Microscopic Steps Research Articles

The role of shear forces in primary and secondary nucleation of amyloid fibrils

Shear forces affect self-assembly processes ranging from crystallization to fiber formation. Here, the effect of mild agitation on amyloid fibril formation was explored for four peptides and investigated in detail for A[Formula: see text]42, which is associated with Alzheimer's disease. To gain mechanistic insights into the effect of mild agitation, nonseeded and seeded aggregation reactions were set up at various peptide concentrations with and without an inhibitor. First, an effect on fibril fragmentation was excluded by comparing the monomer-concentration dependence of aggregation kinetics under idle and agitated conditions. Second, using a secondary nucleation inhibitor, Brichos, the agitation effect on primary nucleation was decoupled from secondary nucleation. Third, an effect on secondary nucleation was established in the absence of inhibitor. Fourth, an effect on elongation was excluded by comparing the seeding potency of fibrils formed under idle or agitated conditions. We find that both primary and secondary nucleation steps are accelerated by gentle agitation. The increased shear forces facilitate both the detachment of newly formed aggregates from catalytic surfaces and the rate at which molecules are transported in the bulk solution to encounter nucleation sites on the fibril and other surfaces. Ultrastructural evidence obtained with cryogenic transmission electron microscopy and free-flow electrophoresis in microfluidics devices imply that agitation speeds up the detachment of nucleated species from the fibril surface. Our findings shed light on the aggregation mechanism and the role of detachment for efficient secondary nucleation. The results inform on how to modulate the relative importance of different microscopic steps in drug discovery and investigations.

Non-destructive measurement of MUCT in micro-milling using surface topography generated by bi-planer size effects

In mechanical micro-cutting, a Minimum Undeformed Chip Thickness (MUCT) is desired to ensure chip formation by the round-edged tool. Although the MUCT controls several machinability, productivity, and sustainability attributes, its measurement using output responses is a challenging task. This article, for the first time, demonstrates a non-destructive methodology to measure MUCT in micro-milling using the topographical pattern that inherently remains embedded on the micro-milled floor surface in the form of a microscopic step at the ploughing-shearing transition boundary. Simultaneous action of two Size Effect phenomena that occur concurrently in two mutually perpendicular planes owing to rounded-nose and rounded-edge produce microscopic step during surface generation. A methodology to quantify MUCT using this inconsistent surface topography is also demonstrated. MUCT remains within 36–41 % of the edge radius during dry micro-milling of Ti-6Al-4V using TiAlN-coated WC-6Co tool. The same reduces to 33–40 % of the edge radius when cutting fluid is delivered through sustainable Minimum Quantity Lubrication (MQL) strategy. Proportionality between MUCT and edge radius remains valid during abrasive wear regime of the cutting tool. Tool wear significantly deteriorates surface quality, causing Ra roughness to increase from 40 to 350 nm when adhesion deposits on cutting edge. Consequently, the proposed surface-dependent methodology fails to provide precise MUCT data when cutting tool experiences aggressive wear.

Microscopic identification of foodborne bacterial pathogens based on deep learning method

Accurate and rapid detection of foodborne bacterial pathogens is critical for food quality control. Nowadays, tracking morphological bacterial properties using microscope is still a priority at the grass-roots food supervision department due to its simplicity and low cost. However, the method requires highly professional personnel and there are certain misjudgments in the process of analysis. Automatically recognizing foodborne pathogen using deep learning algorithm to replace manual microscopy will not only reduce expert cost, artificial misjudgment, and operation time in detection, but also provide more objective and accurate identification. Here, we firstly constructed a high-quality and large-scale dataset of foodborne pathogenic bacteria, allowing the deep learning-based model to be efficiently trained and achieve accurate identification. The deep convolutional neural network-based model is capable of identifying six common foodborne pathogens, including Escherichia coli (O157:H7), Vibrio parahaemolyticus, Staphylococcus aureus, Bacillus cereus, Salmonella typhi, and Streptococcus hemolyticus, with accuracy rates of 90%–100%. This method can assist or replace the manual microscopic inspection step in traditional detection methods, and is promising to break through the traditional approach that heavily relies on manual judgment, greatly reduce the cost of experts and human errors, and provide rapid, accurate, and powerful discriminatory results in large quantities for detection.

Comprehensive perspective towards the management of proteinopathies by elucidating protein misfolding and aggregation.

