Impact of macroporosity on catalytic upgrading of fast pyrolysis bio-oil by esterification over silica sulfonic acids

Fast pyrolysis bio-oils possess unfavourable physicochemical properties and poor stability, due in large part to the presence of carboxylic acids, which hinders their use as biofuels. Catalytic esterification offers an atom and energy efficient route to upgrade pyrolysis bio-oils. Propyl sulfonic acid silicas are active for carboxylic acid esterification but suffer mass-transport limitations for bulky substrates. Macropore (200 nm) incorporation enhances the activity of mesoporous SBA-15 architectures (post-functionalised by hydrothermal saline promoted grafting) for the esterification of linear carboxylic acids, with the magnitude of turnover frequency (TOF) enhancement increasing with chain length from 5 % (C3) to 110 % (C12). Macroporous-mesoporous PrSO3H/SBA-15 also offers a two-fold TOF enhancement over its mesoporous analogue for the esterification of a real thermal fast pyrolysis bio-oil derived from woodchips. The total acid number was reduced by 57 %, with GCxGC-ToFMS evidencing ester and ether formation accompanying loss of acid, phenolic, aldehyde and ketone components

AI-Enabled Predictive Maintenance Framework for Autonomous Mobile Cleaning Robots

Vibration is an indicator of performance degradation or operational safety issues of mobile cleaning robots. Therefore, predicting the source of vibration at an early stage will help to avoid functional losses and hazardous operational environments. This work presents an artificial intelligence (AI)-enabled predictive maintenance framework for mobile cleaning robots to identify performance degradation and operational safety issues through vibration signals. A four-layer 1D CNN framework was developed and trained with a vibration signals dataset generated from the in-house developed autonomous steam mopping robot ‘Snail’ with different health conditions and hazardous operational environments. The vibration signals were collected using an IMU sensor and categorized into five classes: normal operational vibration, hazardous terrain induced vibration, collision-induced vibration, loose assembly induced vibration, and structure imbalanced vibration signals. The performance of the trained predictive maintenance framework was evaluated with various real-time field trials with statistical measurement metrics. The experiment results indicate that our proposed predictive maintenance framework has accurately predicted the performance degradation and operational safety issues by analyzing the vibration signal patterns raised from the cleaning robot on different test scenarios. Finally, a predictive maintenance map was generated by fusing the vibration signal class on the cartographer SLAM algorithm-generated 2D environment map

Adaptive Decentralized Payback Normalization for Socio-Economic Rebalancing of RE subsidies - A Case Study

Clean energy subsidies are designed to stimulate consumer participation and deliver greater benefits to society. India has a fixed centralised federal subsidy model for residential rooftop solar (RTS). Different states have different tariff schemes for electricity consumption and RTS feed-in. Thus, grid parity, payback period (PBP), and willingness to pay (WTP) differ for consumers of different states and income classes, resulting in social and geographical disparity in RTS implementation. A Socio-Economic Rebalancing of RE subsidies thus becomes necessary. This paper proposes a novel adaptive decentralised heterogeneous PBP equalisation-based subsidy policy to enhance the WTP for all prosumers and ensure uniformity of RTS implementation. A two-stage subsidy optimisation is conducted using a case study in diverse states to achieve Grid Parity initially and subsequently desired PBP for all states and income classes. The proposed subsidy ensures grid parity for all, sufficient to transit all the prosumers to 100% net electricity from RTS. The subsidy is further normalised by equalising the PBP to a target PBP thereby ensuring uniformity of RTS implementation in the country bridging the rural-urban WTP disparity, leading to a better social scenario. The strategy is adaptive to the future, as the subsidy can be revised with changes in techno-economic parameters

Modified A-Star Algorithm for Efficient Coverage Path Planning in Tetris Inspired Self-Reconfigurable Robot with Integrated Laser Sensor

Advancing an efficient coverage path planning in robots set up for application such as cleaning, painting and mining are becoming more crucial. Such drive in the coverage path planning field proposes numerous techniques over the past few decades. However, the proposed approaches were only applied and tested with a fixed morphological robot in which the coverage performance was significantly degraded in a complex environment. To this end, an A-star based zigzag global planner for a novel self-reconfigurable Tetris inspired cleaning robot (hTetro) presented in this paper. Unlike the traditional A-star algorithm, the presented approach can generate waypoints in order to cover the narrow spaces while assuming appropriate morphology of the hTtero robot with the objective of maximizing the coverage area. We validated the efficiency of the proposed planning approach in the Robot Operation System (ROS) Based simulated environment and tested with the hTetro robot in real-time under the controlled scenarios. Our experiments demonstrate the efficiency of the proposed coverage path planning approach resulting in superior area coverage performance in all considered experimental scenarios

Continuous minimally-invasive alcohol monitoring using microneedle sensor arrays.

The present work describes an attractive skin-worn microneedle sensing device for the minimally invasive electrochemical monitoring of subcutaneous alcohol. The device consists of an assembly of pyramidal microneedle structures integrated with Pt and Ag wires, each with a microcavity opening. The microneedle aperture was modified by electropolymerizing o-phenylene diamine onto the Pt wire microtransducer, followed by the immobilization of alcohol oxidase (AOx) in an intermediate chitosan layer, along with an outer Nafion layer. The resulting microneedle-based enzyme electrode displays an interference-free ethanol detection in artificial interstitial fluid without compromising its sensitivity, stability and response time. The skin penetration ability and the efficaciousness of the biosensor performance towards subcutaneous alcohol monitoring was substantiated by the ex vivo mice skin model analysis. Our results reveal that the new microneedle sensor holds considerable promise for continuous non-invasive alcohol monitoring in real-life situations

Continuous minimally-invasive alcohol monitoring using microneedle sensor arrays.

The present work describes an attractive skin-worn microneedle sensing device for the minimally invasive electrochemical monitoring of subcutaneous alcohol. The device consists of an assembly of pyramidal microneedle structures integrated with Pt and Ag wires, each with a microcavity opening. The microneedle aperture was modified by electropolymerizing o-phenylene diamine onto the Pt wire microtransducer, followed by the immobilization of alcohol oxidase (AOx) in an intermediate chitosan layer, along with an outer Nafion layer. The resulting microneedle-based enzyme electrode displays an interference-free ethanol detection in artificial interstitial fluid without compromising its sensitivity, stability and response time. The skin penetration ability and the efficaciousness of the biosensor performance towards subcutaneous alcohol monitoring was substantiated by the ex vivo mice skin model analysis. Our results reveal that the new microneedle sensor holds considerable promise for continuous non-invasive alcohol monitoring in real-life situations

Tackling Area Coverage Problems in a Reconfigurable Floor Cleaning Robot Based on Polyomino Tiling Theory

Whilst Polyomino tiling theory has been extensively studied as a branch of research in mathematics, its application has been largely confined to multimedia, graphics and gaming domains. In this paper, we present a novel application of Tromino tiling theory, a class of Polyomino with three cells in the context of a reconfigurable floor cleaning robot, hTromo. The developed robot platform is able to automatically generate a global tiling set required to cover a defined space while leveraging on the Tromino tiling theory. Specifically, we validated the application of five Tromino tiling theorems with our hTromo robot. Experiments performed clearly demonstrate the efficacy of the proposed approach resulting in very high levels of area coverage performance in all considered experimental cases. This paper also presents the system architecture of our hTromo robot and a detailed description of the five tiling theorems applied in this study