Parameter Estimation of Photovoltaic Cell/Modules Using Bonobo Optimizer

In this paper, a new application of Bonobo (BO) metaheuristic optimizer is presented for PV parameter extraction. Its processes depict a reproductive approach and the social conduct of Bonobos. The BO algorithm is employed to extract the parameters of both the single diode and double diode model. The good performance of the BO is experimentally investigated on three commercial PV modules (STM6-40 and STP6-120/36) and an R.T.C. France silicon solar cell under various operating circumstances. The algorithm is easy to implement with less computational time. BO is extensively compared to other state of the art algorithms, manta ray foraging optimization (MRFO), artificial bee colony (ABO), particle swarm optimization (PSO), flower pollination algorithm (FPA), and supply-demand-based optimization (SDO) algorithms. Throughout the 50 runs, the BO algorithm has the best performance in terms of minimal simulation time for the R.T.C. France silicon, STM6-40/36 and STP6-120/36 modules. The fitness results obtained through root mean square (RMSE), standard deviation (SD), and consistency of solution demonstrate the robustness of BO.

Impact and recent approaches of high-efficiency solar cell modules for PV-powered vehicles

Photovoltaic (PV)-powered vehicles are expected to play a critical role in a future carbon neutrality society because it has been reported that the vehicle integrated PVs (VIPVs) have great ability to reduce CO2 emission from the transport sector. Development of high-efficiency solar cell modules is very important for this end. In this paper, analytical results for impact of high-efficiency solar cell modules on increases in electric vehicle (EV) driving distance, reducing CO2 emission and saving charging cost of EV powered by PV are shown. The III-V triple-junction and Si tandem solar cell modules with an efficiency of more than 35% have potential of the EV driving distance of more than 30 km/day on average and more than 50 km/day on a clear day. The effects of temperature, partial shading, curved surface and color variation of solar cell modules upon output power of the VIPV are also briefly shown.

Living material assembly of bacteriogenic protocells

Advancing the spontaneous bottom-up construction of artificial cells with high organisational complexity and diverse functionality remains an unresolved issue at the interface between living and non-living matter. To address this challenge, a living material assembly process based on the capture and on-site processing of spatially segregated bacterial colonies within individual coacervate micro-droplets is developed for the endogenous construction of membrane-bounded, molecularly crowded, compositionally, structurally and morphologically complex synthetic cells. The bacteriogenic protocells inherit diverse biological components, exhibit multi-functional cytomimetic properties and can be endogenously remodelled to include a spatially partitioned DNA/histone nucleus-like condensate, membranized water vacuoles and a self-supporting 3D network of F-actin proto-cytoskeletal filaments. The ensemble is biochemically energized by self-sustainable ATP production derived from implanted live E. coli cells to produce a cellular bionic system with amoeba-like external morphology and integrated life-like properties. Our results demonstrate a novel bacteriogenic strategy for the bottom-up construction of functional protoliving micro-devices and provide opportunities for the fabrication of new synthetic cell modules and augmented living/synthetic cell constructs with potential applications in engineered synthetic biology and biotechnology.

Liquid Crystalline Cholesteric Reflective Layers for Colored Silicon-Based Solar Cells

The performance of a prototype opaque-type colored silicon-based solar cell integrated with liquid crystalline cholesteric layers is investigated. These devices were developed using only organic components and wet processes, without complicated vacuum processes. The evaluated performances of the prototype solar cells were inferior to those of the other types of previously reported colored solar cells because of the inherent limitations of the cholesteric layers, such as the limited reflectance (~50%), narrow color gamut, and viewing angle-dependent color changes. We propose effective strategies for improving the performance of colored solar cell modules integrated with cholesteric layers.

Spontaneous emergence of topologically robust grid cell modules: A multiscale instability theory

Modular structures in the brain play a central role in compositionality and intelligence, however the general mechanisms driving module emergence have remained elusive. Studying entorhinal grid cells as paradigmatic examples of modular architecture and function, we demonstrate the spontaneous emergence of a small number of discrete spatial and functional modules from an interplay between continuously varying lateral interactions generated by smooth cortical gradients. We derive a comprehensive analytic theory of modularization, revealing that the process is highly generic with its robustness deriving from topological origins. The theory generates universal predictions for the sequence of grid period ratios, furnishing the most accurate explanation of grid cell data to date. Altogether, this work reveals novel principles by which simple bottom-up dynamical interactions lead to macroscopic modular organization.

One-pot synthesis of (R)- and (S)-phenylglycinol from bio-based l-phenylalanine by an artificial biocatalytic cascade

Chiral phenylglycinol is a very important chemical in the pharmaceutical manufacturing. Current methods for synthesis of chiral phenylglycinol often suffered from unsatisfied selectivity, low product yield and using the non-renewable resourced substrates, then the synthesis of chiral phenylglycinol remain a grand challenge. Design and construction of synthetic microbial consortia is a promising strategy to convert bio-based materials into high value-added chiral compounds. In this study, we reported a six-step artificial cascade biocatalysis system for conversion of bio-based l-phenylalanine into chiral phenylglycinol. This system was designed using a microbial consortium including two engineered recombinant Escherichia coli cell modules, one recombinant E. coli cell module co-expressed six different enzymes (phenylalanine ammonia lyase/ferulic acid decarboxylase/phenylacrylic acid decarboxylase/styrene monooxygenase/epoxide hydrolase/alcohol dehydrogenase) for efficient conversion of l-phenylalanine into 2-hydroxyacetophenone. The second recombinant E. coli cell module expressed an (R)-ω-transaminase or co-expressed the (S)-ω-transaminase, alanine dehydrogenase and glucose dehydrogenase for conversion of 2-hydroxyacetophenone into (S)- or (R)-phenylglycinol, respectively. Combining the two engineered E. coli cell modules, after the optimization of bioconversion conditions (including pH, temperature, glucose concentration, amine donor concentration and cell ratio), l-phenylalanine could be easily converted into (R)-phenylglycinol and (S)-phenylglycinol with up to 99% conversion and > 99% ee. Preparative scale biotransformation was also conducted on 100-mL scale, (S)-phenylglycinol and (R)-phenylglycinol could be obtained in 71.0% and 80.5% yields, > 99% ee, and 5.19 g/L d and 4.42 g/L d productivity, respectively. The salient features of this biocatalytic cascade system are good yields, excellent ee, mild reaction condition and no need for additional cofactor (NADH/NAD+), provide a practical biocatalytic method for sustainable synthesis of (S)-phenylglycinol and (R)-phenylglycinol from bio-based L-phenylalanine.

Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues

The representation of an animal's position in the medial entorhinal cortex (MEC) is distributed across several modules of grid cells, each characterized by a distinct spatial scale. The population activity within each module is tightly coordinated and preserved across environments and behavioral states. Little is known, however, about the coordination of activity patterns across modules. We analyzed the joint activity patterns of hundreds of grid cells simultaneously recorded in animals that were foraging either in the light, when sensory cues could stabilize the representation, or in darkness, when such stabilization was disrupted. We found that the states of different grid modules are tightly coordinated, even in darkness, when the internal representation of position within the MEC deviates substantially from the true position of the animal. These findings suggest that internal brain mechanisms dynamically coordinate the representation of position in different modules, to ensure that grid cells jointly encode a coherent and smooth trajectory of the animal.