Protein misfolding and aggregation is the phenomenon of the generic propensity of proteins, considered as a dark side of the protein world, and its exact mechanism is still not deciphered. Understanding the complexity of protein aggregation is currently the primary apprehension and challenge in biology and medicine due to their association with various debilitating human proteinopathies and neurodegenerative diseases. The mechanism of protein aggregation, associated diseases, and the development of efficient therapeutic strategies against these diseases are very challenging. These diseases are caused by different proteins, each protein with different mechanisms and consisting of various microscopic phases or events. These microscopic steps are functioning on different timescales during aggregation. Here, we highlighted the different features and current trends in protein aggregation. The study thoroughly recapitulates the various factors influencing, possible causes, types of aggregates and aggregation, their different proposed mechanisms, and the methods used to study the aggregation. Additionally, the formation and elimination of misfolded or aggregated proteins in the cell, the role of the ruggedness of the protein folding landscape in protein aggregation, proteinopathies, and the challenges for their prevention are comprehensively elucidated. A holistic understanding of different aspects of aggregation, molecular steps governing the various features of protein quality control, and crucial queries about the modulation of these processes and their interactions with other systems in cellular protein quality control can be considered conducive to comprehending the mechanism, designing effective approaches towards prevention of protein aggregation, rationalizing the etiology and development of novel strategies against therapy and management of the proteinopathies.

Understanding the Energetics of Ion Intercalation in Lithium-Ion Batteries

Researchers around the world are working to increase the energy efficiency and the energy density of lithium-ion batteries. However, the mechanism and the factors influencing the charge transfer (CT) kinetics at the electrode-electrolyte interface remain poorly understood. Recently, Fraggedakis et al. [1] proposed the theory of coupled ion-electron transfer (CIET) to explain the process of charge transfer at the electrode-electrolyte interfaces. In this work, we provide deep atomistic understanding of the interfacial CT mechanism, the underlying microscopic steps, and the factors influencing the CT rates in a Li-ion battery. In addition, we connect our computational results with the experimental measurements and Marcus-like theories of charge transfer (viz. CIET [1]).Using state-of-the-art computational techniques, such as metadynamics and molecular dynamics simulations, we model the electrode-electrolyte interface and compute the free energy profiles of Li-ion adsorption at the interface, subsequent ion-desolvation, and intercalation into the cathode. Specifically, we study the adsorption of Li+ ion on LixCoO2 surface for different (i) electrolytes, (ii) Li+ concentrations in electrolyte, (iii) salt compositions, and (iv) temperatures to uncover the trends governing charge transfer kinetics. Using the obtained free energy profiles of Li+ desolvation and intercalation at the solid-liquid interface, we provide estimation of the adsorption and desolvation energy at the interface and identify the key energy barrier which acts as the roadblock for ion transfer in Li-ion batteries. Based on this identified key kinetic barrier, we then propose strategies to tune the energy barrier for ion transport. In addition, we identify important thermo-physical observations that can explain the existing experimental trends. For instance, we find that increasing the salt concentration in the electrolyte increases the accessible solvation states to Li+ ion, thereby changing the energy barrier for the Li+ ion to intercalate into the electrode, and thus leading to higher currents. Moreover, we find that changing the salt from LiPF6 to LiClO4 further modifies the energy landscape of Li+ ion, leading to increased measured experimental kinetics as well. This work builds an understanding of the influence of various effects, such as salt concentration and electrolyte composition, on the Li+ transport properties at interfacial regions. Our computational framework can also provide descriptors to enhance the performance and stability of lithium-ion batteries.

Dynamic structure factors of polymer melts as observed by neutron spin echo: Direct comparison and reevaluation.

In this work, we compare the single chain dynamic structure factors for five different polymers: polyolefins (PE and PEP), poly-dienes (PB and PI), and a polyether (PEO). For this purpose, we have extended the De Gennes approximation for the dynamic structure factor. We describe the single chain dynamic structure factor in multiplying the coherent scattering functions for local reptation and Rouse motion within the Rouse blob. Important results are (i) the simple De Gennes structure factor S(Q, t)DG approximates within a few Å the outcome for the tube diameter of the more elaborate structure factor (exception PI); (ii) the extended De Gennes structure factor together with the Rouse blob describes the neutron spin echo spectra from the different polymers over the complete momentum transfer range and the full time regime from early Rouse motion to local reptation; and (iii) the representation of the scattering functions could significantly be improved by introducing non-Gaussianity corrections to the Rouse-blob dynamics. (iv) The microscopic tube step length in all cases is significantly larger than the rheological one; further tweaking the relation between tube length and entanglement blob size may indicate a possible trend toward an anisotropic lean tube with a step-length larger than the lateral extension. (v) All considered polymer data coincide after proper (Q, t) scaling to a universal behavior according to the length scale of the tube, while the relevant time scale is the entanglement time τe. (vi) In terms of the packing model, the required number of chains spanning the entanglement volume consistently is about 40% larger than that obtained from rheology.

