Effects of Grain Boundaries and Surfaces on Electronic and Mechanical Properties of Solid Electrolytes

Extended defects, including exposed surfaces and grain boundaries (GBs), are critical to the properties of polycrystalline solid electrolytes in all-solid-state batteries (ASSBs). These defects can alter the mechanical and electronic properties of solid electrolytes, with direct manifestations in the performance of ASSBs. Here, by building a library of 590 surfaces and grain boundaries of 11 relevant solid electrolytes—including halides, oxides, and sulfides— their electronic, mechanical, and thermodynamic characteristics are linked to the functional properties of polycrystalline solid electrolytes. It is found that the energy required to mechanically “separate” grain boundaries can be significantly lower than in the bulk region of materials, which can trigger preferential cracking of solid electrolyte particles in the grain boundary regions. The brittleness of ceramic solid electrolytes, inferred from the predicted low fracture toughness at the grain boundaries, contributes to their cracking under local pressure imparted by lithium (sodium) penetration in the grain boundaries. Extended defects of solid electrolytes introduce new electronic interfacial states within bandgaps of solid electrolytes. These states alter and possibly increase locally the availability of free electrons and holes in solid electrolytes. Factoring effects arising from extended defects appear crucial to explain electrochemical and mechanical observations in ASSBs.     

Multiscale modeling of cellular actin filaments: from atomistic molecular to coarse-grained dynamics

In this article, we present a computational multiscale model for the characterization of subcellular proteins. The model is encoded inside a simulation tool that builds coarse-grained (CG) force fields from atomistic simulations. Equilibrium molecular dynamics simulations on an all-atom model of the actin filament are performed. Then, using the statistical distribution of the distances between pairs of selected groups of atoms at the output of the MD simulations, the force field is parameterized using the Boltzmann inversion approach. This CG force field is further used to characterize the dynamics of the protein via Brownian dynamics simulations. This combination of methods into a single computational tool flow enables the simulation of actin filaments with length up to 400 nm, extending the time and length scales compared to state-of-the-art approaches. Moreover, the proposed multiscale modeling approach allows to investigate the relationship between atomistic structure and changes on the overall dynamics and mechanics of the filament and can be easily (i) extended to the characterization of other subcellular structures and (ii) used to investigate the cellular effects of molecular alterations due to pathological conditions.     

Multiscale simulations of protein folding: application to formation of secondary structures

A multiscale simulation method of protein folding is proposed, using atomic representation of protein and solvent, combing genetic algorithms to determine the key protein structures from a global view, with molecular dynamic simulations to reveal the local folding pathways, thus providing an integrated landscape of protein folding. The method is found to be superior to previously investigated global search algorithms or dynamic simulations alone. For secondary structure formation of a selected peptide, RN24, the structures and dynamics produced by this method agree well with corresponding experimental results. Three most populated conformations are observed, including hairpin, β-sheet and α-helix. The energetic barriers separating these three structures are comparable to the kinetic energy of the atoms of the peptide, implying that the transition between these states can be easily triggered by kinetic perturbations, mainly through electrostatic interactions between charged atoms. Transitions between α-helix and β-sheet should jump over at least two energy barriers and may stay in the energetic trap of hairpin. It is proposed that the structure of proteins should be jointly governed by thermodynamic and dynamic factors; free energy is not the exclusive dominant for stability of proteins.     

Spatial Analysis and Modeling Tool (SAMT): 2. Applications

The Spatial Analysis and Modeling Tool (SAMT) is a GIS-based analytical software for land use study. This paper demonstrates the capabilities of SAMT as applied in studies of land use and landscape change in the catchment area of the River Quillow, North-East Germany. Neural network and fuzzy models are important features that were incorporated in SAMT. The region of study for this application is a catchment area of about 170 km² and is subdivided into 54,000 grid cells for spatial simulations.Three different applications of SAMT are discussed in this article. The first application involves assessment of the potential soil erosion risk on arable land. This user-defined application combines an economic model (LP model), a temperature-driven crop coverage model and a soil erosion risk model (Universal Soil Loss Equation) using data from tables and map information. The second and third applications are winter wheat yield estimates using, respectively, the fuzzy toolbox SAMT_FUZZY in conjunction with expert knowledge, and using the neural network toolbox SAMT_NN based on observations.     

Modeling the Effect of Amino Acids and Copper on Monoclonal Antibody Productivity and Glycosylation: A Modular Approach

In manufacturing monoclonal antibodies (mAbs), it is crucial to be able to predict how process conditions and supplements affect productivity and quality attributes, especially glycosylation. Supplemental inputs, such as amino acids and trace metals in the media, are reported to affect cell metabolism and glycosylation; quantifying their effects is essential for effective process development. We aim to present and validate, through a commercially relevant cell culture process, a technique for modeling such effects efficiently. While existing models can predict mAb production or glycosylation dynamics under specific process configurations, adapting them to new processes remains challenging, because it involves modifying the model structure and often requires some mechanistic understanding. Here, a modular modeling technique for adapting an existing model for a fed-batch Chinese hamster ovary (CHO) cell culture process without structural modifications or mechanistic insight is presented. Instead, data is used, obtained from designed experimental perturbations in media supplementation, to train and validate a supplemental input effect model, which is used to “patch” the existing model. The combined model can be used for model-based process development to improve productivity and to meet product quality targets more efficiently. The methodology and analysis are generally applicable to other CHO cell lines and cell types.     

