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Combining cellulose substrates and perovskites in sustainable solar cells is possible:a systematic literature review offering realistic solutions
No full textThe aim of this article is to provide direction for the advancement of cellulose films as sustainable substrates for perovskite solar cells (PSCs). Cellulose, the most abundant biopolymer on Earth, represents a viable, renewable alternative to glass and synthetic polymers when subjected to appropriate modifications. It can be customized via crosslinking, plasticization, and functionalization to increase flexibility and solvent resistance while decreasing gas permeation, surface roughness, and thermal expansion. The adoption of cellulose can drive transformative changes in PSC processing, facilitating the integration of sustainable electrode materials and greener alternatives to toxic solvents, as well as the replacement of high-temperature treatments. Although the literature contains numerous solutions to specific challenges, these findings are scattered across different fields and must be critically assessed for PSC suitability. In this article, we critically review alternative fabrication methods and form a step-by-step multidisciplinary strategy to alter both cellulose and PSC fabrication protocols for the development of sustainable next-generation solar cells.</p
Beyond human proxies: The roles and usefulness of large language models in user research for mobility service development
No full textUser research is an integral part of mobility service development. However, user research is resource-intensive, including the effort required to recruit participants, and facilitate data collection procedures. Consequently, large language models (LLM) have been applied in the domain, building on the notion of LLMs being able to provide human-like outputs and thus simulate human users. Despite the increasing interest, guidelines for LLM implementation in user research processes and for evaluating the usefulness of LLM incorporation remain scarce, hindering researchers and practitioners from leveraging them effectively. Therefore, with the aim of providing a structured understanding of LLM integration, we delineate four main roles LLMs can play in user research (i.e., replace, complement, improve, research), along with three facets (i.e., realism, novelty, effort) for evaluating their usefulness. Combining the roles and usefulness facets, we introduce a framework for how LLMs could be used and what are the conditions for realizing their benefits. Additionally, we describe a hypothetical user research path, applying the approach to the development of new mobility services. The framework presents how and why LLMs could be used in various user research stages, providing a structured lens that aids researchers and practitioners to critically consider when and how to incorporate LLMs, and to evaluate LLM output usefulness, while considering the risks for doing so from the perspective of successful service design. By adopting a pragmatic and critical approach, the paper contributes to research on mobility, as well as more broadly on the use of synthetic participants in design praxis.</p
Strategic niobium integration and thermomechanical processing in the advancement of novel CMnSiAlPMo TRIP-aided bainitic steel
No full textThis study examines the effects of niobium (Nb) addition and different thermomechanical controlled processing (TMCP) regimes on the flow stress behaviour and microstructure evolution of a newly developed CMnSiAlPMo TRIP-aided bainitic steel. TMCP tests were conducted with various hot deformation passes, followed by austempering at 400 °C for 10 min using a Gleeble 3800 thermomechanical simulator. Microstructures were analysed using scanning electron microscopy with electron backscattering diffraction and X-ray diffraction. Results showed that increasing the number of passes and reducing the final deformation temperature (FDT) enhanced the flow behaviour for both 0Nb and 0.05Nb alloys, with strain hardening being the dominant mechanism across all regimes. The four-pass regime with an FDT of 850 °C for the 0Nb alloy achieved the highest hardness (457 HV), attributed to grain refinement, which was more influential than the retained austenite fraction. For the 0.05Nb alloy, the two-pass regime at 1050 °C showed the highest hardness (428 HV), resulting from a lower retained austenite fraction. Additionally, Nb addition significantly refined the microstructure and increased the peak flow stress from 385 MPa to 421 MPa for the four-pass regime. The prior austenite grain size decreased from 23 to 12 μm in the single-pass regime, and the largest grain size in the cumulative grain size distribution (D90%) decreased from 8.45 to 7.49 μm.</p
Static Light Scattering for Lignin Particle Size Characterization
