Showing papers by "University of Bath published in 2018"

Machine learning for molecular and materials science.

Abstract: Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

Experimental design and analysis and their reporting II: updated and simplified guidance for authors and peer reviewers

Abstract: This article updates the guidance published in 2015 for authors submitting papers to British Journal of Pharmacology (Curtis et al., 2015) and is intended to provide the rubric for peer review. Thus, it is directed towards authors, reviewers and editors. Explanations for many of the requirements were outlined previously and are not restated here. The new guidelines are intended to replace those published previously. The guidelines have been simplified for ease of understanding by authors, to make it more straightforward for peer reviewers to check compliance and to facilitate the curation of the journal's efforts to improve standards.

Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period

Abstract: Choosing a suitable sample size in qualitative research is an area of conceptual debate and practical uncertainty. That sample size principles, guidelines and tools have been developed to enable researchers to set, and justify the acceptability of, their sample size is an indication that the issue constitutes an important marker of the quality of qualitative research. Nevertheless, research shows that sample size sufficiency reporting is often poor, if not absent, across a range of disciplinary fields. A systematic analysis of single-interview-per-participant designs within three health-related journals from the disciplines of psychology, sociology and medicine, over a 15-year period, was conducted to examine whether and how sample sizes were justified and how sample size was characterised and discussed by authors. Data pertinent to sample size were extracted and analysed using qualitative and quantitative analytic techniques. Our findings demonstrate that provision of sample size justifications in qualitative health research is limited; is not contingent on the number of interviews; and relates to the journal of publication. Defence of sample size was most frequently supported across all three journals with reference to the principle of saturation and to pragmatic considerations. Qualitative sample sizes were predominantly – and often without justification – characterised as insufficient (i.e., ‘small’) and discussed in the context of study limitations. Sample size insufficiency was seen to threaten the validity and generalizability of studies’ results, with the latter being frequently conceived in nomothetic terms. We recommend, firstly, that qualitative health researchers be more transparent about evaluations of their sample size sufficiency, situating these within broader and more encompassing assessments of data adequacy. Secondly, we invite researchers critically to consider how saturation parameters found in prior methodological studies and sample size community norms might best inform, and apply to, their own project and encourage that data adequacy is best appraised with reference to features that are intrinsic to the study at hand. Finally, those reviewing papers have a vital role in supporting and encouraging transparent study-specific reporting.

Excited-state intramolecular proton-transfer (ESIPT) based fluorescence sensors and imaging agents

Abstract: In this review we will explore recent advances in the design and application of excited-state intramolecular proton-transfer (ESIPT) based fluorescent probes. Fluorescence based sensors and imaging agents (probes) are important in biology, physiology, pharmacology, and environmental science for the selective detection of biologically and/or environmentally important species. The development of ESIPT-based fluorescence probes is particularly attractive due to their unique properties, which include a large Stokes shift, environmental sensitivity and potential for ratiometric sensing.

Deep Learning for Household Load Forecasting—A Novel Pooling Deep RNN

Abstract: The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to offset uncertainties), customer classification (to cluster uncertainties) and spectral analysis (to filter out uncertainties). This paper, for the first time, aims to directly learn the uncertainty by applying a new breed of machine learning algorithms—deep learning. However, simply adding layers in neural networks will cap the forecasting performance due to the occurrence of over-fitting. A novel pooling-based deep recurrent neural network is proposed in this paper which batches a group of customers’ load profiles into a pool of inputs. Essentially the model could address the over-fitting issue by increasing data diversity and volume. This paper reports the first attempts to develop a bespoke deep learning application for household load forecasting and achieved preliminary success. The developed method is implemented on Tensorflow deep learning platform and tested on 920 smart metered customers from Ireland. Compared with the state-of-the-art techniques in household load forecasting, the proposed method outperforms ARIMA by 19.5%, SVR by 13.1% and classical deep RNN by 6.5% in terms of RMSE.

