Poly(amic acid)-Polyimide Copolymer Interfacial Layers for Self-Powered CHNHPbI Photovoltaic Photodiodes.

Hybrid organohalide perovskites have received considerable attention due to their exceptional photovoltaic (PV) conversion efficiencies in optoelectronic devices. In this study, we report the development of a highly sensitive, self-powered perovskite-based photovoltaic photodiode (PVPD) fabricated by incorporating a poly(amic acid)-polyimide (PAA-PI) copolymer as an interfacial layer between a methylammonium lead iodide (CHNHPbI, MAPbI) perovskite light-absorbing layer and a poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (PEDOT: PSS) hole injection layer. The PAA-PI interfacial layer effectively suppresses carrier recombination at the interfaces, resulting in a high power conversion efficiency () of 11.

Slurry Synthesis and Thin-Film Fabrication Toward Production of Li₂O-B₂O₃-Al₂O₃-Based Multilayer Oxide Solid-State Batteries for Internet of Things Applications.

Developing thin-film sheets made of oxide-based solid electrolytes is essential for fabricating surface-mounted ultracompact multilayer oxide solid-state batteries. To this end, solid-electrolyte slurry must be optimized for excellent dispersibility. Although oxide-based solid electrolytes for multilayer structures require sintering, high processing temperatures cause problems such as Li-ion volatilization and reactions with graphite anodes.

Outcomes of Calcaneal Lengthening Osteotomy in Ambulatory Patients with Cerebral Palsy and Planovalgus Foot Deformity.

Background: To date, no studies have evaluated the longevity of calcaneal lengthening osteotomy (CLO) in patients with cerebral palsy (CP) and pes planovalgus. This study aimed to explore the changes in foot alignment following CLO in patients with CP, utilizing both radiographic evaluations and dynamic foot-pressure assessments.

Methods: A retrospective study of 282 feet in 180 ambulatory patients was performed.

A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.

Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.

Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.

Quantifying the variation patterns and environmental controls of forest litterfall: A regional synthesis of ecological data across South Korea.

Enhancing the strength of forest carbon sinks is critical in the wake of the accelerating global climate change and intensifying greenhouse effect. However, the regional patterns and environmental controls of forest litter, a major carbon pool and entry pathway from tree-to-soil systems, remain uncertain. Herein, we consolidated up to a decade of data from six ecological studies (totaling 28 stands) conducted across South Korea between 1999 and 2022 (spanning 23 years) to examine variations in total and component-based litterfall with geo-topography and climate.