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

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

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

Metastatic Colo-Rectal Cancer, 2005-2008: Treatment results

"nIntroduction: Colo-rectal cancer has 10% prevalence, among all of the cancer proportionally and also it is the third common cancer in the both sexes. Two recently introduced active drugs in the treatment of advanced colorectal cancer (ACC) are irinotecan and oxaliplatin. The combinations of oxaliplatin (OXA) or irinotecan (IRI) with 5FU-LV have been accepted as standard treatment for metastatic colorectal cancer. "nPatients and Methods: fifty four patients with colo-rectal cancer who came to the Oncology Clinic of Kermanshah University were assessed over a period of 4 years (2005-2008). All cases in stage III were treated by FOLFOX, unlike the patients in Stage IV treated with FOLFOX during 8 cycles fallowed by FOLFIRI in the same cycles (Sequential method). "nResults: the age average was less (49.1 years versus 55 years) than in other studies (6). A parallel analyzation of solid data, overall survival (OS), progression free survival (PFS) were 18 and 17.3 months, respectively. "nConclusion: FOLFOX and FOLFIRI were administrated in 8 cycles each concomitantly (Sequential form) which provided considerable response with manageable complications. The result of the treatment in the study was correlated with other trials utilizing more modern procedures of medication like ‘Target therapies’ (OS; 18.4m for CT versus 19-20m for target therapies)

Comparison between fractional excretions of urea and sodium in children with acute kidney injury

Fractional excretion of sodium (FENa) has been said to be the most sensitive index for differentiating prerenal failure (PRF) from intrinsic renal failure (IRF). However, there are several instances of high FENa (>2) in cases of PRF and low FENa (0.05). FEUN was 23.6±4.9 in PRF and 41.6±4.8 in IRF patients (P<0.05), and low FEUN (<35) was seen in 77.8 of the PRF group (P<0.05). Cutoff values of 30 and 1.6 were reached for FEUN and FENa, respectively. In conclusion, FEUN <35 had higher sensitivity and specificity than FENa <1 for differentiation of PRF from IRF. © IPNA 2009