No full textLignin, a widely available and renewable organic polymer, has several desirable properties and applications. However, as a by-product of pulp and paper industry, it is mainly burned for energy. Limited understanding of the complex and heterogeneous structure and a shortage of tailored analysis methods hinder its utilization in higher value applications. This study describes and compares the use of two different static light scattering methods, laser diffraction and small-angle light scattering (SALS), for studying lignin particle size in suspension. The results from laser diffraction showed that the selected particle concentration and absorption coefficient affect the measured sizes especially for particles <1 µm in diameter. For irregularly shaped particles with broad size distributions, sampling is the most important parameter affecting the results. SALS proved an efficient method for obtaining information on particle aggregation by providing primary particle sizes as well as aggregate sizes. Characterization of samples with spherical particles and narrow size distributions is straightforward with both laser diffraction and SALS, whereas the interpretation of results for more heterogeneous samples is less obvious. Static light scattering methods could make lignin particle size analysis more rapid and automated, thus enhancing lignin valorization, but should be applied carefully to avoid systematic errors
Oxide Formation at the Sulfide Film-Copper Interface in Anoxic Sulfide Solution and On-Line Sulfide Detection Via Linear Polarization Resistance
Get PDFThe observation of a thin oxide film on oxygen free phosphorous doped copper after several days of exposure in supposedly anoxic conditions poses several questions, where the most straight-forward answers regarding sample preparation and handling is oftentimes overlooked. In an effort to minimize the environmental factors contributing to the oxide formation on the copper surface, a flow through cell arrangement was built to investigate the oxide formation at the Cu–Cu2S interface after exposure to anoxic sulfide containing phosphate buffer solution. The post exposure characterization by scanning electron microscopy and focused ion beam revealed no oxide formation on the copper surface in the absence of oxygen, while the exposure of the copper surface during the metallographic sample preparation phase, which employs the use of aerated water, causes the formation of copper oxide. Furthermore, a novel technique for noninvasive, semi-quantitative, and on-line sulfide determination is presented. The anodic current density determined from the linear polarization resistance of copper in sulfide solution was found to linearly increase with sulfide concentration.</p
Implementing internal independent nuclear safety oversight – Insights from a Nordic empirical case study
No full textIndependent Nuclear Safety Oversight (INSO) is an internal organizational function that aims to provide nuclear licensee organizations an independent overview of their nuclear safety situation. This article provides an overview of the implementation and impact of INSO based on an empirical, qualitative case study in three Nordic nuclear power companies. INSO was perceived to contribute to nuclear safety by providing independent challenge of the line activities and decisions, advising and supporting the line organization and senior management, and providing an independent overview of nuclear safety. The implementation challenges were often managerial and included the underutilization of INSO recommendations by top management, lack of agreement between INSO and the line organization regarding INSO’s role, tasks, and results, and the unavailability of resources for conducting INSO activities. Our results also suggest that internal independence is not a black and white phenomenon and that there is no universally correct level of independence. Internal independence involves continuously and intelligently managing the tension between being isolated and losing perspective. The article concludes with recommendations for improving the effectiveness of INSO in global nuclear industry and suggests future development needs
Enhanced YOLOv8 Model for Accurate and Real-Time Remote Sensing Target Detection
No full textCurrent remote sensing image object detection algorithms often struggle with false positives, missed targets, and suboptimal accuracy. To address these issues, we propose an improved YOLOv8 network (PIYN) solution achieved through targeted modifications to the YOLOv8 architecture. The backbone of YOLOv8 utilizes a Cross-Stage Partial (CSP) structure that includes two convolutions, called a faster C2f module. Firstly, we infuse the C2f module integrating an Efficient Multi-Scale Attention (EMA) mechanism, which enhances the module's ability to process information across various scales. Secondly, we introduce a Compact Path Aggregation Network (Compact-PAN) structure within the neck of the network, which reduces the computational complexity of the model. Finally, replacing the Complete Intersection over Union (CIoU) loss function with the Weighted Intersection over Union (WIoU) loss refines the model's detection accuracy. Additionally, we applied K-fold cross-validation on the dataset to mitigate overfitting. Experiments using the extensive Dataset for Object Detection in Aerial images (DOTA) and the Dataset for Object Recognition in Optical Remote Sensing Imagery (DIOR) reveal PIYN's effectiveness: there is a 2.43% and 2.56% increase in Mean Average Precision (mAP) over YOLOv8, respectively, alongside a 4.49% reduction in GFLOPs. These results demonstrate PIYN's capability to enhance accuracy while maintaining efficiency and solidify its progressive and practical impact, particularly for smart city applications
