaya çalışılmıştır. Çalışma kapsamında, Türkiye’de ilk koronavirüs vakasının görüldüğü 11 Mart tarihi başlangıç alınarak 1 haftalık sürede (11-18 Mart 2020) ortaya çıkan iddialara yer verilmiştir., Although false information and rumors have appeared for different purposes throughout the history, it is seen that with the advent of the Internet, false news began to spread more rapidly. Especially with the distortion and reproduction of the realities in the political field, the post-truth period has entered into a period where truth has become worthless. In this period, especially social media causes fake news to spread faster and to reach large masses. This situation may cause disinfection in social media to increase more and cause negative results. Especially in the Covid-19 (new coronavirus) pandemic process, this issue has been seen to reach very serious dimensions. The fake news produced almost daily has been circulated in social networks such as Facebook and Twitter and in WhatsApp groups. Many people believed that this news was true and caused it to spread more quickly on social media. However, people were misled by false social media accounts opened on behalf of the Minister of Health and members of the Coronavirus Scientific Board established within the ministry. In fact, the World Health Organization emphasized that this disinformation is at least as dangerous as the virus.In this study, where a descriptive analysis is used, teyit.org verification platform operating in Turkey has tried to reveal the data regarding the results of the investigation made by the verification platform about the claims circulating in social media in the process of Covid-19 pandemic. In scope of study, the first coronavirus cases seen in Turkey as starting on March 11 are given to claims that arising in one-week period (11-18 March 2020).

Simulations and experiments have revealed enormous transport rates through carbon nanotube (CNT) channels when a pressure gradient drives fluid flow, but comparatively little attention has been given to concentration‐driven transport despite its importance in many fields. Here, membranes are fabricated with a known number of single‐walled CNTs as fluid transport pathways to precisely quantify the diffusive flow through CNTs. Contrary to early experimental studies that assumed bulk or hindered diffusion, measurements in this work indicate that the permeability of small ions through single‐walled CNT channels is more than an order of magnitude higher than through the bulk. This flow enhancement scales with the ion free energy of transfer from bulk solutions to a nanoconfined, lower‐dielectric environment. Reported results suggest that CNT membranes can unlock dialysis processes with unprecedented efficiency., Concentration‐gradient driven diffusion rates of ions through single‐walled carbon nanotubes are shown to be up to 36 times faster than in bulk. This previously unrecognized flow enhancement scales with the ion free energy of transfer from bulk solutions to a nanoconfined, lower‐dielectric environment. Utilization of fast diffusion can greatly benefit fields ranging from hemodialysis to energy storage.

The society that emerged after the industry and the image became dominant was expressed by the French thinker Debord with the term "society of spectacle". In the society of the show where the truth and the fake are intertwined, everything has begun to be evaluated through images. The spectacle, which continued with the traditional media, continued with the advent of the internet and social media. This medium, where the spectacle has found a living space, has gained different dimensions. Social media, where users have become part of the spectacle, has become a new spectacle and surveillance space. In this context, it can be said that social media is a new Panopticon. Panopticon is a prison model created by Jeremy Bentham. In this model, the person in the tower can see all the cells, while those in the cells cannot see the person in the tower. Today, with the social media, this form of surveillance has evolved in a different direction. In this new Panaptikon, one-sided surveillance has been replaced by an environment where everyone is watching each other. The show continues non-stop on social media where privacy has disappeared. In this descriptive and critical study, social media was discussed within the framework of the concepts of " society of spectacle " and "panopticon"., Endüstri sonrası ortaya çıkan ve imajın baskın hale geldiği toplum, Fransız düşünür Debord tarafından “gösteri toplumu” terimiyle ifade edilmiştir. Gerçek ile sahtenin iç içe geçtiği gösteri toplumunda, her şey görüntüler üzerinden değerlendirilmeye başlanmıştır. Geleneksel medyayla birlikte devam eden gösteri, internetin ve sosyal medyanın ortaya çıkmasıyla birlikte devam etmiştir. Gösterinin kendisine yaşam alanı bulduğu bu mecra farklı boyutlar kazanmıştır. Kullanıcıların gösterinin bir parçası haline geldiği sosyal medya, yeni bir gösteri ve gözetim alanı haline gelmiştir. Bu bağlamda sosyal medyanın yeni bir panoptikon olduğu söylenebilir. Panoptikon, Jeremy Bentham tarafından oluşturulmuş bir hapishane modelidir. Bu modelde, kuledeki kişi bütün hücreleri görebilirken hücrelerde bulunanlar kuledeki kişiyi görememektedir. Günümüzde sosyal medyayla birlikte bu gözetim şekli farklı yöne doğru evrilmiştir. Bu yeni panoptikonda tek taraflı gözetimin yerini herkesin birbirini gözetlediği bir ortam almıştır. Mahremiyetin ortadan kalktığı sosyal medyada gösteri durmaksızın devam eder. Betimleyici ve eleştirel nitelikteki bu çalışmada sosyal medya, “gösteri toplumu” ve “panoptikon” kavramları çerçevesinde ele alınarak tartışılmıştır.

