Electrical mismatch within single junction amorphous silicon and micromorph tandem thin film PV modules

Due to the electrical mismatch between the individual cells, the actual efficiency of a PV module is always lower than the sum of the cells under normal measurement conditions. The effect of this electrical mismatch is simulated for single junction amorphous silicon PV modules as well as micromorph thin film PV modules. This paper reports on the design of the realistic parameter distribution for the I-V simulation. It shows that due to the current mismatch in a double junction solar cell, these devices seem to be more significantly affected by similar variation in parameters, which would indicate that tighter production control is necessary but also that it will be more involved to measure these devices with sufficient accuracy. It is shown that device mismatch actually results in a lower fill factor, which is slightly different to what is seen for single cells

The spectral variation effects on energy yield of optimized multi-junction solar cell

The effect of spectral variations on the maximal achievable efficiency of multi-junction solar cells is investigated in this paper. The energy yield rather than power rating are considered here. With the optimized band gaps under STC the average and annual efficiency for spectral irradiances measured at CREST in a wavelength range from 310-1710nm is calculated. The material band gap optimised for the measured average annual spectrum and for STC spectrum are compared. The annual efficiency and the annual yield of multi-junction solar cells are calculated. It shows that optimum material band gaps shift for a spectrum deviates from AM1.5 which indicates that the spectral effects should be taken into account to optimize multi-junction solar cell structure and system design. The energy generated in Loughborough is calculated for one year and it is shown that the performance ratio of multi-junction solar cells optimized under realistic condition is significantly reduced

Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models: A Case Study on ChatGPT

Generative large language models (LLMs), e.g., ChatGPT, have demonstrated remarkable proficiency across several NLP tasks, such as machine translation, text summarization. Recent research (Kocmi and Federmann, 2023) has shown that utilizing ChatGPT for assessing the quality of machine translation (MT) achieves state-of-the-art performance at the system level but performs poorly at the segment level. To further improve the performance of LLMs on MT quality assessment, we conduct an investigation into several prompting methods, and propose a new prompting method called Error Analysis Prompting (EAPrompt) by combining Chain-of-Thoughts (Wei et al., 2022) and Error Analysis (Lu et al., 2022). Our results on WMT22 indicate that prompting LLMs like ChatGPT with error analysis can generate human-like MT evaluations at both the system and segment level. Additionally, we first discover some limitations of ChatGPT as an MT evaluator, such as changing the order of input may significantly influence the judgment when providing multiple translations in a single query. This work provides a preliminary experience of prompting LLMs as an evaluator to improve the reliability of translation evaluation metrics under the error analysis paradigm

Visualising Co nanoparticle aggregation and encapsulation in Co/TiO2 catalysts and its mitigation through surfactant residues

Due to the reducible nature of TiO2, the encapsulation of cobalt nanoparticles (CoNPs) by reduced TiO2-x is often reported to decrease their catalytic performance in reactions such as Fisher-Tropsch synthesis (FTS). Here, we show using HAADF-STEM imaging and electron energy loss spectroscopy (EELS) that a residual C12E4 surfactant used to prepare the CoNPs, remains on the surface of a TiO2 rutile support, preventing the formation of Ti3+/Ti2+ oxides and therefore TiO2-x migration. Furthermore, the presence of these surfactant residues prevents the coalescence and aggregation of CoNPs during catalyst preparation, maintaining the dispersion of CoNPs. As such, using C12E4 in the preparation of Co/TiO2 can be considered beneficial for producing a catalyst with a greater number of active Co species

Observational energy transfers of a spiral cold filament within an anticyclonic eddy

