Insights into lithium inventory quantification of LiNi_0.5Mn_1.5O₄–graphite full cells

High voltage spinel cathode LiNi0.5Mn1.5O4 (LNMO) offers higher energy density and competitive cost compared to traditional cathodes in lithium-ion batteries, making it a promising option for high-performance battery applications. However, the fast capacity decay in full cells hinders further commercialization. The Li inventory evolution upon cycling in the LNMO–graphite pouch cell is systematically studied by developing lithium quantification methods on the cathode, anode, and electrolyte. The findings reveal that active Li loss is a primary factor contributing to capacity decay, stemming from an unstable anode interphase caused by crosstalk. This crosstalk primarily originates from electrolyte degradation on the cathode under high-voltage operation, leading to increased moisture and acidity, subsequently corroding the anode interphase. In response, two approaches including an aluminum oxide (Al2O3) surface coating layer on the cathode and lithium difluoro(oxalato)borate (LiDFOB) electrolyte additives are evaluated systematically, resulting in cycling stability enhancement. This study offers a quantitative approach to understanding the Li inventory loss in the LNMO–Gr system, providing unique insights and guidance into identifying critical bottlenecks for developing high voltage (>4.4 V) lithium battery technology

Identification of Novel Antimalarial Chemotypes via Chemoinformatic Compound Selection Methods for a High-Throughput Screening Program against the Novel Malarial Target, PfNDH2: Increasing Hit Rate via Virtual Screening Methods

Malaria is responsible for approximately 1 million deaths annually; thus, continued efforts to discover new antimalarials are required. A HTS screen was established to identify novel inhibitors of the parasite's mitochondrial enzyme NADH:quinone oxidoreductase (PfNDH2). On the basis of only one known inhibitor of this enzyme, the challenge was to discover novel inhibitors of PfNDH2 with diverse chemical scaffolds. To this end, using a range of ligand-based chemoinformatics methods, ~17000 compounds were selected from a commercial library of ~750000 compounds. Forty-eight compounds were identified with PfNDH2 enzyme inhibition IC(50) values ranging from 100 nM to 40 μM and also displayed exciting whole cell antimalarial activity. These novel inhibitors were identified through sampling 16% of the available chemical space, while only screening 2% of the library. This study confirms the added value of using multiple ligand-based chemoinformatic approaches and has successfully identified novel distinct chemotypes primed for development as new agents against malaria

COVID-19 POTS

Postural orthostatic tachycardia syndrome (POTS) is a common condition marked by autonomic dysfunction. POTS’ pathophysiology is multifactorial and its symptoms include presyncope, heart palpitations, lightheadedness, blurred vision, and syncope. A few possible causes of POTS include trauma, pregnancy, and most importantly, post-infection. Common infections known to trigger POTS include EBV, influenza, and the newly discovered COVID-19. Due to the high transmission rate of COVID-19, POTS has been more heavily diagnosed within the past couple of years. Different theories of why POTS occurs include a lower than normal amount of blood volume, an inability to quickly vasoconstrict blood vessels, and an elevated amount of norepinephrine. COVID-19 is suspected to trigger POTS due to a possible relationship in the downregulation of the RAAS system as the COVID-19 spike protein has been found to bind to ACE inhibitors. This paper focuses on the pathophysiology of POTS and orthostatic intolerance as well as diagnosis and management and the relationship between COVID-19 and POTS and what the timeline for those diseases can look like as well as prognosis and focus for future research. Future research studies are working to develop target therapies for COVID-19 POTS. Although POTS is a chronic condition, it is not associated with high mortality but high morbidity. Furthermore, barriers such as lack of knowledge of providers make it difficult to determine the prognosis

Improved Rate Capability for Dry Thick Electrodes Through Finite Elements Method and Machine-Learning Coupling

A coupled Finite Elements Method (FEM) and Machine-Learning (ML) workflow is presented to optimize the rate capability of thick positive electrodes (ca. 150 µm and 8 mAh/cm²). An ML model is trained based on the geometrical observables of individual LiNi0.8Mn0.1Co0.1O2 particles and their average state of discharge (SOD) predicted from FEM modeling. This model not only bypasses lengthy FEM simulations, but also provides deeper insights on the importance of pore tortuosity and the active particles size, identified as the limiting phenomenon during the discharge. Based on these findings, a bi-layer configuration is proposed to tackle the identified limiting factors for the rate capability. The benefits of this structured electrode are validated through FEM by comparing its performance to a pristine mono-layer electrode. Finally, experimental validation using dry processing demonstrates a 40% higher volumetric capacity of the bi-layer electrode when compared to the previously reported thick NMC electrodes

Forest plot of PW and all other drinking water sources.

<p>Forest plot of the odds ratio of fecal contamination comparing PW and all other drinking water sources.</p

PRISMA flowchart.

<p>Results of literature search and screening according to PRISMA flowchart for systematic review screening process (Adapted from Moher et al. 2009).</p

Results from between-study meta-regression.

<p>*significance at 95%</p><p>Results from between-study meta-regression.</p

Characteristics of included studies.

<p>^aTwo articles reported two separate studies within the article, therefore the total is 172.</p><p>Characteristics of included studies.</p

Criteria used to assess study quality (adapted from Bain et al. 2014b).

<p>Criteria used to assess study quality (adapted from Bain et al. 2014b).</p