Deep video portraits

Abstract: We present a novel approach that enables photo-realistic re-animation of portrait videos using only an input video. In contrast to existing approaches that are restricted to manipulations of facial expressions only, we are the first to transfer the full 3D head position, head rotation, face expression, eye gaze, and eye blinking from a source actor to a portrait video of a target actor. The core of our approach is a generative neural network with a novel space-time architecture. The network takes as input synthetic renderings of a parametric face model, based on which it predicts photo-realistic video frames for a given target actor. The realism in this rendering-to-video transfer is achieved by careful adversarial training, and as a result, we can create modified target videos that mimic the behavior of the synthetically-created input. In order to enable source-to-target video re-animation, we render a synthetic target video with the reconstructed head animation parameters from a source video, and feed it into the trained network - thus taking full control of the target. With the ability to freely recombine source and target parameters, we are able to demonstrate a large variety of video rewrite applications without explicitly modeling hair, body or background. For instance, we can reenact the full head using interactive user-controlled editing, and realize high-fidelity visual dubbing. To demonstrate the high quality of our output, we conduct an extensive series of experiments and evaluations, where for instance a user study shows that our video edits are hard to detect.

PHIBSS: Unified Scaling Relations of Gas Depletion Time and Molecular Gas Fractions

Abstract: This paper provides an update of our previous scaling relations between galaxy-integrated molecular gas masses, stellar masses, and star formation rates (SFRs), in the framework of the star formation main sequence (MS), with the main goal of testing for possible systematic effects. For this purpose our new study combines three independent methods of determining molecular gas masses from CO line fluxes, far-infrared dust spectral energy distributions, and ∼1 mm dust photometry, in a large sample of 1444 star-forming galaxies between z=0 and 4. The sample covers the stellar mass range log(M * /M e)=9.0-11.8, and SFRs relative to that on the MS, δMS=SFR/SFR (MS), from 10 −1.3 to 10 2.2. Our most important finding is that all data sets, despite the different techniques and analysis methods used, follow the same scaling trends, once method-to-method zero-point offsets are minimized and uncertainties are properly taken into account. The molecular gas depletion time t depl , defined as the ratio of molecular gas mass to SFR, scales as (1+z) −0.6 ×(δMS) −0.44 and is only weakly dependent on stellar mass. The ratio of molecular to stellar mass μ gas depends on (* d +´´-) () () z M 1 M S 2.5 0.52 0.36 , which tracks the evolution of the specific SFR. The redshift dependence of μ gas requires a curvature term, as may the mass dependences of t depl and μ gas. We find no or only weak correlations of t depl and μ gas with optical size R or surface density once one removes the above scalings, but we caution that optical sizes may not be appropriate for the high gas and dust columns at high z.

Molecular logic gates: the past, present and future

Abstract: The field of molecular logic gates originated 25 years ago, when A. P. de Silva published a seminal article in Nature. Stimulated by this ground breaking research, scientists were inspired to join the race to simulate the workings of the fundamental components of integrated circuits using molecules. The rules of this game of mimicry were flexible, and have evolved and morphed over the years. This tutorial review takes a look back on and provides an overview of the birth and growth of the field of molecular logics. Spinning-off from chemosensor research, molecular logic gates quickly proved themselves to be more than intellectual exercises and are now poised for many potential practical applications. The ultimate goal of this vein of research became clearer only recently – to “boldly go where no silicon-based logic gate has gone before” and seek out a new deeper understanding of life inside tissues and cells.

Debunking the Myth of Exercise-induced Immune Suppression: Redefining the Impact of Exercise on Immunological Health Across the Lifespan.