Inner pores of carbon nanotubes combine extremely fast water transport and ion selectivity that could potentially be useful for high-performance water desalination and separation applications. We used dye-quenching halide assays and stopped-flow spectrometry to determine intrinsic permeability of three small monovalent halide anions (chloride, bromide, iodide) and one pseudohalide anion (thiocyanate) through narrow 0.8 nm diameter carbon nanotube porins (CNTPs). These measurements revealed unexpectedly strong differential ion selectivity with permeabilities of different ions varying by up to 2 orders of magnitude. Removal of the negative charge from the nanotube entrance increased anion permeability by only a relatively small factor, indicating that electrostatic repulsion was not a major determinant of CNTP selectivity. First principle molecular dynamics simulations revealed that the origin of this strong differential ion selectivity is partial dehydration of anions upon entry into the narrow CNTP channels.

Understanding ion solvation in liquid water is critical in optimizing materials for a wide variety of emerging technologies, including water desalination and purification. In this work, we report a systematic investigation and comparison of solvated K+ and NH4+ using first-principles molecular dynamics simulations. Our simulations reveal a strong analogy in the solvation properties of the two ions, including the size of the solvation shell as well as the solvation strength. On the other hand, we find that the local water structure in the ion solvation is significantly different; specifically, NH4+ yields a smaller number of water molecules and a more ordered water structure in the first solvation shell due to the formation of hydrogen bonds between the ion and water molecules. Finally, our simulations indicate that a comparable solvation strength of the two ions is a result of an interplay between the nature of ion-water interaction and number of water molecules that can be accommodated in the ion solvation shell.

Carbon-based nanomaterials such as nanocomposites and nanosuspensions have gained significant prominence in diverse applications due to their ability to enhance desired material functionalities. Some examples of these applications include drug delivery, additive manufacturing, and technologies reliant on efficient electrical and thermal conductivity. Of specific interest are carbon-based nanomaterials which have potential applications in thermal transfer processes. Experimental techniques have made notable strides in the synthesis, characterization and use of such nanomaterials in heat transfer processes. Yet, these techniques do not have the spatiotemporal resolution to capture processes and mechanics underlying the behavior of these materials. This gap has been met via the employment of computational tools. This chapter will examine the computational methods that have been harnessed to study carbon-based nanomaterials, specifically nanocomposites and nanosuspensions. The computational methods discussed will include the diverse techniques that have been employed to date. Some of these techniques will encompass multiscale simulation methods such as the molecular dynamics and dissipative particle dynamics techniques. Furthermore, the chapter will discuss current challenges in these methods and future directions.

The flow of particles through confined volumes has appeared under different contexts in nature and technology. Some examples include the flow of red blood cells or drug delivery vehicles through capillaries, or surfactant-based particles in nano- or microfluidic cells. The molecular composition of the particles along with external conditions and the characteristics of the confined volume impact the response of the particle to flow. This review focuses on the problem of phospholipid vesicles constrained to flowing in channels. The review examines how experimental and computational approaches have been harnessed to study the response of these particles to the flow.

