Real Configuration Research Articles

Unexpected, mystifying but simple three-dimensional dynamic fracture phenomena.

This contribution addresses what can be learnt from our recent experimental observations of dynamic fracture development in brittle solid materials with real three-dimensional configurations. It is pointed out that the three-dimensional dynamic behaviour of (quasi-)brittle solids is essentially different not only from the one-dimensional dynamic one but also from the three-dimensional static one. The experimental observations include those of cylindrical concrete columns pressurized by deflagration at the centre and ice spheres subjected to dynamic impact at the bottom. Surprisingly, plain fracture patterns can be found through these experiments, but it does not seem simple to describe or predict the involved physical process by conventional analytical treatment or numerical simulations. Indeed, our understanding of mechanical details of actual three-dimensional fracture is still limited, especially in dynamic cases where the length scale of fracture and relevant waves is of the order of the size of solids under consideration. Although a more sophisticated physical interpretation including the dynamic interaction of waves in a relatively high-frequency range is required, the discussed dynamics of three-dimensional fracture development will assist in generating precisely controlled dynamic fracture networks that can be used for practical purposes of dismantling solid structural components and mitigating risks of catastrophic failures. This article is part of the theme issue 'Fracture dynamics of solid materials: from particles to the globe'.

Tunable thermoelectric properties of free-standing PEDOT nanofiber film through adjusting its nanostructure

Recently, organic thermoelectric (TE) materials have attracted increasing attention in green energy conversion. However, researches on polymer nanostructured TE materials are still scarce, especially for the 1 D nanostructured polymer materials. In this work, 1D poly(3,4-ethylenedioxythiophene) (PEDOT) nanofiber was synthesized by a self-assembled micellar soft-template approach using anionic surfactant sodium dodecyl sulfate (SDS). Then, a flexible and free-standing PEDOT nanofiber film was prepared through a simple vacuum-assisted filtration method. FE-SEM and TEM characteristics real 1D configuration for all the PEDOT nanostructures. Through adjusting the molar ratio of SDS, oxidizing agent FeCl3 and EDOT monomer (nSDS: nFeCl3: nEDOT), nanofiber with different diameter (10–200 nm) and microtopography can be obtained. Electrical conductivity and Seebeck coefficient measurement indicates that the TE properties of PEDOT can be effectively tuned by adjusting its nanostructure, and a variation range as high as three orders of magnitude for the power factors (10-2–101 μW/mK2) can be realized. Due to a more ordered structure caused by the edge-on packing mode of PEDOT chain, the sample prepared with nSDS: nFeCl3: nEDOT = 30:15:7 shows the highest power factor of 7.2 μW/mK2. This value can be further enhanced to 14.4 μW/mK2 by constructing PEDOT nanofiber/SWCNTs composite.

A new correlation for estimating the gas turbine cost

The recent changes in energy scenario with rising attention to decarbonization, introduction of new technology and renewable source have led to design power plant with the lowest values of cost of energy, investment payback period, CO2 emission, especially in cogeneration and combined cycle plants. The cost of a gas turbine, an industrial key intellectual property value, represents a large portion of total plant capital cost. In fact, the correlations used to determine this cost, represent an important part in the optimization of power plant studied. In this work, a new cost correlation has been determined using gas turbine data presents into GTW handbook. The overall correlation, dependently only on gas turbine output power, used in a lot of scientific studies is here actualized, calculating new split-power and new coefficients for Heavy Duty and Aeroderivative gas turbine. Therefore, a more complete and detailed correlation is developed, introducing additional parameters, such as thermodynamic efficiency, pressure ratio, exhaust temperature and exhaust mass flow rate, whose values are available on gas turbine datasheet. The new correlation here proposed reflects better real gas turbine configurations and costs.

What can we learn from the exclusion volume of fluctuations and precipitates?

