Ab initio structure prediction methods for battery materials a review of recent computational efforts to predict the atomic level structure and bonding in materials for rechargeable batteries

Portable electronic devices, electric vehicles and stationary energy storage applications, which encourage carbon-neutral energy alternatives, are driving demand for batteries that have concurrently higher energy densities, faster charging rates, safer operation and lower prices. These demands can no longer be met by incrementally improving existing technologies but require the discovery of new materials with exceptional properties. Experimental materials discovery is both expensive and time consuming: before the efficacy of a new battery material can be assessed, its synthesis and stability must be well-understood. Computational materials modelling can expedite this process by predicting novel materials, both in stand-alone theoretical calculations and in tandem with experiments. In this review, we describe a materials discovery framework based on density functional theory (DFT) to predict the properties of electrode and solid-electrolyte materials and validate these predictions experimentally. First, we discuss crystal structure prediction using the Ab initio random structure searching (AIRSS) method. Next, we describe how DFT results allow us to predict which phases form during electrode cycling, as well as the electrode voltage profile and maximum theoretical capacity. We go on to explain how DFT can be used to simulate experimentally measurable properties such as nuclear magnetic resonance (NMR) spectra and ionic conductivities. We illustrate the described workflow with multiple experimentally validated examples: materials for lithium-ion and sodium-ion anodes and lithium-ion solid electrolytes. These examples highlight the power of combining computation with experiment to advance battery materials research.(1) Gates Cambridge Trust, University of Cambridge, UK (2) EPSRC Centre for Doctoral Training in Computational Methods for Materials Science, UK, Grant No. EP/L015552/1. (3) Winton Programme for the Physics of Sustainability, University of Cambridge, UK (4) Sims Fund, University of Cambridge, UK (5) EPSRC Grant No. EP/P003532/1 (6) EPSRC Collaborative Computational Projects on the Electronic Structure of Condensed Matter (CCP9), Grant No. EP/M022595/1, and NMR crystallography, Grant No. EP/M022501/1 (7) Computing resources on the Tier 1 resource ARCHER were provided through the UKCP EPSRC High-End computational consortium (EP/P022561/1) and on the Tier 2 resources HPC Midlands+ (EP/P020232/1) and CSD3 (EP/P020259/1)

Mean-risk models using two risk measures: A multi-objective approach

This paper proposes a model for portfolio optimisation, in which distributions are characterised and compared on the basis of three statistics: the expected value, the variance and the CVaR at a specified confidence level. The problem is multi-objective and transformed into a single objective problem in which variance is minimised while constraints are imposed on the expected value and CVaR. In the case of discrete random variables, the problem is a quadratic program. The mean-variance (mean-CVaR) efficient solutions that are not dominated with respect to CVaR (variance) are particular efficient solutions of the proposed model. In addition, the model has efficient solutions that are discarded by both mean-variance and mean-CVaR models, although they may improve the return distribution. The model is tested on real data drawn from the FTSE 100 index. An analysis of the return distribution of the chosen portfolios is presented

Guided Bone Regeneration Using Injectable Vascular Endothelial Growth Factor Delivery Gel

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141041/1/jper0230.pd

Doses to internal organs for various breast radiation techniques - implications on the risk of secondary cancers and cardiomyopathy

