scholarly journals Sequential vs integrated CO2 capture and electrochemical conversion: An energy comparison

2021 ◽  
Author(s):  
Mengran Li ◽  
Erdem Irtem ◽  
Hugo Pieter Iglesias van Montfort ◽  
Thomas Burdyny
Keyword(s):  
Co2 Capture ◽  
Early Stage ◽  
Level Energy ◽  
Co2 Conversion ◽  
Performance Targets ◽  
Critical Issues ◽  
And Performance ◽  
Energy Gains ◽  
Carbon Dioxide Co2 ◽  
High Level

Integrating carbon dioxide (CO2) electrolysis with CO2 capture provides new exciting opportunities for energy reductions by simultaneously removing the energy-demanding regeneration step in CO2 capture and avoiding critical issues faced by CO2 gas-fed electrolysers. However, understanding the potential energy advantages of an integrated capture and conversion process is not straightforward. There are only early-stage demonstrations of CO2 conversion from capture media very recently, and an evaluation of the broader process is paramount before claiming any energy gains from the integration. Here we identify the upper limits of the integrated capture and conversion from an energy perspective by comparing the working principles and performance of integrated and sequential CO2 conversion approaches. Our high-level energy analyses unveil that an integrated electrolysis unit must operate below 1000 kJ/molCO2 to ensure an energy benefit of up to 44% versus the existing state-of-the-art sequential route. However, such energy benefits diminish if future gas-fed electrolysers resolve the carbonation issue and if an integrated electrolyser has poor conversion efficiencies. We conclude with opportunities and limitations to develop industrially relevant integrated electrolysis, providing performance targets for novel integrated electrolysis processes.

Electronic Structure Benchmark Calculations of Inorganic and Biochemical Carboxylation Reactions

2018 ◽  
Author(s):  
Oscar A. Douglas-Gallardo ◽  
David A. Sáez ◽  
Stefan Vogt-Geisse ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Electronic Structure ◽  
Chemical Reactions ◽  
Density Functional ◽  
Correlation Energy ◽  
Electronic Energy ◽  
Basis Sets ◽  
Electronic Correlation ◽  
Correct Description ◽  
Carbon Dioxide Co2 ◽  
High Level

<div><div><div><p>Carboxylation reactions represent a very special class of chemical reactions that is characterized by the presence of a carbon dioxide (CO2) molecule as reactive species within its global chemical equation. These reactions work as fundamental gear to accomplish the CO2 fixation and thus to build up more complex molecules through different technological and biochemical processes. In this context, a correct description of the CO2 electronic structure turns out to be crucial to study the chemical and electronic properties associated with this kind of reactions. Here, a sys- tematic study of CO2 electronic structure and its contribution to different carboxylation reaction electronic energies has been carried out by means of several high-level ab-initio post-Hartree Fock (post-HF) and Density Functional Theory (DFT) calculations for a set of biochemistry and inorganic systems. We have found that for a correct description of the CO2 electronic correlation energy it is necessary to include post-CCSD(T) contributions (beyond the gold standard). These high-order excitations are required to properly describe the interactions of the four π-electrons as- sociated with the two degenerated π-molecular orbitals of the CO2 molecule. Likewise, our results show that in some reactions it is possible to obtain accurate reaction electronic energy values with computationally less demanding methods when the error in the electronic correlation energy com- pensates between reactants and products. Furthermore, the provided post-HF reference values allowed to validate different DFT exchange-correlation functionals combined with different basis sets for chemical reactions that are relevant in biochemical CO2 fixing enzymes.</p></div></div></div>

https://imsciences.edu.pk/files/journals/vol12_2/New%201%20MA.864.pdf

2020 ◽  
Vol 12 (2) ◽  
pp. 19-50 ◽  
Author(s):  
Muhammad Siddique ◽  
Shandana Shoaib ◽  
Zahoor Jan
Keyword(s):  
Organizational Performance ◽  
Structural Equation ◽  
High Performance ◽  
Service Sector ◽  
Performance Outcomes ◽  
Theory And Practice ◽  
Relational Coordination ◽  
Multiple Sources ◽  
And Performance ◽  
High Level

A key aspect of work processes in service sector firms is the interconnection between tasks and performance. Relational coordination can play an important role in addressing the issues of coordinating organizational activities due to high level of interdependence complexity in service sector firms. Research has primarily supported the aspect that well devised high performance work systems (HPWS) can intensify organizational performance. There is a growing debate, however, with regard to understanding the “mechanism” linking HPWS and performance outcomes. Using relational coordination theory, this study examines a model that examine the effects of subsets of HPWS, such as motivation, skills and opportunity enhancing HR practices on relational coordination among employees working in reciprocal interdependent job settings. Data were gathered from multiple sources including managers and employees at individual, functional and unit levels to know their understanding in relation to HPWS and relational coordination (RC) in 218 bank branches in Pakistan. Data analysis via structural equation modelling, results suggest that HPWS predicted RC among officers at the unit level. The findings of the study have contributions to both, theory and practice.