ABSTRACT In the literature, the volume of a cluster (i.e. a fluctuation of the solid solution or a precipitate) is identified as the volume of a sample of the bulk precipitate phase containing the same number of solute atoms (i.e. of the same size). This approximation is suitable for macroscopic precipitates but is debatable for a rigorous description of microscopic clusters, especially during the nucleation and growth stages. To go beyond this simplification, this work focuses on the notion of ‘exclusion volume’, a volume which accounts for real cluster configurations in a given 3D lattice. The exclusion volume normalised by the cluster size is a complex function of the cluster size, which, like the cluster free energy, evolves during precipitation kinetics and converges toward an asymptote in the long-time limit. Furthermore, this asymptote exhibits a bifurcation which clearly separates fluctuations from precipitates, for a cluster size which is found equal to the minimum value of the critical size for nucleation. With the help of Atomistic Kinetic Monte Carlo (AKMC) simulations, it is shown that the evolution of cluster volume during precipitation can be accurately predicted.

Prediction of air permeability coefficient and water-vapor resistance of 3D textile layer

This study presents a computational model for investigation of the air permeability coefficient and water-vapor resistance coefficient through 3D textile layer. The effective values of the coefficients are highly dependent on the volumetric internal structure of the layer. The computational study of air and water vapor flow has been performed a microscale finite element model of the representative volume of the textile layer by taking into account the real configuration the yarns and filaments. The effective values of the coefficients were obtained by using taking average values of air and water vapor fluxes through the thickness of the representative volume. The steady state computational models in micro scale are based on Navier-Stokes and Brinkman partial differential equations. The simulations were performed in Comsol Multiphysics 5.3a software environment by using laminar flow (.spf) application mode. Numerical results for the air permeability of the samples were obtained, analyzed and validated by comparing against experimental data. Good agreement with experimental data has been achieved. Highlights COMSOL software was used to simulate air permeability and water-vapor resistance of 3D textile layer. The numerical model has demonstrated its efficiency comparing with experimental air permeability measurements.

Micromouse 3D simulator with dynamics capability: a Unity environment approach

The micromouse competition has been gaining prominence in the robotic atmosphere, due to the challenging and multidisciplinary characteristics provided by the teams’ duels, being a gateway for those who intend to deepen their studies in autonomous robotics. In this context, this paper presents a realistic micromouse simulator developed with Unity software, a widely game engine with dynamics and 3D development platform used. The developed simulator has hardware-in-the-loop capabilities, aims to be simple to use, it can be customizable, and designed to be as similar as possible to the real robot configurations. In this way, the proposed simulator requires few modifications to port the microcontroller code to a real robot. Therefore, the framework presented in this work allows the user to simulate the development of new algorithm strategies dedicated to competition and also hardware updates. The simulation supports several mazes, from previous competitions and has the possibility to add different mazes elaborated by the user. Thus, the features and functionality of the simulator can serve to accelerate the project’s development of the beginning and advanced competitors, using real models to reduce the gap between the mouse robot behavior in the simulation and the reality. The developed simulation environment is available to the community.

ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications

To train deep learning models for vision-based action recognition of elders’ daily activities, we need large-scale activity datasets acquired under various daily living environments and conditions. However, most public datasets used in human action recognition either differ from or have limited coverage of elders’ activities in many aspects, making it challenging to recognize elders’ daily activities well by only utilizing existing datasets. Recently, such limitations of available datasets have actively been compensated by generating synthetic data from realistic simulation environments and using those data to train deep learning models. In this paper, based on these ideas we develop ElderSim, an action simulation platform that can generate synthetic data on elders’ daily activities. For 55 kinds of frequent daily activities of the elders, ElderSim generates realistic motions of synthetic characters with various adjustable data-generating options and provides different output modalities including RGB videos, two- and three-dimensional skeleton trajectories. We then generate KIST SynADL, a large-scale synthetic dataset of elders’ activities of daily living, from ElderSim and use the data in addition to real datasets to train three state-of-the-art human action recognition models. From the experiments following several newly proposed scenarios that assume different real and synthetic dataset configurations for training, we observe a noticeable performance improvement by augmenting our synthetic data. We also offer guidance with insights for the effective utilization of synthetic data to help recognize elders’ daily activities.