Influence of the substrate treatment on the microstructure and properties of chemical vapour deposited Ti(C,N) coatings

The effect of the mechanical treatment on the surface morphology of cemented carbide substrates and on the microstructure and properties of chemical vapour deposited (CVD) Ti(C,N) coatings is described in terms of the functional relationships between the substrate surface roughness, and the grain size, preferred orientation of crystallites, residual stress, indentation hardness and adhesion of the coatings. The substrates were flat fine-grained and coarse-grained cemented carbides inserts that underwent different treatments – wet blasting, grinding or polishing. Although the Ti(C,N) coatings were produced in the same moderate-temperature deposition process, their microstructure characteristics and mechanical properties differed significantly. Microscopic steps and edges present on ‘rough’ substrates facilitated the growth of large V-shaped Ti(C,N) grains with a weak {211} texture. In these samples, the tensile residual stress that is typically produced during the cooling of the CVD samples was reduced. The Ti(C,N) coatings deposited on ‘smooth’ substrates were fine-grained, and possessed a pronounced {211} texture and a better adhesion to the substrate. In these samples, the thermal tensile stress was less reduced than in the samples deposited on ‘rough’ substrates. The indentation hardness of the Ti(C,N) coatings was not affected by the substrate treatment. The physical background of these relationships is explained.

Spontaneous nucleation and fast aggregate-dependent proliferation of α-synuclein aggregates within liquid condensates at neutral pH

The aggregation of α-synuclein into amyloid fibrils has been under scrutiny in recent years because of its association with Parkinson's disease. This process can be triggered by a lipid-dependent nucleation process, and the resulting aggregates can proliferate through secondary nucleation under acidic pH conditions. It has also been recently reported that the aggregation of α-synuclein may follow an alternative pathway, which takes place within dense liquid condensates formed through phase separation. The microscopic mechanism of this process, however, remains to be clarified. Here, we used fluorescence-based assays to enable a kinetic analysis of the microscopic steps underlying the aggregation process of α-synuclein within liquid condensates. Our analysis shows that at pH 7.4, this process starts with spontaneous primary nucleation followed by rapid aggregate-dependent proliferation. Our results thus reveal the microscopic mechanism of α-synuclein aggregation within condensates through the accurate quantification of the kinetic rate constants for the appearance and proliferation of α-synuclein aggregates at physiological pH.

Direct In Situ Measurement of Quantum Efficiencies of Charge Separation and Proton Reduction at TiO2-Protected GaP Photocathodes.

Photoelectrochemical solar fuel generation at the semiconductor/liquid interface consists of multiple elementary steps, including charge separation, recombination, and catalytic reactions. While the overall incident light-to-current conversion efficiency (IPCE) can be readily measured, identifying the microscopic efficiency loss processes remains difficult. Here, we report simultaneous in situ transient photocurrent and transient reflectance spectroscopy (TRS) measurements of titanium dioxide-protected gallium phosphide photocathodes for water reduction in photoelectrochemical cells. Transient reflectance spectroscopy enables the direct probe of the separated charge carriers responsible for water reduction to follow their kinetics. Comparison with transient photocurrent measurement allows the direct probe of the initial charge separation quantum efficiency (ϕCS) and provides support for a transient photocurrent model that divides IPCE into the product of quantum efficiencies of light absorption (ϕabs), charge separation (ϕCS), and photoreduction (ϕred), i.e., IPCE = ϕabsϕCSϕred. Our study shows that there are two general key loss pathways: recombination within the bulk GaP that reduces ϕCS and interfacial recombination at the junction that decreases ϕred. Although both loss pathways can be reduced at a more negative applied bias, for GaP/TiO2, the initial charge separation loss is the key efficiency limiting factor. Our combined transient reflectance and photocurrent study provides a time-resolved view of microscopic steps involved in the overall light-to-current conversion process and provides detailed insights into the main loss pathways of the photoelectrochemical system.

Measurement of kinetic isotope effects on peptide hydroxylation using MALDI-MS.