Preparation and Papermaking Properties of Dry-Cut Powder from Chemically Crosslinked BEKP
No full textChemical crosslinking of cellulosic fibers increases their brittleness, making them more susceptible to dry powdering. In this study, bleached eucalyptus kraft pulp (BEKP) sheets were crosslinked with glyoxal (GO) and citric acid (CA) and subsequently dry cut into powders using a Wiley cutting mill. Key variables in the powder preparation were dosages of GO and CA, as well as their respective catalysts, aluminum sulphate (alum) and sodium hypophosphite (SHP). The average fiber length of the GO and CA crosslinked pulps was reduced, at most down to 0.12 and 0.17 mm by the dry cutting, using a 0.5 mm perforated screen in the final dry-cutting stage. The powders exhibited reduced water retention, lower sedimentation volume in water, and, when dry, showed increased tapped and bulk densities. When mixed with refined BEKP, the powders enhanced dewatering during handsheet formation and improved the resulting sheets’ bulk, light scattering, and opacity, while reducing tensile strength. These findings suggest that chemically crosslinked pulp powders have potential as a bulking and dewatering aid in papermaking. Furthermore, due to their low water absorbency and presumable low abrasiveness, the powder may have potential applications beyond papermaking, such as filler of plastics, glues, and coating materials
Automating Customer Feedback Analysis in E-commerce: A Multi-Model Approach
No full textUnderstanding customer satisfaction in e-commerce is crucial for businesses to remain competitive. While traditional feedback analysis methods are labour-intensive and subjective, machine learning advances have enabled more efficient and scalable sentiment analysis. However, existing models struggle with aspect-based sentiment analysis (ABSA), particularly in detecting implicit aspects and handling mixed sentiments. This paper presents a multi-model machine learning pipeline designed to enhance ABSA by integrating fine-tuned Large Language Models (LLMs) with BERT and RoBERTa-based models. The pipeline consists of an LLM-generated synthesized annotated feedback model, a BERT-based aspect detection model, a RoBERTa-based ABSA model, and an LLM-based ABSA model for handling implicit aspects and mixed sentiments. Additionally, a RoBERTa-based model is employed for overall sentiment detection. By leveraging both manually annotated and synthetic data, the pipeline improves sentiment classification accuracy and aspect coverage, even in data-scarce environments. The results demonstrate that combining multiple models enhances detection accuracy compared to single-model approaches. This study provides a scalable and effective solution for e-commerce feedback analysis, offering businesses valuable insights for improving customer experience and decision-making
A probabilistic-driven approach for early design quality risk and crux identification using non-Markovian stochastic Petri nets
Get PDFQuality risk analysis of high-process-oriented systems, which refers to their ability to achieve required tasks on time, receives little attention during the early conceptual design stage, primarily due to the high level of abstraction when the system form is not yet fully defined. Although several mathematical methods exist to address this issue, they are fragmented across domains and lack a unified integration into early design practice. To address this problem, this paper introduces a novel approach that models design problems as discrete events with output conflict representation, using the non-Markovian stochastic Petri net. The framework is further integrated with mathematical techniques, including semi-Markov performance evaluation, sensitivity analysis, and uncertainty analysis, to quantify quality risks and identify the design crux (the most critical design parameters). By incorporating Monte Carlo simulations, it facilitates designers and engineers with early insights and allows them to compare alternative design specifications. Its applicability is demonstrated through a case study on the conceptual development of a remote maintenance system for the In-Bioshield area of the EU-DEMO fusion power plant. Initial results showed potential in identifying quality risks, addressing key factors contributing to the design problem, and finding optimal design specifications in the early stages