FWS: Analyzing, maintaining and transcompiling firewalls

Firewalls are essential for managing and protecting computer networks. They permit specifying which packets are allowed to enter a network, and also how these packets are modified by IP address translation and port redirection. Configuring a firewall is notoriously hard, and one of the reasons is that it requires using low level, hard to interpret, configuration languages. Equally difficult are policy maintenance and refactoring, as well as porting a configuration from one firewall system to another. To address these issues we introduce a pipeline that assists system administrators in checking if: (i) the intended security policy is actually implemented by a configuration; (ii) two configurations are equivalent; (iii) updates have the desired effect on the firewall behavior; (iv) there are useless or redundant rules; additionally, an administrator can (v) transcompile a configuration into an equivalent one in a different language; and (vi) maintain a configuration using a generic, declarative language that can be compiled into different target languages. The pipeline is based on IFCL, an intermediate firewall language equipped with a formal semantics, and it is implemented in an open source tool called FWS. In particular, the first stage decompiles real firewall configurations for iptables, ipfw, pf and (a subset of) Cisco IOS into IFCL. The second one transforms an IFCL configuration into a logical predicate and uses the Z3 solver to synthesize an abstract specification that succinctly represents the firewall behavior. System administrators can use FWS to analyze the firewall by posing SQL-like queries, and update the configuration to meet the desired security requirements. Finally, the last stage allows for maintaining a configuration by acting directly on its abstract specification and then compiling it to the chosen target language. Tests on real firewall configurations show that FWS can be fruitfully used in real-world scenarios.

The hybrid method for the plate-finned tube evaporator design process

The plate-finned tube evaporator performance, in terms of heat transfer rate and refrigerant pressure drops, is influenced by several choices done during the design process to be carried out complying with different constraints. In this paper different refrigerant circuitry layout options together with other parameters variations were investigated with the purpose of supporting designers. Performance predictions were calculated using the hybrid method as well as appropriate Performance Evaluation Criteria (PEC) were adopted to select the best layout. The hybrid method has been here revised and improved aiming at modelling heat exchangers with an approach closer to real configurations that include complex circuit layouts. The method was chosen as its main advantage (high accuracy in the results with low computational costs) allowed to easily perform operating conditions modifications to be compared.

Духовный смысл войны и метаморфозы коллективной ответственности в социально-философской концепции И.А. Ильина

The article reveals the problem of collective responsibility in the works of the Russian philosopher I.A. Ilyin, shows the dynamics of the development of his ideas from early work to articles of the emigrant period. Responsibility is con­sidered by I.A. Ilyin as a key concept that ensures the interconnection of the past and the future, which is especially acute in a situation of war. The First World War was supposed to be a source of spiritual uplift for the Russian people, but the ensuing revolution led to the emergence of a new socio-historical situation. According to I.A. Ilyin, traditional patriotism is replaced by its new form, in which responsibility for preserving Russian society forces neutrality in the armed con­frontation between communist Russia and Nazi Germany. A key element of such a choice is moral justification, which forces us to abandon the idea of overthrow­ing the regime at the cost of the life of the people, but, at the same time, does not allow us to side with this regime. I.A. Ilyin notes the key mistakes of Nazi ideol­ogy that do not allow us to make a choice in its favor: sectarianism, right-wing totalitarianism, party monopoly, nationalism, nationalization of the economy, idolatrous Caesarism. As a result, the Russian thinker considers authoritarian regimes based on traditional social institutions and preserving the primacy of morality over rationality to be the most optimal form of political structure. The article justifies that the ideas of I.A. Ilyin demonstrate the complexity and ambiguity of understanding patriotism in the context of the transformation of collective subjects of responsibility, when there is an inconsistency between the images of historical memory and the real configuration of the political and social space.