The ocean surface mixed layer represents a critical interface linking the ocean and atmosphere. The physical processes determining the surface mixed layer properties and mediate atmosphere-ocean exchange. Submesoscale processes play a key role in cross-scale oceanic energy transformation and the determination of surface mixed-layer properties, including the enhancement of vertical nutrient transport, leading to increased primary productivity. Herein, we presented observations of the spiral chlorophyll-a filament and its influence on turbulence within an anticyclonic eddy in the western South China Sea during August 2021. The filament had a negative Ertel potential vorticity associated with strong upwelled/downward currents (approximately 20-40 m/day). Across-filament sections of the in-situ profiles showed turbulent dissipation rates enhanced in the filament. We suggested this enhancement values can be attributed to submesoscale processes, which accounted for 25% of the total parameterized turbulent dissipation rates. The present parametrized submesoscale turbulent scheme overestimated the in-situ values. The filament transferred kinetic energy upward to anticyclonic eddy via barotropic instability and gained energy from the anticyclonic eddy via baroclinic instability. After kinetic energy budget diagnostic, we suggested besides symmetric instability, centrifugal instability and mixed layer baroclinic instability should also be included in the turbulence scheme to overcome the overestimation. The observed dual energy transfers between the anticyclonic eddy and filament, and the observed high turbulent energy dissipation within the filament, emphasized the need for these processes to be accurately parameterized regional and climate models

Deep Reinforcement Learning Based System for Intraoperative Hyperspectral Video Autofocusing

Hyperspectral imaging (HSI) captures a greater level of spectral detail than traditional optical imaging, making it a potentially valuable intraoperative tool when precise tissue differentiation is essential. Hardware limitations of current optical systems used for handheld real-time video HSI result in a limited focal depth, thereby posing usability issues for integration of the technology into the operating room. This work integrates a focus-tunable liquid lens into a video HSI exoscope, and proposes novel video autofocusing methods based on deep reinforcement learning. A first-of-its-kind robotic focal-time scan was performed to create a realistic and reproducible testing dataset. We benchmarked our proposed autofocus algorithm against traditional policies, and found our novel approach to perform significantly ($p<0.05$) better than traditional techniques ($0.070\pm.098$ mean absolute focal error compared to $0.146\pm.148$). In addition, we performed a blinded usability trial by having two neurosurgeons compare the system with different autofocus policies, and found our novel approach to be the most favourable, making our system a desirable addition for intraoperative HSI.Comment: To be presented at MICCAI 202

Gold nanoparticles assembled with dithiocarbamate-anchored molecular wires

A protocol for the bottom-up self-assembly of nanogaps is developed through molecular linking of gold nanoparticles (AuNPs). Two €-conjugated oligo(phenylene ethynylene) molecules (OPE) with dithiocarbamate anchoring groups are used as ligands for the AuNPs. OPE-4S with a dithiocarbamate in each end of the molecule and a reference molecule OPE-2S with only a single dithiocarbamate end group. The linking mechanism of OPE-4S is investigated by using a combination of TEM, UV-Vis absorption and surface enhanced Raman spectroscopy (SERS) as well as studying the effect of varying the OPE-4S to AuNP concentration ratio. UV-Vis absorption confirms the formation of AuNP aggregates by the appearance of an extended plasmon band (EPB) for which the red shift and intensity depend on the OPE-4S:AuNP ratio. SERS confirms the presence of OPE-4S and shows a gradual increase of the signal intensity with increasing OPE-4S:AuNP ratios up to a ratio of about 4000, after which the SERS intensity does not increase significantly. For OPE-2S, no linking is observed below full coverage of the AuNPs indicating that the observed aggregate formation at high OPE-2S:AuNP ratios, above full AuNP coverage, is most likely of a physical nature (van der Waals forces or €-€ interactions)

The spectral variation effects on energy yield of optimized multi-junction solar cell

The effect of spectral variations on the maximal achievable efficiency of multi-junction solar cells is investigated in this paper. The energy yield rather than power rating are considered here. With the optimized band gaps under STC the average and annual efficiency for spectral irradiances measured at CREST in a wavelength range from 310-1710nm is calculated. The material band gap optimised for the measured average annual spectrum and for STC spectrum are compared. The annual efficiency and the annual yield of multi-junction solar cells are calculated. It shows that optimum material band gaps shift for a spectrum deviates from AM1.5 which indicates that the spectral effects should be taken into account to optimize multi-junction solar cell structure and system design. The energy generated in Loughborough is calculated for one year and it is shown that the performance ratio of multi-junction solar cells optimized under realistic condition is significantly reduced