Understanding the permeation of biomolecules through cellular membranes is critical for many biotechnological applications, including targeted drug delivery, pathogen detection, and the development of new antibiotics. To this end, computer simulations are routinely used to probe the underlying mechanisms of membrane permeation. Despite great progress and continued development, permeation simulations of realistic systems (e.g., more complex drug molecules or biologics through heterogeneous membranes) remain extremely challenging if not intractable. In this work, we combine molecular dynamics simulations with transition-tempered metadynamics and techniques from the variational approach to conformational dynamics to study the permeation mechanism of a drug molecule, trimethoprim, through a multicomponent membrane. We show that collective variables (CVs) obtained from an unsupervised machine learning algorithm called time-structure based Independent Component Analysis (tICA) improve performance and substantially accelerate convergence of permeation potential of mean force (PMF) calculations. The addition of cholesterol to the lipid bilayer is shown to increase both the width and height of the free energy barrier due to a condensing effect (lower area per lipid) and increase bilayer thickness. Additionally, the tICA CVs reveal a subtle effect of cholesterol increasing the resistance to permeation in the lipid head group region, which is not observed when canonical CVs are used. We conclude that the use of tICA CVs can enable more efficient PMF calculations with additional insight into the permeation mechanism.

Kriz dönemlerinde hedef kitle ile etkili bir iletişim kurulamadığı ve kriz iyi yönetilmediği takdirde kurumsal markaya ilişkin olumsuz bir algı oluşmakta ve kurumun itibarı sarsılabilmektedir. Dolayısıyla krizlerin kurumsal markaya en az zarar verecek şekilde yönetilmesi büyük önem taşımaktadır. Bunun için de kriz anlarında kurumsal markaların hedef kitlesi ile hızlı bir şekilde iletişime geçerek onlara ikna edici ve bilgilendirici mesajlar göndermesi gerekmektedir. Çalışma kapsamında, gıda sektöründe faaliyet gösteren “Pınar” markasının 2017 yılında yaşadığı itibar krizinde, markanın kriz iletişimini nasıl gerçekleştirdiğini tespit etmek amacıyla nitel araştırma yöntemlerinden bütüncül tek durum deseni kullanılmıştır. Krize Coombs’un itibarı onarma stratejileri açısından yaklaşılmıştır. Sonuç olarak kurum tarafından destekleme ve onarma yönlü bir yaklaşımın sergilendiği görülmüştür. Kurumun saldırgan ve suçlayıcı bir dilden uzak durarak yapıcı bir söylemle iletişimi yönettiği tespit edilmiştir.

Confinement plays an important role in determining ion transport in porous materials, which, in turn, may influence the performance of many energy storage and desalination devices. In this work, we combined density functional theory (DFT) with an implicit solvation model and ab initio molecular dynamics (AIMD) to investigate the effects of nanoconfinement on several solvated alkaline metal cations in a single-digit 1T-MoS2 nanochannel. Our DFT calculations with a solvation model indicated that cations with stronger hydration energy introduce a higher number of co-intercalated water molecules into the channel, consistent with early experimental observation obtained for MXene (2D transition metal carbide) channels. The predicted optimal water numbers for the cations were then used for AIMD simulations that explicitly include the effects of the solvent. When compared with the cations in bulk solution, our simulations showed that the hydration structure and coordination number (CN) of the solvated cations confined in the MoS2 channel can be significantly altered. We found that larger cations with weaker hydration energy (K+, Rb+, and Cs+) exhibited a distinctive CN decrease under confinement, while smaller cations (Li+ and Na+) retained a similar hydration shell as in the bulk solution. More specifically, the hydration shell of large cations (K+, Rb+, and Cs+) in MoS2 showed similar features of the coordination angle to the bulk, which suggests the partially broken hydration shell with no geometry change under confinement. Our simulations provided insights into the change of the hydration structure of alkaline metal cations under confinement, which may have important implications on their transport in the 1T-MoS2 channel.

We demonstrate the adsorption of nanoparticles (NPs) with charged patches onto a binary vesicle encompassing polar neutral and polar zwitterionic lipids via an implicit solvent coarse-grained model and molecular dynamics simulations. Our investigations on the interactions between NPs and a binary vesicle demonstrate that the adsorption of charged NPs onto a binary vesicle surface can induce structural reorganization of the lipid bilayer. The approach of the NP to the vesicle surface is accompanied by spatial reorganization of the zwitterionic lipids, and the degree of reorganization is found to depend on the NP patch size. Interfacial adsorption of the NP is observed to promote a group of zwitterionic lipids to cluster at the adsorption site. Spatial reorganization of the zwitterionic lipids is activated by favorable electrostatic interactions with the NP and not between the lipids. The favorable electrostatic interaction between oppositely charged lipid headgroup moieties increases and assists the clustering process as the NP approaches the vesicle surface. In addition, the availability of zwitterionic lipids in the vesicle affects the adsorption dynamics of multiple NPs. Our results can be used for the design of reconfigurable biomaterials for applications in drug delivery, sensing, and imaging.