Abstract: Epidemiological evidence indicates that regular physical activity and/or frequent structured exercise reduces the incidence of many chronic diseases in older age, including communicable diseases such as viral and bacterial infections, as well as non-communicable diseases such as cancer and chronic inflammatory disorders. Despite the apparent health benefits achieved by leading an active lifestyle, which imply that regular physical activity and frequent exercise enhance immune competency and regulation, the effect of a single bout of exercise on immune function remains a controversial topic. Indeed, to this day, it is perceived by many that vigorous exercise can temporarily suppress immune function. In the first part of this review, we deconstruct the key pillars which lay the foundation to this theory – referred to as the ‘open window’ hypothesis – and highlight that: (i) limited reliable evidence exists to support the claim that vigorous exercise heightens risk of opportunistic infections; (ii) purported changes to mucosal immunity, namely salivary IgA levels, after exercise do not signpost a period of immune suppression; and (iii) the dramatic reductions to lymphocyte numbers and function 1-2 hours after exercise reflects a transient and time-dependent redistribution of immune cells to peripheral tissues, resulting in a heightened state of immune surveillance and immune regulation, as opposed to immune suppression. In the second part of this review, we provide evidence that frequent exercise enhances – rather than suppresses – immune competency, and highlight key findings from human vaccination studies which show heightened responses to bacterial and viral antigens following bouts of exercise. Finally, in the third part of this review, we highlight that regular physical activity and frequent exercise might limit or delay ageing of the immune system, providing further evidence that exercise is beneficial for immunological health. In summary, the over-arching aim of this review is to rebalance opinion over the perceived relationships between exercise and immune function. We emphasise that it is a misconception to label any form of acute exercise as immunosuppressive, and, instead, exercise most likely improves immune competency across the lifespan.

Invited review article: Strategies and processes for high quality wire arc additive manufacturing

Abstract: Wire Arc Additive Manufacturing (WAAM) is attracting significant attention in industry and academia due to its ability to capture the benefits of additive manufacturing for production of large components of medium geometric complexity. Uniquely, WAAM combines the use of wire and electric arc as a fusion source to build components in a layer-by-layer approach, both of which can offer significant cost savings compared to powder and alternative fusion sources, such as laser and electron beam, respectively. Meanwhile, a high deposition rate, key for producing such components, is provided, whilst also allowing significant material savings compared to conventional manufacturing processes. However, high quality production in a wide range of materials is limited by the elevated levels of heat input which causes a number of materials processing challenges in WAAM. The materials processing challenges are fully identified in this paper to include the development of high residual stresses, undesirable microstructures, and solute segregation and phase transformations at solidification. The thermal profile during the build poses another challenge leading to heterogeneous and anisotropic material properties. This paper outlines how the materials processing challenges may be addressed in WAAM by implementation of quality improving ancillary processes. The primary WAAM process selections and ancillary processes are classified by the authors and a comprehensive review of their application conducted. Strategies by which the ancillary processes can enhance the quality of WAAM parts are presented. The efficacy and suitability of these strategies for versatile and cost effective WAAM production are discussed and a future vision of WAAM process developments provided.

Gas Permeation Properties, Physical Aging, and Its Mitigation in High Free Volume Glassy Polymers

Abstract: Hundreds of polymers have been evaluated as membrane materials for gas separations, but fewer than 10 have made it into current commercial applications, mainly due to the effects of physical aging and plasticization. Efforts to overcome these two problems are a significant focus in gas separation membrane research, in conjunction with improving membrane separation performance to surpass the Robeson upper bounds of selectivity versus permeability for commercially important gas pairs. While there has been extensive research, ranging from manipulating the chemistry of existing polymers (e.g., thermally rearranged or cross-linked polyimides) to synthesizing new polymers such as polymers of intrinsic microporosity (PIMs), there have been three major oversights that this review addresses: (1) the need to compare the approaches to achieving the best performance in order to identify their effectiveness in improving gas transport properties and in mitigating aging, (2) a common standardized aging protocol that all...