Active fault-tolerant control of rotation angle sensor in steer-by-wire system based on multi-objective constraint fault estimator

Purpose Steer-by-wire (SBW) system mainly relies on sensors, controllers and motors to replace the traditionally mechanical transmission mechanism to realize steering functions. However, the sensors in the SBW system are particularly vulnerable to external influences, which can cause systemic faults, leading to poor steering performance and even system instability. Therefore, this paper aims to adopt a fault-tolerant control method to solve the safety problem of the SBW system caused by sensors failure. Design/methodology/approach This paper proposes an active fault-tolerant control framework to deal with sensors failure in the SBW system by hierarchically introducing fault observer, fault estimator, fault reconstructor. Firstly, the fault observer is used to obtain the observation output of the SBW system and then obtain the residual between the observation output and the SBW system output. And then judge whether the SBW system fails according to the residual. Secondly, dependent on the residual obtained by the fault observer, a fault estimator is designed using bounded real lemma and regional pole configuration to estimate the amplitude and time-varying characteristics of the faulty sensor. Eventually, a fault reconstructor is designed based on the estimation value of sensors fault obtained by the fault estimator and SBW system output to tolerate the faulty sensor. Findings The numerical analysis shows that the fault observer can be rapidly activated to detect the fault while the sensors fault occurs. Moreover, the estimation accuracy of the fault estimator can reach to 98%, and the fault reconstructor can make the faulty SBW system to retain the steering characteristics, comparing to those of the fault-free SBW system. In addition, it was verified for the feasibility and effectiveness of the proposed control framework. Research limitations/implications As the SBW fault diagnosis and fault-tolerant control in this paper only carry out numerical simulation research on sensors faults in matrix and laboratory/Simulink, the subsequent hardware in the loop test is needed for further verification. Originality/value Aiming at the SBW system with parameter perturbation and sensors failure, this paper proposes an active fault-tolerant control framework, which integrates fault observer, fault estimator and fault reconstructor so that the steering performance of SBW system with sensors faults is basically consistent with that of the fault-free SBW system.

Machine learning phases and criticalities without using real data for training

We study the phase transitions of three-dimensional (3D) classical O(3) model and the two-dimensional (2D) classical XY model, as well as both the quantum phase transitions of 2D and 3D dimerized spin-1/2 antiferromagnets, using the techniques of supervised neural network (NN). Moreover, unlike the conventional approaches commonly used in the literature, the training sets employed in our investigation are neither the theoretical nor the real configurations of the considered systems. Remarkably, with such an unconventional set up of the training stage in conjunction with semi-experimental finite-size scaling formulas, the associated critical points determined by the NN method agree well with the established results in the literature. The outcomes obtained here imply that certain unconventional training strategies, like the one used in this study, are not only cost-effective in computation, but are also applicable for a wild range of physical systems.

A full three‐dimensional model for the estimation of the natural frequencies of an offshore wind turbine in sand

AbstractThe design of an offshore wind turbine (OWT) founded on a monopile foundation is principally based on dimensioning criteria related to its fundamental frequencies. These frequencies must remain outside the excitation frequencies to avoid resonance. For the calculation of the OWT natural frequencies, several studies exist, but few of them simultaneously consider both the real geometrical configuration of the OWT superstructure (tower, blades, and transition piece) and the three‐dimensional (3D) soil domain and its interaction with the monopile foundation. This paper aims at filling this gap. A rigorous 3D finite element method‐based model of a 10 MW DTU OWT installed in sand is developed. The aim is to perform a structural modal analysis of the wind turbine in parked condition. The obtained natural frequencies are compared with those corresponding to other simplified models available in literature for the foundation and the superstructure in the scope of giving an insight about how poorly the existing simplified models can predict the OWT natural frequencies. Finally, a parametric analysis is performed to study the effect of the water depth, the monopile dimensions (diameter, thickness, and embedded depth), the transition piece height, and the sandy soil relative density on the system natural frequencies.

