Structural Insight into Protective Alumina Coatings for Layered Li-Ion Cathode Materials by Solid-State NMR Spectroscopy.

Layered transition metal oxide cathode materials can exhibit high energy densities in Li-ion batteries, in particular, those with high Ni contents such as LiNiO2. However, the stability of these Ni-rich materials often decreases with increased nickel content, leading to capacity fade and a decrease in the resulting electrochemical performance. Thin alumina coatings have the potential to improve the longevity of LiNiO2 cathodes by providing a protective interface to stabilize the cathode surface. The structures of alumina coatings and the chemistry of the coating-cathode interface are not fully understood and remain the subject of investigation. Greater structural understanding could help to minimize excess coating, maximize conductive pathways, and maintain high capacity and rate capability while improving capacity retention. Here, solid-state nuclear magnetic resonance (NMR) spectroscopy, paired with powder X-ray diffraction and electron microscopy, is used to provide insight into the structures of the Al2O3 coatings on LiNiO2. To do this, we performed a systematic study as a function of coating thickness and used LiCoO2, a diamagnetic model, and the material of interest, LiNiO2. 27Al magic-angle spinning (MAS) NMR spectra acquired for thick 10 wt % coatings on LiCoO2 and LiNiO2 suggest that in both cases, the coatings consist of disordered four- and six-coordinate Al-O environments. However, 27Al MAS NMR spectra acquired for thinner 0.2 wt % coatings on LiCoO2 identify additional phases believed to be LiCo1-xAlxO2 and LiAlO2 at the coating-cathode interface. 6,7Li MAS NMR and T1 measurements suggest that similar mixing takes place near the interface for Al2O3 on LiNiO2. Furthermore, reproducibility studies have been undertaken to investigate the effect of the coating method on the local structure, as well as the role of the substrate.

Elucidating local diffusion dynamics in nickel-rich layered oxide cathodes.

Elucidating Li-ion transport properties is essential for designing suitable methodologies to optimise electrochemical performance in Ni-rich cathodes for high energy density Li-ion batteries. Here, we report the local-scale Li-diffusion characteristics of a series of nickel-rich layered oxide cathodes, prepared via microwave methods, using muon spin relaxation methods. Our results detail the effects of cation dopants, selected for structure stability, on transport properties in candidate nickel-rich chemistries. We find that the local diffusion properties improve with increasing nickel content. Our results demonstrate that these observations are dependant on substitutional effects.

Use of electronic health data to identify patients with moderate-to-severe osteoarthritis of the hip and/or knee and inadequate response to pain medications.

BACKGROUND: No algorithms exist to identify important osteoarthritis (OA) patient subgroups (i.e., moderate-to-severe disease, inadequate response to pain treatments) in electronic healthcare data, possibly due to the complexity in defining these characteristics as well as the lack of relevant measures in these data sources. We developed and validated algorithms intended for use with claims and/or electronic medical records (EMR) to identify these patient subgroups. METHODS: We obtained claims, EMR, and chart data from two integrated delivery networks. Chart data were used to identify the presence or absence of the three relevant OA-related characteristics (OA of the hip and/or knee, moderate-to-severe disease, inadequate/intolerable response to at least two pain-related medications); the resulting classification served as the benchmark for algorithm validation. We developed two sets of case-identification algorithms: one based on a literature review and clinical input (predefined algorithms), and another using machine learning (ML) methods (logistic regression, classification and regression tree, random forest). Patient classifications based on these algorithms were compared and validated against the chart data. RESULTS: We sampled and analyzed 571 adult patients, of whom 519 had OA of hip and/or knee, 489 had moderate-to-severe OA, and 431 had inadequate response to at least two pain medications. Individual predefined algorithms had high positive predictive values (all PPVs ≥ 0.83) for identifying each of these OA characteristics, but low negative predictive values (all NPVs between 0.16-0.54) and sometimes low sensitivity; their sensitivity and specificity for identifying patients with all three characteristics was 0.95 and 0.26, respectively (NPV 0.65, PPV 0.78, accuracy 0.77). ML-derived algorithms performed better in identifying this patient subgroup (range: sensitivity 0.77-0.86, specificity 0.66-0.75, PPV 0.88-0.92, NPV 0.47-0.62, accuracy 0.75-0.83). CONCLUSIONS: Predefined algorithms adequately identified OA characteristics of interest, but more sophisticated ML-based methods better differentiated between levels of disease severity and identified patients with inadequate response to analgesics. The ML methods performed well, yielding high PPV, NPV, sensitivity, specificity, and accuracy using either claims or EMR data. Use of these algorithms may expand the ability of real-world data to address questions of interest in this underserved patient population.