A review of self-healing concrete for damage management of structures

Abstract: The increasing concern for safety and sustainability of structures is calling for the development of smart self-healing materials and preventive repair methods. The appearance of small cracks (<300 µm in width) in concrete is almost unavoidable, not necessarily causing a risk of collapse for the structure, but surely impairing its functionality, accelerating its degradation, and diminishing its service life and sustainability. This review provides the state-of-the-art of recent developments of self-healing concrete, covering autogenous or intrinsic healing of traditional concrete followed by stimulated autogenous healing via use of mineral additives, crystalline admixtures or (superabsorbent) polymers, and subsequently autonomous self-healing mechanisms, i.e. via, application of micro-, macro-, or vascular encapsulated polymers, minerals, or bacteria. The (stimulated) autogenous mechanisms are generally limited to healing crack widths of about 100–150 µm. In contrast, most autonomous self-healing mechanisms can heal cracks of 300 µm, even sometimes up to more than 1 mm, and usually act faster. After explaining the basic concept for each self-healing technique, the most recent advances are collected, explaining the progress and current limitations, to provide insights toward the future developments. This review addresses the research needs required to remove hindrances that limit market penetration of self-healing concrete technologies.

A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots

Abstract: Genetic clustering algorithms, implemented in programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans as a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups that do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach, badMIXTURE, to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history.

Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components.

Abstract: Active infrared thermography is a fast and accurate non-destructive evaluation technique that is of particular relevance to the aerospace industry for the inspection of aircraft and helicopters’ primary and secondary structures, aero-engine parts, spacecraft components and its subsystems. This review provides an exhaustive summary of most recent active thermographic methods used for aerospace applications according to their physical principle and thermal excitation sources. Besides traditional optically stimulated thermography, which uses external optical radiation such as flashes, heaters and laser systems, novel hybrid thermographic techniques are also investigated. These include ultrasonic stimulated thermography, which uses ultrasonic waves and the local damage resonance effect to enhance the reliability and sensitivity to micro-cracks, eddy current stimulated thermography, which uses cost-effective eddy current excitation to generate induction heating, and microwave thermography, which uses electromagnetic radiation at the microwave frequency bands to provide rapid detection of cracks and delamination. All these techniques are here analysed and numerous examples are provided for different damage scenarios and aerospace components in order to identify the strength and limitations of each thermographic technique. Moreover, alternative strategies to current external thermal excitation sources, here named as material-based thermography methods, are examined in this paper. These novel thermographic techniques rely on thermoresistive internal heating and offer a fast, low power, accurate and reliable assessment of damage in aerospace composites.

Inducing High Ionic Conductivity in the Lithium Superionic Argyrodites Li6+xP1–xGexS5I for All-Solid-State Batteries

Abstract: Solid-state batteries with inorganic solid electrolytes are currently being discussed as a more reliable and safer future alternative to the current lithium-ion battery technology. To compete with ...

Survey of computational intelligence as basis to big flood management: challenges, research directions and future work

Abstract: Flooding produces debris and waste including liquids, dead animal bodies and hazardous materials such as hospital waste. Debris causes serious threats to people’s health and can even block the road...

Dispositional Mindfulness and Psychological Health: a Systematic Review

Abstract: Interest in the influence of dispositional mindfulness (DM) on psychological health has been gathering pace over recent years. Despite this, a systematic review of this topic has not been conducted. A systematic review can benefit the field by identifying the terminology and measures used by researchers and by highlighting methodological weaknesses and empirical gaps. We systematically reviewed non-interventional, quantitative papers on DM and psychological health in non-clinical samples published in English up to June 2016, following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. A literature search was conducted using PsycINFO, PubMED, Medline and Embase, and 93 papers met the inclusion criteria. Within these, three main themes emerged, depicting the relationship between DM and psychological health: (1) DM appears to be inversely related to psychopathological symptoms such as depressive symptoms, (2) DM is positively linked to adaptive cognitive processes such as less rumination and pain catastrophizing and (3) DM appears to be associated with better emotional processing and regulation. These themes informed the creation of a taxonomy. We conclude that research has consistently shown a positive relationship between DM and psychological health. Suggestions for future research and conceptual and methodological limitations within the field are discussed.

Compositional data analysis for physical activity, sedentary time and sleep research

Abstract: The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children's daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.

