Roadmap on Li-ion battery manufacturing research

Growth in the Li-ion battery market continues to accelerate, driven primarily by the increasing need for economic energy storage for electric vehicles. Electrode manufacture by slurry casting is the first main step in cell production but much of the manufacturing optimisation is based on trial and error, know-how and individual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding to the electrode manufacturing value chain. Overcoming the current barriers in electrode manufacturing requires advances in materials, manufacturing technology, in-line process metrology and data analytics, and can enable improvements in cell performance, quality, safety and process sustainability. In this roadmap we explore the research opportunities to improve each stage of the electrode manufacturing process, from materials synthesis through to electrode calendering. We highlight the role of new process technology, such as dry processing, and advanced electrode design supported through electrode level, physics-based modelling. Progress in data driven models of electrode manufacturing processes is also considered. We conclude there is a growing need for innovations in process metrology to aid fundamental understanding and to enable feedback control, an opportunity for electrode design to reduce trial and error, and an urgent imperative to improve the sustainability of manufacture

Pion contamination in the MICE muon beam

The international Muon Ionization Cooling Experiment (MICE) will perform a systematic investigation of ionization cooling with muon beams of momentum between 140 and 240\,MeV/c at the Rutherford Appleton Laboratory ISIS facility. The measurement of ionization cooling in MICE relies on the selection of a pure sample of muons that traverse the experiment. To make this selection, the MICE Muon Beam is designed to deliver a beam of muons with less than $\sim$1\% contamination. To make the final muon selection, MICE employs a particle-identification (PID) system upstream and downstream of the cooling cell. The PID system includes time-of-flight hodoscopes, threshold-Cherenkov counters and calorimetry. The upper limit for the pion contamination measured in this paper is $f_\pi < 1.4\%$ at 90\% C.L., including systematic uncertainties. Therefore, the MICE Muon Beam is able to meet the stringent pion-contamination requirements of the study of ionization cooling.Department of Energy and National Science Foundation (U.S.A.), the Instituto Nazionale di Fisica Nucleare (Italy), the Science and Technology Facilities Council (U.K.), the European Community under the European Commission Framework Programme 7 (AIDA project, grant agreement no. 262025, TIARA project, grant agreement no. 261905, and EuCARD), the Japan Society for the Promotion of Science and the Swiss National Science Foundation, in the framework of the SCOPES programme

Roadmap on Li-ion battery manufacturing research

Growth in the Li-ion battery market continues to accelerate, driven by increasing need for economic energy storage in the electric vehicle market. Electrode manufacture is the first main step in production and in an industry dominated by slurry casting, much of the manufacturing process is based on trial and error, know-how and individual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding value to the electrode manufacturing value chain. Overcome the current barriers in the electrode manufacturing requires advances in material innovation, manufacturing technology, in-line process metrology and data analytics to improve cell performance, quality, safety and process sustainability. In this roadmap we present where fundamental research can impact advances in each stage of the electrode manufacturing process from materials synthesis to electrode calendering. We also highlight the role of new process technology such as dry processing and advanced electrode design supported through electrode level, physics-based modelling. To compliment this, the progresses in data driven models of full manufacturing processes is reviewed. For all the processes we describe, there is a growing need process metrology, not only to aid fundamental understanding but also to enable true feedback control of the manufacturing process. It is our hope this roadmap will contribute to this rapidly growing space and provide guidance and inspiration to academia and industry

Detection and survival of group A rotavirus in a piggery

Samples of dust, faeces and effluent were collected from a piggery and examined for group A rotavirus, using a commercial ELISA test, electron microscopy and inoculation of MA-104 cells. Rotavirus antigen was demonstrated in samples collected from farrowing and weaner rooms but not from fattener and sow houses. Rotavirus antigen was also detected in samples collected from a weaner room which had been free of piglets for three months. A cytopathic porcine rotavirus (British isolate SW20/21) was kept at room temperature for four months; it survived with titres reduced by 2 log10. These observations suggest that the environment of commercial piggeries is an important source of rotaviral infection for young piglets

Epidemiology of typical and atypical rotavirus infections in New Zealand pigs

Polyacrylamide gel electrophoresis (PAGE) and enzyme-linked immunosorbent assay (ELISA) were employed to investigate the epidemiology of typical and atypical rotavirus infections in five piggeries. Of 152 faecal samples examined, 46 (30 per cent) were positive by ELISA for group A rotavirus. Rotaviruses with electrophoretic patterns resembling groups A, B and C were detected. At least two and up to five different rotavirus electrophoretypes (typical and/or atypical) were detected in each of the five piggeries. Out of 152 faecal samples examined, 28 (18 per cent) contained rotaviruses with group A electrophor etypes, 9 (6 per cent) with group C but only 1 with Group B. Six samples contained both group A and group C rotaviruses. No common electrophoretypes of group A or C rotaviruses were detected in these five piggeries. The PAGE technique was also used to analyze group A rotavirus isolated sequentially from another piggery over a three year period. A singIe electrophoretype was found during the first two years, but in the third year a different electrophoretype was detected

Biochemical values in equine medicine

SIGLELD:81/21252(Biochemical). / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Tapped granular column dynamics: simulations, experiments and modeling

This paper communicates the results of a synergistic investigation that initiates our long term research goal of developing a continuum model capable of predicting a variety of granular flows. We consider an ostensibly simple system consisting of a column of inelastic spheres subjected to discrete taps in the form of half sine wave pulses of amplitude a/d and frequency f. A three-pronged approach is used, consisting of discrete element simulations based on linear loading-unloading contacts, experimental validation, and preliminary comparisons with our continuum model in the form of an integro-partial differential equation. Tapped Granular Column Dynamics: Simulations, Experiments and Modeling. Available from: https://www.researchgate.net/publication/274391492_Tapped_Granular_Column_Dynamics_Simulations_Experiments_and_Modeling [accessed Feb 1, 2016]

An analytical approach differentiates between individual and collective cancer invasion

Tumour cells employ a variety of mechanisms to invade their environment and to form metastases. An important property is the ability of tumour cells to transition between individual cell invasive mode and collective mode. The switch from collective to individual cell invasion in the breast was shown recently to determine site of subsequent metastasis. Previous studies have suggested a range of invasion modes from single cells to large clusters. Here, we use a novel image analysis method to quantify and categorise invasion. We have developed a process using automated imaging for data collection, unsupervised morphological examination of breast cancer invasion using cognition network technology (CNT) to determine how many patterns of invasion can be reliably discriminated. We used Bayesian network analysis to probabilistically connect morphological variables and therefore determine that two categories of invasion are clearly distinct from one another. The Bayesian network separated individual and collective invading cell groups based on the morphological measurements, with the level of cell-cell contact the most discriminating morphological feature. Smaller invading groups were typified by smoother cellular surfaces than those invading collectively in larger groups. Interestingly, elongation was evident in all invading cell groups and was not a specific feature of single cell invasion as a surrogate of epithelial-mesenchymal transition. In conclusion, the combination of cognition network technology and Bayesian network analysis provides an insight into morphological variables associated with transition of cancer cells between invasion modes. We show that only two morphologically distinct modes of invasion exist