Structural Properties of Neurofilament Sidearms: Sequence-Based Modeling of Neurofilament Architecture

Neurofilaments (NFs) are essential cytoskeletal filaments that impart mechanical integrity to nerve cells. They are assembled from three distinct molecular mass proteins that bind to each other to form a 10-nm-diameter filamentous rod with sidearm extensions. The sidearms are considered to play a critical role in modulating interfilament spacing and axonal caliber. However, the precise mechanism by which NF protrusions regulate axonal diameter remains to be well understood. In particular, the role played by individual NF protrusions in specifying interfilament distances is yet to be established. To gain insight into the role of individual proteins, we investigated the structural organization of NF architecture under different phosphorylation conditions. To this end, a physically motivated sequence-based coarse-grain model of NF brush has been developed based on the three-dimensional architecture of NFs. The model incorporates the charge distribution of sidearms, including charges from the phosphorylation sites corresponding to Lys-Ser-Pro repeat motifs. The model also incorporates the proper grafting of the real NF sidearms based on the stoichiometry of the three subunits. The equilibrium structure of the NF brush is then investigated under different phosphorylation conditions. The phosphorylation of NF modifies the structural organization of sidearms. Upon phosphorylation, a dramatic change involving a transformation from a compact conformation to an extended conformation is found in the heavy NF (NF-H) protein. However, in spite of extensive phosphorylation sites present in the NF-H subunit, the tails of the medium NF subunit are found to be more extended than the NF-H sidearms. This supports the notion that medium NF protrusions are critical in regulating NF spacings and, hence, axonal caliber.     

A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientation Tuning

We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are grouped into large populations of similar neurons. For each population, we form a probability density that represents the distribution of neurons over all possible states. The populations are coupled via stochastic synapses in which the conductance of a neuron is modulated according to the firing rates of its presynaptic populations. The evolution equation for each of these probability densities is a partial differential-integral equation, which we solve numerically. Results obtained for several example networks are tested against conventional computations for groups of individual neurons.We apply this approach to modeling orientation tuning in the visual cortex. Our population density model is based on the recurrent feedback model of a hypercolumn in cat visual cortex of Somers et al. (1995). We simulate the response to oriented flashed bars. As in the Somers model, a weak orientation bias provided by feed-forward lateral geniculate input is transformed by intracortical circuitry into sharper orientation tuning that is independent of stimulus contrast.The population density approach appears to be a viable method for simulating large neural networks. Its computational efficiency overcomes some of the restrictions imposed by computation time in individual neuron simulations, allowing one to build more complex networks and to explore parameter space more easily. The method produces smooth rate functions with one pass of the stimulus and does not require signal averaging. At the same time, this model captures the dynamics of single-neuron activity that are missed in simple firing-rate models.     

The Potential Role of Stream Habitat Restoration in Facilitating Salmonid Invasions: A Habitat‐Hydraulic Modeling Approach

Many successful invasions have taken place in systems where harmful disturbance has changed habitat conditions. However, less attention has been paid to the role of habitat restoration, which modifies habitats and thus also has the potential to facilitate invasions. We examined whether in‐stream habitat restorations have the potential to either facilitate or resist invasion by two widely introduced non‐native stream salmonids, Salvelinus fontinalis Mitchill and Oncorhynchus mykiss Walbaum, in Finland. A physical habitat simulation system was used to calculate whether the habitat area for the target species increased or decreased following the restorations. For comparison, we also reported results for four native stream fish species. The simulations showed that the restored streams provided the highest amount of usable habitat area for the native species, particularly for Salmo salar L. and Gottus gobio L. However, it was interesting to note that the restorations significantly increased habitat quality for the two non‐native species, especially at low flows. Nevertheless, the non‐native species had the lowest amount of usable habitat area overall. The modeling results indicated that not only habitat destruction but also habitat restoration could contribute to the spread of non‐native species. Fisheries and wildlife managers should be aware of the possibility, when restoring habitats in order to preserve native ecosystems, that non‐native species could manage to gain a foothold in restored habitats and use them as population sources for further spread. Knowing the widespread negative effect of non‐native species, this risk should not be underestimated.     