Maximizing social welfare in a competitive diffusion model

Influence maximization (IM) has garnered a lot of attention in the literature owing to applications such as viral marketing and infection containment. It aims to select a small number of seed users to adopt an item such that adoption propagates to a large number of users in the network. Competitive IM focuses on the propagation of competing items in the network. Existing works on competitive IM have several limitations. (1) They fail to incorporate economic incentives in users' decision making in item adoptions. (2) Majority of the works aim to maximize the adoption of one particular item, and ignore the collective role that different items play. (3) They focus mostly on one aspect of competition - pure competition. To address these concerns we study competitive IM under a utility-driven propagation model called UIC, and study social welfare maximization. The problem in general is not only NP-hard but also NP-hard to approximate within any constant factor. We, therefore, devise instant dependent efficient approximation algorithms for the general case as well as a (1 - 1/ e - ∈ )-approximation algorithm for a restricted setting. Our algorithms outperform different baselines on competitive IM, both in terms of solution quality and running time on large real networks under both synthetic and real utility configurations.

Reconfigurable Web-Interface Remote Lab for Instrumentation and Electronic Learning

Lab sessions in engineering education are designed to reinforce theoretical concepts. However, usually there are not enough time to reinforce all of them. Remote and virtual lab give students more time for reinforce those concepts. In particular, with remote labs, this can be done interacting with real lab equipment and specific configurations. This work proposes a flexible configuration for Remote Lab Sessions, based on some of 2019 most popular programming languages (Python and JavaScript). This configuration needed minimal network privileges, it is easily to scale and reconfigure. Its structure is based on a unique Reception-Server (which hosts User database, and Time Shift Manager, it is accessible from The Internet, and connect Users with Instruments-Servers) and some Instrument-Servers (which manage hardware connection and host experiences). Users always connect to Reception-Server, and book a shift for an experience. During the time range associate to that shift, User is internally forwarded to Instrument-Server associated with selected experience, so User is still connected to Reception-Serer. In this way, Reception-Server acts as a firewall, protecting Instrument-Servers, which never are open to The Internet. A triple evaluation system is implemented, User session logging and auto-evaluation (objectives accomplished) a knowledge test and an interaction survey. An experience is implemented, controlling a DC source using Standard Commands for Programmable Instruments.

(Invited) Benchmarking Carbon-Supported Pt-Based Oxygen Reduction Reaction Electrocatalysts for PEMFC Cathodes

The present performance of state-of-the-art proton exchange membrane fuel cells (PEMFC) enable their commercialization, as demonstrated by the recent release of fuel-cell powered vehicles (forklifts by Plug Power, FCEV Miraï by Toyota, etc.). Now, all PEMFC manufacturers need to reduce the PEMFC systems initial cost and to enhance their durability and reliability in operation to reach the market requirements and industrial sustainability. To this goal, one must develop highly-efficient oxygen reduction reaction (ORR) electrocatalysts, which was claimed to be obtained by numerous groups in a recent past [1-6]. Unfortunately, the scientific community still struggles to obtain the best performance of these materials in operating PEFMCs: their practical performance in membrane electrode assembly (MEA) do not approach those expected from an analytical approach performed using the rotating disk electrode setup, RDE (the most widely-used setup to assess a material’s ORR performance).There are several reasons that may explain why RDE data are not relevant to account for MEA data. Firstly, in RDE, the O2 reactant is fed as gas dissolved in the electrolyte (slow diffusivity and solubility), hence the mass-transfer rate and related limiting current density are ca. 3 orders of magnitude lower than in real PEMFC conditions. Secondly, the activity data is only extracted at high potential values in RDE (E > 0.85 V vs RHE), although PEMFC optimal performance is reached in the 0.6 – 0.8 V vs RHE cathode potential range. Thirdly, the proton conduction can be limiting in the thin layer of ionomer covering the electrocatalyst nanoparticles in MEA, which could limit their operation, especially at the high current densities at stake in MEA. In essence, one is not sure that the electrocatalysts are used in optimized conditions in MEA, as emphasized mass-transport of reactants (both H+ and O2) to the catalytic sites is not granted for present ionomers and MEA structure [7, 8]. Recent results obtained in newly-developed electrochemical characterization setups like the floating electrode (FE) [9], the gas-diffusion electrode (GDE) [10] or differential cell (DC), could enable to reach much higher ORR current densities at the lab scale and therefore better match MEA data, a prerequisite for relevant benchmarking.In the present contribution, these setups will be used to characterize three state-of-the-art ORR electrocatalysts (50 wt% Pt/Vulcan XC72, 50 wt% Pt3Co/Vulcan XC72 and 30 wt% Pt/graphitized carbon black), and comparison will be made with large single-cell PEMFC data in automotive conditions. We will show whether the “RDE promises” of alloyed electrocatalysts (measured in RDE configuration) do maintain in FE, GDE and DC, and whether the “advanced electrocatalysts” still exhibit their plain potential in real PEMFC catalytic layer configuration.

