Synthesis and characterization of LiNi 0.85 Mn 0.075 Co 0.075 O 2 cathode for Li-ion batteries

Li-ion batteries have played a very important role in the commercialization of HEVs (hybrid electric vehicles) and EVs (electric vehicles) in the past few decades. With major companies like Ford promising to go fully electric within the decade, research into battery materials have become more extensive. Originally, lithium cobalt oxide has been one of the main cathode materials (still used extensively in smart devices), but this material has low energy density, since it is able to intercalate only half of the Li while cycling. LiNixMnyCo1-x-yO2 (or NMC for short) are currently being utilized by many EVs due to their high energy density. Current battery research is more focused on increasing the Ni content in the NMCs which further increases energy density. With NMC811 recently commercialized, our studies focus on LiNi0.85Mn0.075Co0.075O2, which is the next step. In this study, we will present the synthesis process for LiNi0.85Mn0.075Co0.075O2 by co-precipitation method (adopted industrially), which is optimized very carefully with respect to pH, temperature, as well as concentration of the reactants, etc. This material has been engineered to have a better capacity and capacity retention using the optimization of the calcination temperature. This material was further characterized by PXRD (powdered x-ray diffraction), ICP-OES (inductive coupled plasma-optical emission spectrometry), SEM (scanning electron microscopy), and electrochemical performance using galvanostatic charge-discharge cycling technique.https://orb.binghamton.edu/research_days_posters_2021/1074/thumbnail.jp

Measurements of the Composite Fermion masses from the spin polarization of 2-D electrons in the region 1<ν<21<\nu<2

Measurements of the reflectivity of a 2-D electron gas are used to deduce the polarization of the Composite Fermion hole system formed for Landau level occupancies in the regime 1<\nu<2. The measurements are consistent with the formation of a mixed spin CF system and allow the density of states or `polarization' effective mass of the CF holes to be determined. The mass values at \nu=3/2 are found to be ~1.9m_{e} for electron densities of 4.4 x 10^{11} cm^{-2}, which is significantly larger than those found from measurements of the energy gaps at finite values of effective magnetic field.Comment: 4 pages, 3 fig

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.ImportanceTo fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available

Generative Models: What do they know? Do they know things? Let's find out!

Generative models have been shown to be capable of synthesizing highly detailed and realistic images. It is natural to suspect that they implicitly learn to model some image intrinsics such as surface normals, depth, or shadows. In this paper, we present compelling evidence that generative models indeed internally produce high-quality scene intrinsic maps. We introduce Intrinsic LoRA (I LoRA), a universal, plug-and-play approach that transforms any generative model into a scene intrinsic predictor, capable of extracting intrinsic scene maps directly from the original generator network without needing additional decoders or fully fine-tuning the original network. Our method employs a Low-Rank Adaptation (LoRA) of key feature maps, with newly learned parameters that make up less than 0.6% of the total parameters in the generative model. Optimized with a small set of labeled images, our model-agnostic approach adapts to various generative architectures, including Diffusion models, GANs, and Autoregressive models. We show that the scene intrinsic maps produced by our method compare well with, and in some cases surpass those generated by leading supervised techniques.Comment: https://intrinsic-lora.github.io

Major inpatient surgeries and in-hospital mortality in New South Wales public hospitals in Australia: A state-wide retrospective cohort study

BACKGROUND Surgical interventions save lives and are important focus for health services research worldwide. Investigating variation in postoperative mortality may improve understanding of unwarranted variations and promote safety and quality in surgical care. We aimed to evaluate trends of in-hospital mortality rates among adult inpatients receiving major elective surgeries and determine the variation in mortality among New South Wales (NSW) public hospitals. MATERIALS AND METHODS In this study, we used the all-inclusive population-based NSW Admitted Patient Data from July 2001 to June 2014. We retrospectively included adult patients aged 18 + years receiving Abdominal Aortic Aneurysm (AAA) repair, Peripheral bypass, Colorectal surgeries, Joint replacement, Spinal surgeries, or Cardiac surgeries. The primary outcome was in-hospital mortality for selected surgeries. Changes in mortality rates over time and hospital standardised mortality rates were modelled using multivariate logistic regression models adjusting for case-mix factors. RESULTS Over 13-year study period, the in-hospital mortality rates declined annually by 6.4% (95% Confidence Interval (CI): 4.3, 8.4) for Colorectal surgery by 5.7% (95%CI: 2.0, 9.3) for Joint replacement and by 4.2% (95%CI: 1.9, 6.4) for Cardiac surgery. After controlling for patient-level factors, little variation was observed among hospitals for in-hospital mortality. There was a greater variability for cardiac surgery compared with the other surgical groups but no outlier hospital was consistently associated with significantly higher than expected mortality rate. CONCLUSIONS Mortality has declined for major surgeries in the past 15 years. There was some variation among hospitals regarding in-hospital mortality that was mostly explained by patients demographic and admission characteristics. Our findings are reassuring for patients and contribute to knowledge that can help further improve surgical care