Three‐Phase Multiscale Modeling of a LiCoO2 Cathode: Combining the Advantages of FIB–SEM Imaging and X‐Ray Tomography

LiCoO₂ electrodes contain three phases, or domains, each having specific‐intended functions: ion‐conducting pore space, lithium‐ion‐reacting active material, and electron conducting carbon‐binder domain (CBD). Transport processes take place in all domains on different characteristic length scales: from the micrometer scale in the active material grains through to the nanopores in the carbon‐binder phase. Consequently, more than one imaging approach must be utilized to obtain a hierarchical geometric representation of the electrode. An approach incorporating information from the micro‐ and nanoscale to calculate 3D transport‐relevant properties in a large‐reconstructed active domain is presented. Advantages of focused ion beam/scanning electron microscopy imaging and X‐ray tomography combined by a spatial stochastic model, validated with an artificially produced reference structure are used. This novel approach leads to significantly different transport relevant properties compared with previous tomographic approaches: nanoporosity of the CBD leads to up to 42% additional contact area between active material and pore space and increases ionic conduction by a factor of up to 3.6. The results show that nanoporosity within the CBD cannot be neglected.     

A Candidate Complex Approach to Study Functional Mitochondrial DNA Changes: Sequence Variation and Quaternary Structure Modeling of Drosophila simulans Cytochrome c Oxidase

A problem with studying evolutionary dynamics of mitochondrial (mt) DNA is that classical population genetic techniques cannot identify selected substitutions because of genetic hitchhiking. We circumvented this problem by employing a candidate complex approach to study sequence variation in cytochrome c oxidase (COX) genes within and among three distinct Drosophila simulans mtDNA haplogroups. First, we determined sequence variation in complete coding regions for all COX mtDNA and nuclear loci and their isoforms. Second, we constructed a quaternary structure model of D. simulans COX. Third, we predicted that six of nine amino acid changes in D. simulans mtDNA are likely to be functionally important. Of these seven, genetic crosses can experimentally determine the functional significance of three. Fourth, we identified two single amino acid changes and a deletion of two consecutive amino acids in nuclear encoded COX loci that are likely to influence cytochrome c oxidase activity. These data show that linking population genetics and quaternary structure modeling can lead to functional predictions of specific mtDNA amino acid mutations and validate the candidate complex approach. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.     

TSAR,a new graph–theoretical approach to computational modeling of protein side‐chain flexibility: Modeling of ionization properties of proteins

A new graph–theoretical approach called thermodynamic sampling of amino acid residues (TSAR) has been elaborated to explicitly account for the protein side chain flexibility in modeling conformation‐dependent protein properties. In TSAR, a protein is viewed as a graph whose nodes correspond to structurally independent groups and whose edges connect the interacting groups. Each node has its set of states describing conformation and ionization of the group, and each edge is assigned an array of pairwise interaction potentials between the adjacent groups. By treating the obtained graph as a belief‐network—a well‐established mathematical abstraction—the partition function of each node is found. In the current work we used TSAR to calculate partition functions of the ionized forms of protein residues. A simplified version of a semi‐empirical molecular mechanical scoring function, borrowed from our Lead Finder docking software, was used for energy calculations. The accuracy of the resulting model was validated on a set of 486 experimentally determined pK_a values of protein residues. The average correlation coefficient (R) between calculated and experimental pK_a values was 0.80, ranging from 0.95 (for Tyr) to 0.61 (for Lys). It appeared that the hydrogen bond interactions and the exhaustiveness of side chain sampling made the most significant contribution to the accuracy of pK_a calculations. Proteins 2011; © 2011 Wiley‐Liss, Inc.     

Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

The aim of this study is to develop a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product life cycle through utilizing the capabilities of an agent‐based modeling (ABM) technique. An ABM framework is presented to model consumers’ daily product usage decisions and to assess the corresponding electricity consumption patterns. The theory of planned behavior (TPB), with the addition of the habit construct, is used to model agents’ decision‐making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total PC electricity consumption of households by 20%.     

An Approach to Prebiotic Synthesis of α-Oligoribonucleotides and Description of Their Properties: Selective Advantage of β-RNA over α-RNA

Oligomerization of α-adenosine 5′-phosphorimidazolide (α-ImpA) has been done in an aqueous solution using a uranyl-ion catalyst or a poly(U) template as a model process of prebiotic synthesis of RNA with α-glycosidic linkage. α-Oligoriboadenylates up to hexamer were formed from α-ImpA by the uranyl-ion catalyst. 3′-5′ Linkage was mainly formed in the oligomerization. The poly(U) template mediated the oligomerization of α-ImpA, but to a very low extent. The yield and chain length of the resulting α-oligomers were far lower than those of the corresponding β-oligomer formation under the same conditions. Physico-chemical properties of α-oligoriboadenylates are presented along with those of the corresponding β-oligoriboadenylates. The results indicate that β-RNA is more advantageous than α-RNA from the points of their synthesis and properties. Received: 10 February 1997 / Accepted: 31 March 1997