Primary kinetic isotope effects (KIEs) provide unique insight into enzymatic reactions, as they can reveal rate-limiting steps and detailed chemical mechanisms. HIF hydroxylases, part of a family of 2-oxoglutarate (2OG) oxygenases are central to the regulation of many crucial biological processes through O2-sensing, but present a challenge to monitor due to the large size of the protein substrate and the similarity between native and hydroxylated substrate. MALDI-TOF MS is a convenient tool to measure peptide masses, which can also be used to measure the discontinuous kinetics of peptide hydroxylation for Factor Inhibiting HIF (FIH). Using this technique, rate data can be observed from the mole-fraction of CTAD and CTAD-OH in small volumes, allowing noncompetitive H/D KIEs to be measured. Slow dCTAD substrate leads to extensive uncoupling of O2 consumption from peptide hydroxylation, leading to enzyme autohydroxylation, which is observed using UV-vis spectroscopy. Simultaneously measuring both the normal product, CTAD-OH, and the uncoupled product, autohydroxylated enzyme, the KIE on the microscopic step of hydrogen atom transfer (HAT) can be estimated. MALDI-MS analysis is a strong method for monitoring reactions that hydroxylate peptides, and can be generalized to other similar reactions, and simultaneous kinetic detection of branched products can provide valuable insight on microscopic KIEs at intermediate mechanistic steps.

Measurement of specular surfaces using electrically tunable lens in digital holography

In the field of industrial metrology, the 3D nondestructive imaging of reflective metallic surfaces is a delicate task. In this work, we propose a novel application of the electrically tunable lens (ETL) in digital holography for imaging specularly reflecting objects. The precise surface profile of the microscopic step height at different axial depths is obtained by tuning the liquid lens at different currents. Initially, the ETL’s focal length is set by tuning its control current to image the specular reflection observed from the surface of the reflecting sample. The current of the ETL is tuned accordingly as the sample is moved to different z-positions. In order to demonstrate the efficacy of the proposed setup, the object is kept at multiple axial distances within the depth of field of the ETL. The step height measurements are carried out and a measurement uncertainty of 0.083 µm is calculated for step height measurements at different axial positions ranging from 2 cm–21 cm. The axial range of the setup is validated by keeping two specularly reflecting samples in the field of view of the ETL. The experimental results demonstrate the ETL’s efficiency in a digital holographic system for accurately imaging specularly reflecting objects present at multiple axial depths. The setup is useful for precise step height measurements and for obtaining surface profiles of microstructures.

Influence of denaturants on amyloid β42 aggregation kinetics.

Amyloid formation is linked to devastating neurodegenerative diseases, motivating detailed studies of the mechanisms of amyloid formation. For Aβ, the peptide associated with Alzheimer’s disease, the mechanism and rate of aggregation have been established for a range of variants and conditions in vitro and in bodily fluids. A key outstanding question is how the relative stabilities of monomers, fibrils and intermediates affect each step in the fibril formation process. By monitoring the kinetics of aggregation of Aβ42, in the presence of urea or guanidinium hydrochloride (GuHCl), we here determine the rates of the underlying microscopic steps and establish the importance of changes in relative stability induced by the presence of denaturant for each individual step. Denaturants shift the equilibrium towards the unfolded state of each species. We find that a non-ionic denaturant, urea, reduces the overall aggregation rate, and that the effect on nucleation is stronger than the effect on elongation. Urea reduces the rate of secondary nucleation by decreasing the coverage of fibril surfaces and the rate of nucleus formation. It also reduces the rate of primary nucleation, increasing its reaction order. The ionic denaturant, GuHCl, accelerates the aggregation at low denaturant concentrations and decelerates the aggregation at high denaturant concentrations. Below approximately 0.25 M GuHCl, the screening of repulsive electrostatic interactions between peptides by the charged denaturant dominates, leading to an increased aggregation rate. At higher GuHCl concentrations, the electrostatic repulsion is completely screened, and the denaturing effect dominates. The results illustrate how the differential effects of denaturants on stability of monomer, oligomer and fibril translate to differential effects on microscopic steps, with the rate of nucleation being most strongly reduced.

