Impact of transport electrification on critical metal sustainability with a focus on the heavy-duty segment

The majority of transport electrification studies, examining the demand and sustainability of critical metals, have focused on light-duty vehicles. Heavy-duty vehicles have often been excluded from the research scope due to their smaller vehicle stock and slower pace of electrification. This study fills this research gap by evaluating the lithium resource impacts from electrification of the heavy-duty segment at the global level. Our results show that a mass electrification of the heavy-duty segment on top of the light-duty segment would substantially increase the lithium demand and impose further strain on the global lithium supply. The significant impact is attributed to the large single-vehicle battery capacity required by heavy-duty vehicles and the expected battery replacement needed within the lifetime of heavy-duty vehicles. We suggest that the ambition of mass electrification in the heavy-duty segment should be treated with cautions for both policy makers and entrepreneurs

"Knees" in lithium-ion battery aging trajectories

Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear degradation that severely limits battery lifetime. In this work, we review prior work on "knees" in lithium-ion battery aging trajectories. We first review definitions for knees and three classes of "internal state trajectories" (termed snowball, hidden, and threshold trajectories) that can cause a knee. We then discuss six knee "pathways", including lithium plating, electrode saturation, resistance growth, electrolyte and additive depletion, percolation-limited connectivity, and mechanical deformation -- some of which have internal state trajectories with signals that are electrochemically undetectable. We also identify key design and usage sensitivities for knees. Finally, we discuss challenges and opportunities for knee modeling and prediction. Our findings illustrate the complexity and subtlety of lithium-ion battery degradation and can aid both academic and industrial efforts to improve battery lifetime.Comment: Submitted to the Journal of the Electrochemical Societ

Glaucoma management in the era of artificial intelligence

Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature makes it difficult to diagnose until a late stage. The diagnosis of glaucoma is a complicated and expensive effort that is heavily dependent on the experience and expertise of a clinician. The application of artificial intelligence (AI) algorithms in ophthalmology has improved our understanding of many retinal, macular, choroidal and corneal pathologies. With the advent of deep learning, a number of tools for the classification, segmentation and enhancement of ocular images have been developed. Over the years, several AI techniques have been proposed to help detect glaucoma by analysis of functional and/or structural evaluations of the eye. Moreover, the use of AI has also been explored to improve the reliability of ascribing disease prognosis. This review summarises the role of AI in the diagnosis and prognosis of glaucoma, discusses the advantages and challenges of using AI systems in clinics and predicts likely areas of future progress

Exploring experiences of infertility amongst women and men in low-income and middle-income countries: Protocol for a qualitative systematic review

Introduction: Infertility is increasingly recognised as a global public health issue for women and men that merits further investigation to support policy and programming. While research in high-income settings has examined the consequences of infertility and access to services, there has been limited synthesis of how individuals experience infertility in low-income and middle-income countries (LMICs). This protocol describes a systematic review that will synthesise qualitative evidence on experiences of infertility among women and men in LMICs. Methods and analysis: The review will follow the Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) guidelines for reporting on qualitative evidence syntheses. The study team will search for published literature in PubMed, CINAHL and Scopus and PsycINFO databases and review available grey literature. Using Covidence software, two independent reviewers will conduct title and abstract screening based on inclusion and exclusion criteria, followed by full-text reviews and extraction by a larger team. Quality will be appraised using an adapted version of the Critical Appraisal Skills Programme guidelines. We will conduct thematic synthesis to characterise individual experiences and related factors at the individual, interpersonal, community and health system levels. We will develop a conceptual framework to describe evidence on experiences of infertility in LMICs and to help inform interventions across settings. Ethics and dissemination: This protocol has been internally approved as exempt by the Institutional Review Board of the Population Council, as it does not involve contact with human subjects or personally identifying data. Results of the review will be published in a peer-reviewed journal and will be used to inform future infertility research and programming in LMICs