Via the Dissipative Particle Dynamics simulation technique we investigate the interfacial adsorption of nanoparticles with a binding site onto a hairy vesicle encompassing phospholipids and lipids functionalized with oligo ethylene glycol (OEG) chain. The functionalized nanoparticles are modeled as patchy spherical particles. We examine the relation between the relative concentration and size of the OEG chains, the adsorption kinetics, life-time and post-adsorption dynamics of the nanoparticles. We also draw correspondence with experimental studies on the adsorption of proteins onto the surface of colloidal particles. Results from our investigations can elucidate the fundamental factors and mechanisms controlling the adsorption of functionalized nanoparticles onto colloidal particles.

Highly branched polymers such as polyamidoamine (PAMAM) dendrimers are promising macromolecules in the realm of nanobiotechnology due to their high surface coverage of tunable functional groups. Modeling efforts of PAMAM can provide structural and morphological properties, but the inclusion of solvents and the exponential growth of atoms with generations make atomistic simulations computationally expensive. We apply an implicit solvent coarse-grained model, called the Dry Martini force field, to PAMAM dendrimers. The reduced number of particles and the absence of a solvent allow the capture of longer spatiotemporal scales. This study characterizes PAMAM dendrimers of generations one through seven in acidic, neutral, and basic pH environments. Comparison with existing literature, both experimental and theoretical, is done using measurements of the radius of gyration, moment of inertia, radial distributions, and scaling exponents. Additionally, ion coordination distributions are studied to provide insight into the effects of interior and exterior protonation on counter ions. This model serves as a starting point for future designs of larger functionalized dendrimers.

Mycolactone, a cytotoxic and immunosuppressive macrolide produced by Mycobacterium ulcerans, is the central virulent factor in the skin disease Buruli ulcer. This multifunctional cytotoxin affects fundamental cellular processes such as cell adhesion, immune response and cell death by targeting various cellular structures. Developing effective diagnostics that target mycolactone has been challenging, potentially due to suspected interactions with lipophilic architectures, including membranes. To better understand the pathogenesis of Buruli ulcer disease, aid in the development of diagnostics, and learn how amphiphiles in general use lipid trafficking to navigate the host environment, we seek to understand the nature of mycolactone-membrane interactions. Herein we characterize how the two dominant isomers of mycolactone (A and B) interact with and permeate DPPC membranes with all-atom molecular dynamics simulations employing transition tempered metadynamics, and compare these results with those obtained by MARTINI coarse-grained simulations. Our all-atom simulations reveal that both isomers have a strong preference to associate with the membrane, although their mechanisms and energetics of membrane permeation differ slightly. Water molecules are found to play an important role in the permeation process. Although the MARTINI coarse-grained simulations give the correct free energy of membrane association, they fail to capture the mechanism of permeation and role of water during permeation as seen in all-atom simulations.

Mycolactone, a cytotoxic and immunosuppressive macrolide produced by Mycobacterium ulcerans, is the central virulent factor in the skin disease Buruli ulcer. This multifunctional cytotoxin affects fundamental cellular processes such as cell adhesion, immune response, and cell death by targeting various cellular structures. Developing effective diagnostics that target mycolactone has been challenging, potentially because of suspected interactions with lipophilic architectures, including membranes. To better understand the pathogenesis of Buruli ulcer disease, aid in the development of diagnostics, and learn how amphiphiles in general use lipid trafficking to navigate the host environment, we seek to understand the nature of mycolactone-membrane interactions. Herein, we characterize how the two dominant isomers of mycolactone (A and B) interact with and permeate DPPC membranes with all-atom molecular dynamics simulations employing transition-tempered metadynamics and compare these results to those obtained by MARTINI coarse-grained simulations. Our all-atom simulations reveal that both isomers have a strong preference to associate with the membrane, although their mechanisms and energetics of membrane permeation differ slightly. Water molecules are found to play an important role in the permeation process. Although the MARTINI coarse-grained simulations give the correct free energy of membrane association, they fail to capture the mechanism of permeation and role of water during permeation as seen in all-atom simulations.