Enhancing Data Quality in Federated Fine-Tuning of Foundation Models

In the current landscape of foundation model training, there is a significant reliance on public domain data, which is nearing exhaustion according to recent research. To further scale up, it is crucial to incorporate collaboration among multiple specialized and high-quality private domain data sources. However, the challenge of training models locally without sharing private data presents numerous obstacles in data quality control. To tackle this issue, we propose a data quality control pipeline for federated fine-tuning of foundation models. This pipeline computes scores reflecting the quality of training data and determines a global threshold for a unified standard, aiming for improved global performance. Our experiments show that the proposed quality control pipeline facilitates the effectiveness and reliability of the model training, leading to better performance.Comment: Accepted at ICLR 2024 Workshop on Navigating and Addressing Data Problems for Foundation Models (DPFM

Reference to index of records of extracts of the officers' logs of the French naval vessel Mascarin's voyage of exploration led by Captain Nicholas Marion Du Fresne -Tasmanian part of voyage, March 1772

Extracts of officers' logs on the French voyage of exploration led by Captain Nicholas Marion Du Fresne,1771-72. All extracts relate to the Tasmanian part of voyage, March 1772. - Private Deposit F.

Determination of phase equilibria for long-chain linear hydrocarbons by Monte Carlo simulation.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.The focus of this study was to determine the coexistence phase equilibria for three groups of long-chain linear hydrocarbons (n-alkanes, 1-alkenes and 1-alcohols) using Monte Carlo simulation. Three common transferable united-atom force fields were used in the simulations: OPLS-UA (Jorgensen et al., 1984), TraPPE-UA (Martin and Siepmann, 1998) and NERD (Nath, Escobedo, de Pablo and Patramai, 1998). Isothermal phase equilibria was calculated over a temperature range from approximately the normal boiling point up to just below the critical temperature. The liquid and vapour densities and vapour pressures were determined from the simulations. The density results were then fitted using least-squares regression to the scaling law and the law of rectilinear diameters in order to estimate the critical properties. The vapour pressure data were fitted using least-squares to the Clausius-Clapeyron equation to estimate the normal boiling points. The NVT-Gibbs ensemble method was used to simulate the pure-component coexistence of the vapour and liquid phases. The NPT-Gibbs ensemble was used to simulate the n-alkane binary mixtures. Two forms of configurational-bias Monte Carlo (standard CBMC and coupled-decoupled CBMC) were used to increase the number of swap moves accepted during the simulations. Dual-cutoff CBMC was implemented with a second cut-off of sA in order to speed up the CBMC calculations. Minimum image and a spherical potential truncation after 14A were implemented with standard tail corrections. BICMAC and TOWHEE were the two Fortran-77 codes used to simulate the hydrocarbon compounds. BICMAC was used in the simulations of non-polar molecules and TOWHEE was used in the simulations of polar molecules. System sizes ranged from 300 (for the CB'S) down to 100 molecules (for the Czo's). The simulations were typically equilibrated for at least 30000 cycles and production runs ranged from 50000 to 120000 cycles for the different hydrocarbon groups. Standard deviations of the calculated thermophysical properties were between 1-3% for the liquid densities and 10-20% for the vapour densities and vapour pressures. It was found that the coexistence density curves were generally in good agreement with experiment for all the hydrocarbon groups investigated (the OPL5-UA force field being the exception). The chain-length appeared to have littl e effect on the quality of the calculated thermophysical properties. The chain-length did however increase the time required to perform the simulations substantially. The va pour pressures were consistently over-predicted by NERD and TraPPE-UA. The normal boiling pOints were typically under-predicted by 2-5%. The critical tempe ratures and densities were predicted to within 1-5% of experimental values. The n-alkane mixtures were satisfactorily predicted using the NPT-Gibbs ensemble. While both the NERD and TraPPE-UA force fields were shown to be substantially more accurate compared to the OPLS-UA force field, there was little difference between their predictions. Thus, it is likely that the added complexity of using the bond-stretching potential (used by NERD) is unnecessary. The results of this study show that Monte Carlo simulation may be used to predict vapour-liquid coexistence properties of long-chain hydrocarbons and to approximate critical properties. However, current force fields require more refinement in ord er to accurately predict the hydrocarbon thermophysical properties. Plus, faster computing speeds are required before Monte Carlo simulation becomes an industrially viable method