A Review of the Evolution of Vision-Based Motion Analysis and the Integration of Advanced Computer Vision Methods Towards Developing a Markerless System

Abstract: The study of human movement within sports biomechanics and rehabilitation settings has made considerable progress over recent decades. However, developing a motion analysis system that collects accurate kinematic data in a timely, unobtrusive and externally valid manner remains an open challenge. This narrative review considers the evolution of methods for extracting kinematic information from images, observing how technology has progressed from laborious manual approaches to optoelectronic marker-based systems. The motion analysis systems which are currently most widely used in sports biomechanics and rehabilitation do not allow kinematic data to be collected automatically without the attachment of markers, controlled conditions and/or extensive processing times. These limitations can obstruct the routine use of motion capture in normal training or rehabilitation environments, and there is a clear desire for the development of automatic markerless systems. Such technology is emerging, often driven by the needs of the entertainment industry, and utilising many of the latest trends in computer vision and machine learning. However, the accuracy and practicality of these systems has yet to be fully scrutinised, meaning such markerless systems are not currently in widespread use within biomechanics. This review aims to introduce the key state-of-the-art in markerless motion capture research from computer vision that is likely to have a future impact in biomechanics, while considering the challenges with accuracy and robustness that are yet to be addressed.

The outflow structure of GW170817 from late-time broad-band observations

Abstract: We present our broad-band study of GW170817 from radio to hard X-rays, including NuSTAR and Chandra observations up to 165 d after the merger, and a multimessenger analysis including LIGO constraints. The data are compared with predictions from a wide range of models, providing the first detailed comparison between non-trivial cocoon and jet models. Homogeneous and power-law shaped jets, as well as simple cocoon models are ruled out by the data, while both a Gaussian shaped jet and a cocoon with energy injection can describe the current data set for a reasonable range of physical parameters, consistent with the typical values derived from short GRB afterglows. We propose that these models can be unambiguously discriminated by future observations measuring the post-peak behaviour, with F_ν ∝ t^(∼−1.0) for the cocoon and F_ν∝ t^(∼−2.5) for the jet model.

Construction of Bi2WO6/RGO/g-C3N4 2D/2D/2D hybrid Z-scheme heterojunctions with large interfacial contact area for efficient charge separation and high-performance photoreduction of CO2 and H2O into solar fuels

Abstract: We have rationally constructed a hybrid heterojunction comprising of Bi2WO6, reduced graphene oxide, and g-C3N4 (BWO/RGO/CN) with a 2D/2D/2D configuration for efficient photoreduction to generate solar fuels. These heterojunctions displayed dramatically improved performance towards CO2 reduction to generate CO and CH4 under visible-light irradiation, compared to the base material (CN), P25 as reference, as well as binary BWO/CN and RGO/CN heterojunctions. Particularly, the BWO/RGO/CN heterojunctions with 1 wt. % RGO and 15 wt. % BWO achieved record performance in the yields of carbonaceous products (CO + CH4) compared to other synthesized catalysts, with a selectivity of 92% against H2. The remarkable photocatalytic performance was mainly attributed to the unique 2D/2D/2D architecture that creates large interfacial contact between the constituent materials for rapid charge transfer, to hinder the direct recombination of photoinduced electrons and holes. Notably, RGO played two significant roles: as a supporter to capture the electrons from CN, and as a redox mediator to promote the Z-scheme charge transfer between CN and BWO. The result is a greater extent of charge separation in the present BWO/RGO/CN heterojunction system, as evidenced by the photoluminescence, photocurrent responses, and electron microscopy findings. More importantly, the heterojunctions displayed excellent stability during recycling tests with no obvious loss in the generation of CO and CH4 from photoreduction of CO2. This interesting interfacial engineering approach presented herein offers a promising route for the rational design of a new class of layered multicomponent heterojunctions with 2D/2D/2D architecture for various applications in environmental protection and solar energy conversion.

Integrated genomic and fossil evidence illuminates life's early evolution and eukaryote origin.