Effects of N-terminal Acetylation on the Aggregation of Disease-related α-synuclein Variants

Mutations in the SNCA gene, which encodes the protein α-synuclein, have been linked with early onset Parkinson’s disease. The exact nature of this association, however, is still poorly understood. To investigate this problem, we started from the observation that α-synuclein is constitutively N-terminally acetylated, a post-translational modification that alters the charge and structure of α-synuclein molecules and affects their interaction with lipid membranes, as well as their aggregation process. We thus studied five N-terminal acetylated familial variants (A30P, E46K, H50Q, G51D and A53T) of α-synuclein through a wide range of biophysical assays to probe the microscopic steps in their aggregation process and the structures of the resulting aggregates. Our results reveal a great complexity in the combined effects of the disease-related mutations with N-terminal acetylation on the aggregation of α-synuclein, which underscores the great sensitivity to even relatively small perturbations of the behaviour of this protein.

Kinetic profiling of therapeutic strategies for inhibiting the formation of amyloid oligomers.

Protein self-assembly into amyloid fibrils underlies several neurodegenerative conditions, including Alzheimer's and Parkinson's diseases. It has become apparent that the small oligomers formed during this process constitute neurotoxic molecular species associated with amyloid aggregation. Targeting the formation of oligomers represents, therefore, a possible therapeutic avenue to combat these diseases. However, it remains challenging to establish which microscopic steps should be targeted to suppress most effectively the generation of oligomeric aggregates. Recently, we have developed a kinetic model of oligomer dynamics during amyloid aggregation. Here, we use this approach to derive explicit scaling relationships that reveal how key features of the time evolution of oligomers, including oligomer peak concentration and lifetime, are controlled by the different rate parameters. We discuss the therapeutic implications of our framework by predicting changes in oligomer concentrations when the rates of the individual microscopic events are varied. Our results identify the kinetic parameters that control most effectively the generation of oligomers, thus opening a new path for the systematic rational design of therapeutic strategies against amyloid-related diseases.

A Protein Corona Modulates Interactions of α-Synuclein with Nanoparticles and Alters the Rates of the Microscopic Steps of Amyloid Formation.

Nanoparticles (NPs) can modulate protein aggregation and fibril formation in the context of amyloid diseases. Understanding the mechanism of this action remains a critical next step in developing nanomedicines for the treatment or prevention of Parkinson's disease. α-Synuclein (α-Syn) can undergo interactions of different strength with nanoparticles, and these interactions can be prevented by the presence of a protein corona (PC) acquired during the exposure of NPs to serum proteins. Here, we develop a method to attach the PC irreversibly to the NPs, which enables us to study in detail the interaction of α-Syn and polyethylenimine-coated carboxyl-modified polystyrene NPs (PsNPs-PEI) and the role of the dynamics of the interactions. Analysis of the kinetics of fibril formation reveals that the NPs surface promotes the primary nucleation step of amyloid fibril formation without significantly affecting the elongation and fragmentation steps or the final equilibrium. Furthermore, the results show that even though α-Syn can access the surface of NPs that are precoated with a PC, due to the dynamic nature of the PC proteins, the PC nevertheless reduces the acceleratoring effect of the NPs. This effect is likely to be caused by reducing the overall amount of weakly interacting α-Syn molecules on the NP surface and the access of further α-Syn required for fibril elongation. Our experimental approach provides microscopic insight into how serum proteins can modulate the complex interplay between NPs and amyloid proteins.

A Beam-Splitting Bianisotropic Metasurface Designed by Optimization and Machine Learning

Electromagnetic metasurfaces have attracted significant interest recently due to their low profile and advantageous applications. Practically, many metasurface designs start with a set of constraints for the radiated far-field, such as main-beam direction(s) and side lobe levels, and end with a non-uniform physical structure for the surface. This problem is quite challenging, since the required tangential field transformations are not completely known when only constraints are placed on the scattered fields. Hence, the required surface properties cannot be solved for analytically. Moreover, the translation of the desired surface properties to the physical unit cells can be time-consuming and difficult, as it is often a one-to-many mapping in a large solution space. Here, we divide the inverse design process into two steps: a macroscopic and microscopic design step. In the former, we use an iterative optimization process to find the surface properties that radiate a far-field pattern that complies with specified constraints. This iterative process exploits non-radiating currents to ensure a passive and lossless design. In the microscopic step, these optimized surface properties are realized with physical unit cells using machine learning surrogate models. The effectiveness of this end-to-end synthesis process is demonstrated through measurement results of a beam-splitting prototype.

Molecular mechanisms of amyloid formation in living systems.

