Lithium-ion batteries (LIBs) have been widely used as the most popular rechargeable energy storage and power sources in today’s portable electronics, electric vehicles, and plug-in hybrid electric vehicles. LIBs have gained much interest worldwide in the last three decades because of their high energy density, voltage, rate of charge and discharge, reliability, and design flexibility. I am exploring the possibility of developing battery manufacturing technologies that would lower the cost, reduce the environmental impact, and increase cell performance and durability. This dissertation is focused firstly on understanding the effect of mixing sequence (the order of introducing materials) and optimizing the electrode fabrication for the best electrochemical performance, durability, lower cost, and improve the existing manufacturing processes. The electrode system consists of active material, polymer binder, conductive agent, and solvent. I have investigated four different mixing sequences to prepare the slurries for making the positive electrode. The key sequence-related factor appears to be whether the active material and conductive agent are mixed in the presence of or prior to the introduction of the binder solution. The mixing sequences 1, 2, 3, and 4 were optimized, and the rheological behavior of the slurries, morphology, conductivity, and mechanical and electrochemical properties of electrodes were investigated. Slurries from sequences 1 and 4 show different rheological properties from 2 and 3. The amount of NMP required to achieve a comparable final slurry viscosity differed significantly for the sequences under study. The sequence 1 shows better long-term cycling behavior than sequences 2, 3 and 4. This study quantifies the link between electrode slurry mix parameters and electrode quality. Secondly, a new method of making lithium-ion battery electrodes by adapting an immersion precipitation (IP) technology commonly used in membrane manufacturing was developed and demonstrated. The composition, structure, and electrochemical performance of the electrode made by the IP method were compared favorably with that made by the conventional method. The toxic and expensive organic solvent (NMP) was captured in coagulation bath instead of being released to the atmosphere. The IP electrodes show an excellent performance and durability at potentially lower cost and less environmental impact. Thirdly, I have developed and demonstrated a solvent-free dry-powder coating process for making LiNi1/3Mn1/3Co1/3O2 (NMC) positive electrodes in lithium-ion batteries, and compared the performance and durability of electrodes made by the dry-powder coating processes with that by wet-slurry coating processes. The technology that has been used is the electrostatic spray deposition (ESD) process. This process eliminates volatile organic compound emission, reduces thermal curing time from hours to minutes, and offers high deposition rates onto large surfaces. The long-term cycling shows that the dry-powder coated electrodes have similar performance and durability as the conventional wet-slurry made electrodes.

No description available.

A frequent problem that appears in practical survival data analysis is censoring. A censored observation occurs when the observation of the event time (duration or survival time) may be prevented by the occurrence of an earlier competing event (censoring time). Censoring may be due to different causes. For example, the loss of some subjects under study, the end of the follow-up period, drop out or the termination of the study and the limitation in the sensitivity of a measurement instrument. The literature about censored data focuses on the i.i.d. case. However in many real applications the data are collected sequentially in time or space and so the assumption of independence in such case does not hold. Here we only give some typical examples from the literature involving correlated data which are subject to censoring. In the clinical trials domain it frequently happens that the patients from the same hospital have correlated survival times due to unmeasured variables like the quality of the hospital equipment. Censored correlated data are also a common problem in the domain of environmental and spatial (geographical or ecological) statistics. In fact, due to the process being used in the data sampling procedure, e.g. the analytical equipment, only the measurements which exceed some thresholds, for example the method detection limits or the instrumental detection limits, can be included in the data analysis. Many other examples can also be found in other fields like econometrics and financial statistics. Observations on duration of unemployment e.g., may be right censored and are typically correlated. When the data are not independent and are subject to censoring, estimation and inference become more challenging mathematical problems with a wide area of applications. In this context, we propose here some new and flexible tools based on a nonparametric approach. More precisely, allowing dependence between individuals, our main contribution to this domain concerns the following aspects. First, we are interested in developing more suitable confidence intervals for a general class of functionals of a survival distribution via the empirical likelihood method. Secondly, we study the problem of conditional mean estimation using the local linear technique. Thirdly, we develop and study a new estimator of the conditional quantile function also based on the local linear method. In this dissertation, for each proposed method, asymptotic results like consistency and asymptotic normality are derived and the finite sample performance is evaluated in a simulation study.

A frequent problem that appears in practical survival data analysis is censoring. A censored observation occurs when the observation of the event time (duration or survival time) may be prevented by the occurrence of an earlier competing event (censoring time). Censoring may be due to different causes. For example, the loss of some subjects under study, the end of the follow-up period, drop out or the termination of the study and the limitation in the sensitivity of a measurement instrument. The literature about censored data focuses on the i.i.d. case. However in many real applications the data are collected sequentially in time or space and so the assumption of independence in such case does not hold. Here we only give some typical examples from the literature involving correlated data which are subject to censoring. In the clinical trials domain it frequently happens that the patients from the same hospital have correlated survival times due to unmeasured variables like the quality of the hospital equipment. Censored correlated data are also a common problem in the domain of environmental and spatial (geographical or ecological) statistics. In fact, due to the process being used in the data sampling procedure, e.g. the analytical equipment, only the measurements which exceed some thresholds, for example the method detection limits or the instrumental detection limits, can be included in the data analysis. Many other examples can also be found in other fields like econometrics and financial statistics. Observations on duration of unemployment e.g., may be right censored and are typically correlated. When the data are not independent and are subject to censoring, estimation and inference become more challenging mathematical problems with a wide area of applications. In this context, we propose here some new and flexible tools based on a nonparametric approach. More precisely, allowing dependence between individuals, our main contribution to this domain concerns the following aspects. First, we are interested in developing more suitable confidence intervals for a general class of functionals of a survival distribution via the empirical likelihood method. Secondly, we study the problem of conditional mean estimation using the local linear technique. Thirdly, we develop and study a new estimator of the conditional quantile function also based on the local linear method. In this dissertation, for each proposed method, asymptotic results like consistency and asymptotic normality are derived and the finite sample performance is evaluated in a simulation study.