Understanding the fundamental thermodynamic limits of photo-electrochemical (PEC) water splitting is of great scientific and practical importance. In this work, a 'detailed balance' type model of solar quantum energy converters and non-linear circuit analysis is used to calculate the thermodynamic limiting efficiency of various configurations of PEC design. This model is released as freely accessible open-source (GNU GPL v3) code written in MATLAB with a graphical user interface (GUI). The capabilities of the model are demonstrated by simulating selected permutations of PEC design and results are validated against previous literature. This tool will enable solar fuel researchers to easily compare experimental results to theoretical limits to assess its realised performance using the GUI. Furthermore, the code itself is intended to be extendable and so can be modified to include non-ideal losses such as the over-potential required or complex optical phenomena.
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http://dx.doi.org/10.1038/s41598-018-30959-9 | DOI Listing |
Nanotechnology
January 2025
Qingdao University, Ningxia Road 308, Qingdao, Shandong, 266071, CHINA.
Graphitic carbon nitride (g-C3N4) has gained significant attention as a promising nonmetallic semiconductor photocatalyst due to its photochemical stability, favorable electronic properties, and efficient light absorption. Nevertheless, its practical applications are hindered by limitations such as low specific surface area, rapid recombination of photogenerated charge carriers, poor electrical conductivity, and restricted photo-response ranges. This review explores recent advancements in the synthesis, modification and application of g-C3N4 and its nanocomposites with a focus on addressing these challenges.
View Article and Find Full Text PDFN Z Med J
January 2025
Executive Dean, Bond Business School, Bond University, Gold Coast, QLD, Australia; Harkness Senior Fellow, Commonwealth Fund of New York.
This article makes the case for taking a model-based management approach, specifically using the Viable System Model (VSM), to embed learning and adaptation into the New Zealand health system so it can function as a learning health system. We draw on a case study of a specialist clinical service where the VSM was used to guide semi-structured interviews and workshops with clinicians and managers and to guide analysis of the findings. The VSM analysis revealed a lack of clarity of organisational functioning, and of the systems, processes and integrated IT infrastructure necessary to support the fundamental requirements of a learning health system.
View Article and Find Full Text PDFPLoS Med
January 2025
Division of Infectious Diseases, Department of Medicine II, Medical Centre and Faculty of Medicine, Albert-Ludwigs-University, Freiburg, Germany.
Background: Self-reported health problems following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are common and often include relatively non-specific complaints such as fatigue, exertional dyspnoea, concentration or memory disturbance and sleep problems. The long-term prognosis of such post-acute sequelae of COVID-19/post-COVID-19 syndrome (PCS) is unknown, and data finding and correlating organ dysfunction and pathology with self-reported symptoms in patients with non-recovery from PCS is scarce. We wanted to describe clinical characteristics and diagnostic findings among patients with PCS persisting for >1 year and assessed risk factors for PCS persistence versus improvement.
View Article and Find Full Text PDFBioinformatics
January 2025
Guangdong Provincial Key Laboratory IRADS, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, China.
Motivation: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models have emerged as a promising solution to expedite the annotation process. However, despite making significant progress in protein research, graph neural networks face challenges in capturing long-range structural correlations and identifying critical residues in protein graphs.
View Article and Find Full Text PDFMol Biol Evol
January 2025
Center for Genomics and Systems Biology, Department of Biology, New York University.
Copy-number variants (CNVs) are an important class of genetic variation that can mediate rapid adaptive evolution. Whereas CNVs can increase the relative fitness of the organism, they can also incur a cost due to the associated increased gene expression and repetitive DNA. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus.
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