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

scholarly journals Towards a contemporary player learning in development framework for sports practitioners

2021 ◽  
pp. 174795412110023
Author(s):  
Mark O Sullivan ◽  
Carl T Woods ◽  
James Vaughan ◽  
Keith Davids
Keyword(s):  
Linear Process ◽  
Task Environment ◽  
Coach Education ◽  
Development Framework ◽  
Novel Approach ◽  
Non Linear ◽  
And Performance ◽  
Learning Development ◽  
High Level ◽  
User Friendly

As it is appreciated that learning is a non-linear process – implying that coaching methodologies in sport should be accommodative – it is reasonable to suggest that player development pathways should also account for this non-linearity. A constraints-led approach (CLA), predicated on the theory of ecological dynamics, has been suggested as a viable framework for capturing the non-linearity of learning, development and performance in sport. The CLA articulates how skills emerge through the interaction of different constraints (task-environment-performer). However, despite its well-established theoretical roots, there are challenges to implementing it in practice. Accordingly, to help practitioners navigate such challenges, this paper proposes a user-friendly framework that demonstrates the benefits of a CLA. Specifically, to conceptualize the non-linear and individualized nature of learning, and how it can inform player development, we apply Adolph’s notion of learning IN development to explain the fundamental ideas of a CLA. We then exemplify a learning IN development framework, based on a CLA, brought to life in a high-level youth football organization. We contend that this framework can provide a novel approach for presenting the key ideas of a CLA and its powerful pedagogic concepts to practitioners at all levels, informing coach education programs, player development frameworks and learning environment designs in sport.

scholarly journals Neighborhood Energy Modeling and Monitoring: A Case Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3716
Author(s):  
Francesco Causone ◽  
Rossano Scoccia ◽  
Martina Pelle ◽  
Paola Colombo ◽  
Mario Motta ◽  
...  
Keyword(s):  
High Performance ◽  
High Efficiency ◽  
Early Stage ◽  
Energy Performance ◽  
Monitoring Plan ◽  
Performance Targets ◽  
Carrier Energy ◽  
Zero Carbon ◽  
Energy Grid

Cities and nations worldwide are pledging to energy and carbon neutral objectives that imply a huge contribution from buildings. High-performance targets, either zero energy or zero carbon, are typically difficult to be reached by single buildings, but groups of properly-managed buildings might reach these ambitious goals. For this purpose we need tools and experiences to model, monitor, manage and optimize buildings and their neighborhood-level systems. The paper describes the activities pursued for the deployment of an advanced energy management system for a multi-carrier energy grid of an existing neighborhood in the area of Milan. The activities included: (i) development of a detailed monitoring plan, (ii) deployment of the monitoring plan, (iii) development of a virtual model of the neighborhood and simulation of the energy performance. Comparisons against early-stage energy monitoring data proved promising and the generation system showed high efficiency (EER equal to 5.84), to be further exploited.

scholarly journals Critical Issues and Opportunities for Producing Biomethane in Italy

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2431
Author(s):  
Roberto Murano ◽  
Natascia Maisano ◽  
Roberta Selvaggi ◽  
Gioacchino Pappalardo ◽  
Biagio Pecorino
Keyword(s):  
Anaerobic Digestion ◽  
Case Studies ◽  
Regulatory Framework ◽  
Biofuel Production ◽  
Political Incentives ◽  
Critical Issues ◽  
Biogas Plants ◽  
High Level ◽  
By Products ◽  
Lack Of Knowledge

Nowadays, most Italian biogas produces electricity even though recent political incentives are promoting biomethane from biogas by “upgrading” it. The aim of this paper is to focus on the regulatory framework for producing biomethane from new or already-existent anaerobic digestion plants. The complexity and lack of knowledge of the regulations on biofuel production and of anaerobic digested biomethane from waste and by-products create difficulties of both interpretation and application. Consequently, the aim of this paper is to analyze the regulations for producing biomethane, underline the critical issues and opportunities, and evaluate whether an electrical plant built in the last 10 years in Italy can really be converted to a biomethane plant, thereby lengthening its lifespan. Three case studies were considered to look more closely into applying Italian biomethane incentives and to simulate the types of incentivization in agriculture with examples based on certain fuel types typical of a standard biomethane plant of 500 standard cubic meter per hour. All the considered cases put in evidence that biomethane is a further opportunity for development with a high level of efficiency for all biogas producers, especially for many biogas plants whose incentivization period is about to finish.

Lung nodule classification using combination of CNN, second and higher order texture features

2021 ◽  
pp. 1-9
Author(s):  
Amrita Naik ◽  
Damodar Reddy Edla
Keyword(s):  
Malignant Tumors ◽  
Early Stage ◽  
Lung Nodule ◽  
Texture Features ◽  
Svm Classifier ◽  
Softmax Classifier ◽  
Spatial Features ◽  
High Level ◽  
Learning Architectures ◽  
Nodule Classification

Lung cancer is the most common cancer throughout the world and identification of malignant tumors at an early stage is needed for diagnosis and treatment of patient thus avoiding the progression to a later stage. In recent times, deep learning architectures such as CNN have shown promising results in effectively identifying malignant tumors in CT scans. In this paper, we combine the CNN features with texture features such as Haralick and Gray level run length matrix features to gather benefits of high level and spatial features extracted from the lung nodules to improve the accuracy of classification. These features are further classified using SVM classifier instead of softmax classifier in order to reduce the overfitting problem. Our model was validated on LUNA dataset and achieved an accuracy of 93.53%, sensitivity of 86.62%, the specificity of 96.55%, and positive predictive value of 94.02%.

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