<p>Abstract</p> <p>Background</p> <p>Breast cancers are more frequently diagnosed at an early stage and currently have improved long term outcomes. Late normal tissue complications induced by adjuvant radiotherapy like secondary cancers or cardiomyopathy must now be avoided at all cost. Several new breast radiotherapy techniques have been developed and this work aims at comparing the scatter doses of internal organs for those techniques.</p> <p>Methods</p> <p>A CT-scan of a typical early stage left breast cancer patient was used to describe a realistic anthropomorphic phantom in the MCNP Monte Carlo code. Dose tally detectors were placed in breasts, the heart, the ipsilateral lung, and the spleen. Five irradiation techniques were simulated: whole breast radiotherapy 50 Gy in 25 fractions using physical wedge or breast IMRT, 3D-CRT partial breast radiotherapy 38.5 Gy in 10 fractions, HDR brachytherapy delivering 34 Gy in 10 treatments, or Permanent Breast ¹⁰³Pd Seed Implant delivering 90 Gy.</p> <p>Results</p> <p>For external beam radiotherapy the wedge compensation technique yielded the largest doses to internal organs like the spleen or the heart, respectively 2,300 mSv and 2.7 Gy. Smaller scatter dose are induced using breast IMRT, respectively 810 mSv and 1.1 Gy, or 3D-CRT partial breast irradiation, respectively 130 mSv and 0.7 Gy. Dose to the lung is also smaller for IMRT and 3D-CRT compared to the wedge technique. For multicatheter HDR brachytherapy a large dose is delivered to the heart, 3.6 Gy, the spleen receives 1,171 mSv and the lung receives 2,471 mSv. These values are 44% higher in case of a balloon catheter. In contrast, breast seeds implant is associated with low dose to most internal organs.</p> <p>Conclusions</p> <p>The present data support the use of breast IMRT or virtual wedge technique instead of physical wedges for whole breast radiotherapy. Regarding partial breast irradiation techniques, low energy source brachytherapy and external beam 3D-CRT appear safer than ¹⁹²Ir HDR techniques.</p

Fluvial sediment supply to a mega-delta reduced by shifting tropical-cyclone activity

© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. The world's rivers deliver 19 billion tonnes of sediment to the coastal zone annually, with a considerable fraction being sequestered in large deltas, home to over 500 million people. Most (more than 70 per cent) large deltas are under threat from a combination of rising sea levels, ground surface subsidence and anthropogenic sediment trapping, and a sustainable supply of fluvial sediment is therefore critical to prevent deltas being 'drowned' by rising relative sea levels. Here we combine suspended sediment load data from the Mekong River with hydrological model simulations to isolate the role of tropical cyclones in transmitting suspended sediment to one of the world's great deltas. We demonstrate that spatial variations in the Mekong's suspended sediment load are correlated (r = 0.765, P < 0.1) with observed variations in tropical-cyclone climatology, and that a substantial portion (32 per cent) of the suspended sediment load reaching the delta is delivered by runoff generated by rainfall associated with tropical cyclones. Furthermore, we estimate that the suspended load to the delta has declined by 52.6 ± 10.2 megatonnes over recent years (1981-2005), of which 33.0 ± 7.1 megatonnes is due to a shift in tropical-cyclone climatology. Consequently, tropical cyclones have a key role in controlling the magnitude of, and variability in, transmission of suspended sediment to the coast. It is likely that anthropogenic sediment trapping in upstream reservoirs is a dominant factor in explaining past, and anticipating future, declines in suspended sediment loads reaching the world's major deltas. However, our study shows that changes in tropical-cyclone climatology affect trends in fluvial suspended sediment loads and thus are also key to fully assessing the risk posed to vulnerable coastal systems

Ribosome Display Selection of a Murine IgG1 Fab Binding Affibody Molecule Allowing Species Selective Recovery Of Monoclonal Antibodies

Affinity reagents recognizing constant parts of antibody molecules are invaluable tools in immunotechnology applications, including purification, immobilization, and detection of immunoglobulins. In this article, murine IgG1, the primary isotype of monoclonal antibodies (mAbs) was used as target for selection of novel binders from a combinatorial ribosome display (RD) library of 1011 affibody molecules. Four rounds of selection using three different mouse IgG1 mAbs as alternating targets resulted in the identification of binders with broad mIgG1 recognition and dissociation constants (KD) in the low nanomolar to low micromolar range. For one of the binders, denoted Zmab25, competition in binding to full length mIgG1 by a streptococcal protein G (SPG) fragment and selective affinity capture of mouse IgG1 Fab fragments after papain cleavage of a full mAb suggest that an epitope functionally overlapping with the SPG-binding site in the CH1 domain of mouse IgG1 had been addressed. Interestingly, biosensor-based binding experiments showed that neither human IgG1 nor bovine Ig, the latter present in fetal bovine serum (FBS) was recognized by Zmab25. This selective binding profile towards murine IgG1 was successfully exploited in species selective recovery of two different mouse mAbs from complex samples containing FBS, resembling a hybridoma culture supernatant