Actin is an important cytoskeletal protein that serves as a building block to form filament networks that span across the cell. These networks are orchestrated by a myriad of other cytoskeletal entities including the unbranched filament-forming protein formin and branched network-forming protein complex Arp2/3. Computational models have been able to provide insights into many important structural transitions that are involved in forming these networks, and into the nature of interactions essential for actin filament formation and for regulating the behavior of actin-associated proteins. In this review, we summarize a subset of such models that focus on the atomistic features and those that can integrate atomistic features into a larger picture in a multiscale fashion.

Formins play an important role in the polymerization of unbranched actin filaments, and particular formins slow elongation by 5-95%. We studied the interactions between actin and the FH2 domains of formins Cdc12, Bni1 and mDia1 to understand the factors underlying their different rates of polymerization. All-atom molecular dynamics simulations revealed two factors that influence actin filament elongation and correlate with the rates of elongation. First, FH2 domains can sterically block the addition of new actin subunits. Second, FH2 domains flatten the helical twist of the terminal actin subunits, making the end less favorable for subunit addition. Coarse-grained simulations over longer time scales support these conclusions. The simulations show that filaments spend time in states that either allow or block elongation. The rate of elongation is a time-average of the degree to which the formin compromises subunit addition rather than the formin-actin complex literally being in ‘open’ or ‘closed’ states.

We design sterically stable biocompatible vehicles with tunable shapes through the self-assembly of a binary mixture composed of amphiphilic molecular species, such as PEGylated lipids, and phospholipids under volumetric confinement. We use a molecular dynamics-based mesoscopic simulation technique called dissipative particle dynamics to resolve the aggregation dynamics, structure, and morphology of the hybrid aggregate. We examine the effect of confinement on the growth dynamics and shape of the hybrid aggregate, and demonstrate the formation of different morphologies, such as oblate and prolate shaped vesicles and bicelles. We perform these investigations by varying the degree of nanoscale confinement, for different relative concentrations of the species and the length of the functional groups. Results from our investigations can be used for the design and prediction of novel hybrid soft materials for applications requiring the encapsulation of therapeutic agents in micro- or nanofluidic channels.

The structural integrity of red blood cells and drug delivery carriers through blood vessels is dependent upon their ability to adapt their shape during their transportation. Our goal is to examine the role of the composition of bio-inspired multicomponent and hairy vesicles on their shape during their transport through in a channel. Through the dissipative particle dynamics simulation technique, we apply Poiseuille flow in a cylindrical channel. We investigate the effect of flow conditions and concentration of key molecular components on the shape, phase separation, and structural integrity of the bio-inspired multicomponent and hairy vesicles. Our results show the Reynolds number and molecular composition of the vesicles impact their flow-induced deformation, phase separation on the outer monolayer due to the Marangoni effect, and rupture. The findings from this study could be used to enhance the design of drug delivery and tissue engineering systems.

Kurumsal markalaşma sürecinde kurumlar sahip oldukları özellikleri, değerleri tüketicilere duyurmak ve olumlu bir imaj yaratmak için kitle iletişim araçlarını kullanmaktadır. Sosyal medyanın ortaya çıkmasıyla birlikte, kurumlar bu yeni ortamı da amaçları doğrultusunda kullanmaya başlamış ve sosyal medyayı kullanarak markalaşma amaçlarına hizmet etmeye çalışmaktadır. Sosyal medya sayesinde kurumsal markalar, tüketicilerle her zamankinden daha hızlı, daha etkin ve kişisel düzeyde iletişim kurma imkânı yakalamıştır. Markalar, özellikle sosyal medya üzerinden yürüttükleri kampanyalarda, kullanıcıları da sürecin içine katarak onlarla birlikte ortak çalışmalar yapmaktadır. Bu interaktif süreç iyi yönetildiği takdirde, kurumsal markalara önemli ölçüde katkı sağlayabilmektedir. Bu çalışmada bazı anaakım iletişim kuramlarından yola çıkılarak sosyal medya ve kurumsal markalaşma ilişkisine yönelik bir değerlendirme yapılmıştır.