Abstract: Establishing a unified timescale for the early evolution of Earth and life is challenging and mired in controversy because of the paucity of fossil evidence, the difficulty of interpreting it and dispute over the deepest branching relationships in the tree of life. Surprisingly, it remains perhaps the only episode in the history of life where literal interpretations of the fossil record hold sway, revised with every new discovery and reinterpretation. We derive a timescale of life, combining a reappraisal of the fossil material with new molecular clock analyses. We find the last universal common ancestor of cellular life to have predated the end of late heavy bombardment (>3.9 billion years ago (Ga)). The crown clades of the two primary divisions of life, Eubacteria and Archaebacteria, emerged much later (<3.4 Ga), relegating the oldest fossil evidence for life to their stem lineages. The Great Oxidation Event significantly predates the origin of modern Cyanobacteria, indicating that oxygenic photosynthesis evolved within the cyanobacterial stem lineage. Modern eukaryotes do not constitute a primary lineage of life and emerged late in Earth’s history (<1.84 Ga), falsifying the hypothesis that the Great Oxidation Event facilitated their radiation. The symbiotic origin of mitochondria at 2.053–1.21 Ga reflects a late origin of the total-group Alphaproteobacteria to which the free living ancestor of mitochondria belonged.

RADpainter and fineRADstructure: Population Inference from RADseq Data.

Abstract: Powerful approaches to inferring recent or current population structure based on nearest neighbor haplotype "coancestry" have so far been inaccessible to users without high quality genome-wide haplotype data. With a boom in nonmodel organism genomics, there is a pressing need to bring these methods to communities without access to such data. Here, we present RADpainter, a new program designed to infer the coancestry matrix from restriction-site-associated DNA sequencing (RADseq) data. We combine this program together with a previously published MCMC clustering algorithm into fineRADstructure-a complete, easy to use, and fast population inference package for RADseq data (https://github.com/millanek/fineRADstructure; last accessed February 24, 2018). Finally, with two example data sets, we illustrate its use, benefits, and robustness to missing RAD alleles in double digest RAD sequencing.

Non-invasive, transdermal, path-selective and specific glucose monitoring via a graphene-based platform

Abstract: Currently, there is no available needle-free approach for diabetics to monitor glucose levels in the interstitial fluid. Here, we report a path-selective, non-invasive, transdermal glucose monitoring system based on a miniaturized pixel array platform (realized either by graphene-based thin-film technology, or screen-printing). The system samples glucose from the interstitial fluid via electroosmotic extraction through individual, privileged, follicular pathways in the skin, accessible via the pixels of the array. A proof of principle using mammalian skin ex vivo is demonstrated for specific and ‘quantized’ glucose extraction/detection via follicular pathways, and across the hypo- to hyper-glycaemic range in humans. Furthermore, the quantification of follicular and non-follicular glucose extraction fluxes is clearly shown. In vivo continuous monitoring of interstitial fluid-borne glucose with the pixel array was able to track blood sugar in healthy human subjects. This approach paves the way to clinically relevant glucose detection in diabetics without the need for invasive, finger-stick blood sampling.

Atomic-Scale Influence of Grain Boundaries on Li-Ion Conduction in Solid Electrolytes for All-Solid-State Batteries.

Abstract: Solid electrolytes are generating considerable interest for all-solid-state Li-ion batteries to address safety and performance issues. Grain boundaries have a significant influence on solid electrolytes and are key hurdles that must be overcome for their successful application. However, grain boundary effects on ionic transport are not fully understood, especially at the atomic scale. The Li-rich anti-perovskite Li3OCl is a promising solid electrolyte, although there is debate concerning the precise Li-ion migration barriers and conductivity. Using Li3OCl as a model polycrystalline electrolyte, we apply large-scale molecular dynamics simulations to analyze the ionic transport at stable grain boundaries. Our results predict high concentrations of grain boundaries and clearly show that Li-ion conductivity is severely hindered through the grain boundaries. The activation energies for Li-ion conduction traversing the grain boundaries are consistently higher than that of the bulk crystal, confirming the high g...