Deep residual networks for quantification of muscle fiber orientation and curvature from ultrasound images

This paper concerns fully automatic and objective measurement of human skeletal muscle fiber orientation directly from standard b-mode ultrasound images using deep residual (ResNet) and convolutional neural networks (CNN). Fiber orientation and length is related with active and passive states of force production within muscle. There is currently no non-invasive way to measure force directly from muscle. Measurement of forces and other contractile parameters like muscle length change, thickness, and tendon length is not only important for understanding healthy muscle, but such information has contributed to understanding, diagnosis, monitoring, targeting and treatment of diseases ranging from myositis to stroke and motor neurone disease (MND). We applied well established deep learning methods to ultrasound data recorded from 19 healthy participants (5 female, ages: 30 ± 7.7) and achieved state of the art accuracy in predicting fiber orientation directly from ultrasound images of the calf muscles. First we used a previously developed segmentation technique to extract a region of interest within the gastrocnemius muscle. Then we asked an expert to annotate the main line of fiber orientation in 4 × 4 partitions of 400 normalized images. A linear model was then applied to the annotations to regulate and recover the orientation field for each image. Then we applied a CNN and a ResNet to predict the fiber orientation in each image. With leave one participant out cross-validation and dropout as a regulariser, we were able to demonstrate state of the art performance, recovering the fiber orientation with an average error of just 2°

Long-term sediment decline causes ongoing shrinkage of the Mekong megadelta, Vietnam

Since the 1990s the Mekong River delta has suffered a large decline in sediment supply causing coastal erosion, following catchment disturbance through hydropower dam construction and sand extraction. However, our new geological reconstruction of 2500-years of delta shoreline changes show that serious coastal erosion actually started much earlier. Data shows the sandy coast bounding river mouths accreted consistently at a rate of +2 to +4 km2/year. In contrast, we identified a variable accretion rate of the muddy deltaic protrusion at Camau; it was < +1 km2/year before 1400 years ago but increased drastically around 600 years ago, forming the entire Camau Peninsula. This high level of mud supply had sharply declined by the early 20th century after a vast canal network was built on the delta. Since then the Peninsula has been eroding, promoted by the conjunction of mud sequestration in the delta plain driven by expansion of rice cultivation, and hysteresis of long-term muddy sedimentation that left the protrusion exposed to wave erosion. Natural mitigation would require substantial increases in sediment supply well above the pre-1990s levels

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Evaluating housing quality, health and safety using an Internet-based data collection and response system: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Typically housing and health surveys are not integrated together and therefore are not representative of population health or national housing stocks. In addition, the existing channels for distributing information about housing and health issues to the general public are limited. The aim of this study was to develop a data collection and response system that would allow us to assess the Finnish housing stock from the points of view of quality, health and safety, and also to provide a tool to distribute information about important housing health and safety issues.</p> <p>Methods</p> <p>The data collection and response system was tested with a sample of 3000 adults (one per household), who were randomly selected from the Finnish Population Register Centre. Spatial information about the exact location of the residences (i.e. coordinates) was included in the database inquiry. People could participate either by completing and returning a paper questionnaire or by completing the same questionnaire via the Internet. The respondents did not receive any compensation for their time in completing the questionnaire.</p> <p>Results</p> <p>This article describes the data collection and response system and presents the main results of the population-based testing of the system. A total of 1312 people (response rate 44%) answered the questionnaire, though only 80 answered via the Internet. A third of the respondents had indicated they wanted feedback. Albeit a majority (>90%) of the respondents reported being satisfied or quite satisfied with their residence, there were a number of prevalent housing issues identified that can be related to health and safety.</p> <p>Conclusions</p> <p>The collected database can be used to evaluate the quality of the housing stock in terms of occupant health and safety, and to model its association with occupant health and well-being. However, it must be noted that all the health outcomes gathered in this study are self-reported. A follow-up study is needed to evaluate whether the occupants acted on the feedback they received. Relying solely on an Internet-based questionnaire for collecting data would not appear to provide an adequate response rate for random population-based surveys at this point in time.</p