We are interested in designing nanostructured biomaterials using nanoscopic building blocks such as functionalized nanotubes and lipid molecules. In our earlier work, we summarized the multiple control parameters which direct the equilibrium morphology of a specific class of nanostructured biomaterials. Individual lipid molecules were composed of a hydrophilic head group and two hydrophobic tails. A bare nanotube encompassed an ABA architecture, with a hydrophobic shaft (B) and two hydrophilic ends (A). We introduced hydrophilic hairs at one end of the tube to enable selective transport through the channel. The dimensions of the nanotube were set to minimize its hydrophobic mismatch with the lipid bilayer. We used a Molecular Dynamics-based mesoscopic simulation technique called Dissipative Particle Dynamics which simultaneously resolves the structure and dynamics of the nanoscopic building blocks and the hybrid aggregate. The amphiphilic lipids and functionalized nanotubes self-assembled into a stable hybrid vesicle or a bicelle in the presence of a hydrophilic solvent. We showed that the morphology of the hybrid structures was directed by factors such as the temperature, the rigidity of the lipid molecules, and the concentration of the nanotubes. Another type of hybrid nanostructured biomaterial could be multi-component lipid bilayers. In this paper, we present approaches to design hybrid nanostructured materials using multiple lipid species with different chemistries and molecular chain stiffness.

We examine the interaction between peptide-inspired nanoparticles, or nanopins, and multicomponent vesicles using the dissipative particle dynamics simulation technique. We study the role of nanopin architecture and cholesterol concentration on the binding of the nanopins to the lipid bilayer, their insertion, and postembedding self-organization. We find the insertion to be triggered by enthalpically unfavorable interactions between the hydrophilic solvent and the lipophilic components of the nanopins. The nanopins are observed to form aggregates in solution, insert into the bilayer, and disassemble into the individual nanopins following the insertion process. We examine factors that influence the orientation of the nanopins in the host vesicle. We report the length of the hydrophilic segment of the nanopins to regulate their orientation within the clusters before the embedding process and in the bilayer, after the postinsertion disassembly of the aggregates. The orientation angle distribution for a given nanopin architecture is found to be driven by energy minimization. In addition, higher concentration of cholesterol is observed to constrain the orientation of the nanopins. We also report thermal fluctuations to induce transverse diffusion of nanopins with specific architectures. The incidence of transverse diffusion is observed to decrease with the concentration of cholesterol. Our results can provide guidelines for designing peptide-inspired nanoparticles or macromolecules that can interface with living cells to serve as sensors for applications in medicine, sustainability, and energy.

The Dissipative Particle Dynamics (DPD) simulation technique is a coarse-grained (CG) Molecular Dynamics-based approach that can effectively capture the hydrodynamics of complex systems while retaining essential information about the structural properties of the molecular species. An advantageous feature of DPD is that it utilizes soft repulsive interactions between the beads, which are CG representation of groups of atoms or molecules. In this study, we used the DPD simulation technique to study the aggregation characteristics of ABA triblock copolymers in aqueous medium. Pluronic® polymers (PEG-PPO-PEG) were modeled as two segments of hydrophilic beads and one segment of hydrophobic beads. Tyrosine-derived PEG(5K)-b-oligo(desaminotyrosyl tyrosine octyl ester-suberate)-b-PEG(5K) (PEG(5k)-oligo(DTO-SA)-PEG(5k)) block copolymers possess alternate rigid and flexible components along the hydrophobic oligo(DTO-SA) chain, and were modeled as two segments of hydrophilic beads and one segment of hydrophobic, alternate soft and hard beads. The formation, structure, and morphology of the initial aggregation of the polymer molecules in aqueous medium were investigated by following the aggregation dynamics. The dimensions of the aggregates predicted by the computational approach were in good agreement with corresponding results from experiments, for the Pluronic® and PEG(5k)-oligo(DTO-SA)-PEG(5k) block copolymers. In addition, DPD simulations were utilized to determine the critical aggregation concentration (CAC), which was compared with corresponding results from an experimental approach. For Pluronic® polymers F68, F88, F108, and F127, the computational results agreed well with experimental measurements of the CAC measurements. For PEG(5k)-b-oligo(DTO-SA)-b-PEG(5K) block polymers, the complexity in polymer structure made it difficult to directly determine their CAC values via the CG scheme. Therefore, we determined CAC values of a series of triblock copolymers with 3 to 8 DTO-SA units using DPD simulations, and used these results to predict the CAC values of triblock copolymers with higher molecular weights by extrapolation. In parallel, a PEG(5K)-b-oligo(DTO-SA)-b-PEG(5K) block copolymer was synthesized and the CAC value was determined experimentally using the pyrene method. The experimental CAC value agreed well with the CAC value predicted by simulation. These results validate our CG models, and demonstrate an avenue to simulate and predict aggregation characteristics of ABA amphiphilic triblock copolymers with complex structures.