Fibrillar protein aggregation is a hallmark of a variety of human diseases. Examples include the deposition of amyloid-β and tau in Alzheimer's disease, and that of α-synuclein in Parkinson's disease. The molecular mechanisms by which soluble proteins form amyloid fibrils have been extensively studied in the test tube. These investigations have revealed the microscopic steps underlying amyloid formation, and the role of factors such as chaperones that modulate these processes. This perspective explores the question to what extent the mechanisms of amyloid formation elucidated in vitro apply to human disease. The answer is not yet clear, and may differ depending on the protein and the associated disease. Nevertheless, there are striking qualitative similarities between the aggregation behaviour of proteins in vitro and the development of the related diseases. Limited quantitative data obtained in model organisms such as Caenorhabditis elegans support the notion that aggregation mechanisms in vivo can be interpreted using the same biophysical principles established in vitro. These results may however be biased by the high overexpression levels typically used in animal models of protein aggregation diseases. Molecular chaperones have been found to suppress protein aggregation in animal models, but their mechanisms of action have not yet been quantitatively analysed. Several mechanisms are proposed by which the decline of protein quality control with organismal age, but also the intrinsic nature of the aggregation process may contribute to the kinetics of protein aggregation observed in human disease.

Surface-Catalyzed Secondary Nucleation Dominates the Generation of Toxic IAPP Aggregates.

The aggregation of the human islet amyloid polypeptide (IAPP) is associated with diabetes type II. A quantitative understanding of this connection at the molecular level requires that the aggregation mechanism of IAPP is resolved in terms of the underlying microscopic steps. Here we have systematically studied recombinant IAPP, with amidated C-terminus in oxidised form with a disulphide bond between residues 3 and 7, using thioflavin T fluorescence to monitor the formation of amyloid fibrils as a function of time and IAPP concentration. We used global kinetic analyses to connect the macroscopic measurements of aggregation to the microscopic mechanisms, and show that the generation of new aggregates is dominated by the secondary nucleation of monomers on the fibril surface. We then exposed insulinoma cells to aliquots extracted from different time points of the aggregation process, finding the highest toxicity at the midpoint of the reaction, when the secondary nucleation rate reaches its maximum. These results identify IAPP oligomers as the most cytotoxic species generated during IAPP aggregation, and suggest that compounds that target secondary nucleation of IAPP could be most effective as therapeutic candidates for diabetes type II.

Three-level hybrid modeling for systematic optimization of biocatalytic synthesis: α-glucosyl glycerol production by enzymatic trans-glycosylation from sucrose.

Mechanism‐based kinetic models are rigorous tools to analyze enzymatic reactions, but their extension to actual conditions of the biocatalytic synthesis can be difficult. Here, we demonstrate (mechanistic‐empirical) hybrid modeling for systematic optimization of the sucrose phosphorylase‐catalyzed glycosylation of glycerol from sucrose, to synthesize the cosmetic ingredient α‐glucosyl glycerol (GG). The empirical model part was developed to capture nonspecific effects of high sucrose concentrations (up to 1.5 M) on microscopic steps of the enzymatic trans‐glycosylation mechanism. Based on verified predictions of the enzyme performance under initial rate conditions (Level 1), the hybrid model was expanded by microscopic terms of the reverse reaction to account for the full‐time course of GG synthesis (Level 2). Lastly (Level 3), the application of the hybrid model for comprehensive window‐of‐operation analysis and constrained optimization of the GG production (~250 g/L) was demonstrated. Using two candidate sucrose phosphorylases (from Leuconostoc mesenteroides and Bifidobacterium adolescentis), we reveal the hybrid model as a powerful tool of “process decision making” to guide rational selection of the best‐suited enzyme catalyst. Our study exemplifies a closing of the gap between enzyme kinetic models considered for mechanistic research and applicable in technologically relevant reaction conditions; and it highlights the important benefit thus realizable for biocatalytic process development.

(Invited) Entropy-Enhanced Ion Transport in Solid Electrolytes

Long-range ion transport is composed of microscopic steps of ion migration, which is governed by local structures and interactions of the charge carriers with their surroundings. Therefore, understanding the local environments of conducting ions and their impact on ion dynamics and transport pathways are critical to design of high-performance solid electrolytes. We have synthesized and studied a variety of Li superionic conductors. Systematic solid-state nuclear magnetic resonance (NMR) investigations, complemented by pair distribution analysis (PDF) and DFT/MD simulations, have revealed that entropies in structures, compositions, and Li-coordination play a key role in determining ion hoping frequencies, jumping distance, transport pathways, and activation barriers. Via maximizing these entropies, “liquid-like” Li-sublattice is produced with a flattened energy landscape yielding extremely low activation barrier for ion transport. A few such examples will be discussed, including glass, ceramic, and glass-ceramic composites.