In Situ Diffusion Measurements of a NASICON-Structured All-Solid-State Battery Using Muon Spin Relaxation.

In situ muon spin relaxation is demonstrated as an emerging technique that can provide a volume-averaged local probe of the ionic diffusion processes occurring within electrochemical energy storage devices as a function of state of charge. Herein, we present work on the conceptually interesting NASICON-type all-solid-state battery LiM2(PO4)3, using M = Ti in the cathode, M = Zr in the electrolyte, and a Li metal anode. The pristine materials are studied individually and found to possess low ionic hopping activation energies of ∼50-60 meV and competitive Li+ self-diffusion coefficients of ∼10-10-10-9 cm2 s-1 at 336 K. Lattice matching of the cathode and electrolyte crystal structures is employed for the all-solid-state battery to enhance Li+ diffusion between the components in an attempt to minimize interfacial resistance. The cell is examined by in situ muon spin relaxation, providing the first example of such ionic diffusion measurements. This technique presents an opportunity to the materials community to observe intrinsic ionic dynamics and electrochemical behavior simultaneously in a nondestructive manner.

Benzo-Dipteridine Derivatives as Organic Cathodes for Li- and Na-ion Batteries.

Organic-based electrodes for Li- and Na-ion batteries present attractive alternatives to commonly applied inorganic counterparts which can often carry with them supply-chain risks, safety concerns with thermal runaway, and adverse environmental impact. The ability to chemically direct the structure of organic electrodes through control over functional groups is of particular importance, as this provides a route to fine-tune electrochemical performance parameters. Here, we report two benzo-dipteridine derivatives, BF-Me2 and BF-H2 , as high-capacity electrodes for use in Li- and Na-ion batteries. These moieties permit binding of multiple Li-ions per molecule while simultaneously ensuring low solubility in the supporting electrolyte, often a precluding issue with organic electrodes. Both display excellent electrochemical stability, with discharge capacities of 142 and 182 mAh g-1 after 100 cycles at a C/10 rate and Coulombic efficiencies of 96% and ∼ 100% demonstrated for BF-Me2 and BF-H2 , respectively. The application of a Na-ion cell has also been demonstrated, showing discharge capacities of 88.8 and 137 mAh g-1 after 100 cycles at a C/2 rate for BF-Me2 and BF-H2 , respectively. This work provides an encouraging precedent for these and related structures to provide versatile, high-energy density, and long cycle-life electrochemical energy storage materials.

Pain, opioids, and confusion after arthroplasty in older adults.

BACKGROUND: Postoperative confusion is a common complication in older adults, particularly after total joint replacement (arthroplasty). Confusion after surgery can result in slower mobility progression, longer hospital stay, and increased patient distress. Postoperative pain has been shown to be a risk factor related to confusion; however, there is limited evidence regarding pain level, medication use, and confusion development in postoperative arthroplasty patients. PURPOSE: To evaluate development of postoperative confusion and the current practice of pain management for older adult patients with hip or knee arthroplasty. METHODS: Two-month retrospective chart review of medical records at a large, Midwestern, private hospital. Pain assessments were performed on a regular basis using self-report 11-point Numeric Rating Scale (0-10). Opioid use was scored using an equianalgesic conversion chart. RESULTS: Ninety-eight patients met inclusion criteria and 97 received treatment with opioids during the first 48 hours postoperatively. No patients received opioid agents that are contraindicated in older adults. Thirty-three patients had evidence in the medical record of confusion during the first 48 hours postoperatively. Lower equianalgesic dose was significant for increased age and increased confusion on postoperative day 1 (POD 1) and POD 2. Patients with higher equianalgesic scores were less likely to meet benchmark pain scores less than 5 on POD 0, POD 1, and POD 2. CONCLUSIONS: Patients receiving lower amounts of opioids in the first 48 hours after surgery were more likely to be confused on POD 1(p = .023) and POD 2 (p = .049).