Effect of the gas injection angle and configuration in the efficiency of gas lift

In oil wells using gas lift as a method of artificial lift, the gas is normally injected inside the tubing at a downward direction, i.e., in countercurrent flow relative to the fluids coming from the reservoir. This creates turbulence in the flow, causing pressure drop for the gas to change direction and to flow upward along with the produced fluid. The optimization of this geometry, by changing the gas injection angle, for instance, may introduce some gain. In this paper, we present theoretical analyzes and computer simulation showing that, for high gas injection flow rates and/or small jet diameters, it is possible to obtain a gain when reversing the direction of the gas injection. Although it is intuitive that an upward injection can improve the flow, experiments are needed to give confidence to this proposal. However, there is very few studies in the literature addressing this issue. To improve the knowledge of subject, this study shows experiments performed using an experimental well flowing oil and natural gas. Such an experiment, at real scale configurations and fluids is unique. The usual configuration, injecting downward, was compared with two alternatives, injecting the gas jet upward and injecting in an annular pattern. This article describes and discusses the tests and the results obtained. Although the tests have not been performed with the ideal conditions to maximize the gain, the results were consistent and conclusive. A slight local gain was observed due to the gas angle change, consistent with the previsions of a simple theoretical model. The estimated gains can reach 2 bar and are obtained at no additional cost by simply inverting the gas jet direction, but it is more effective for wells with high gas injection flow rate. Since gas lift is applied to a large number of wells, even a modest gain can be significant in the overall context. Based on the results, it is speculated that there is probably an optimum way to inject gas by taking advantage of the jet inversion and of the reduction on slippage between gas and liquid.

New Cadanav Methodology for Rock Fall Hazard Zoning Based on 3D Trajectory Modelling

Most rock fall hazard zoning methodologies are currently based on trajectory modelling, usually performed along 2D slope profiles. For many topographic configurations, this approach cannot provide a realistic description of the way rock fall trajectories and, ultimately, hazard are spatially distributed all over a slope. This paper presents a new methodology for rock fall hazard zoning, directly applicable to 3D topographies, starting from 3D trajectory simulation results. The procedure is an extension of the Cadanav methodology introduced for hazard zoning along 2D slope profiles. As such, it is fully quantitative and attempts at reducing as much as possible uncertainties and subjective elements affecting current methods for rock fall hazard analysis and zoning. It is also among the first to introduce a “fully-coupled” rock fall intensity-frequency approach. Hazard is estimated by means of “hazard curves”, described at each point of the slope by rock fall intensity-return period couples. These curves may be superimposed on any intensity-return period diagram prescribed in national or regional land use planning regulations, in order to determine which hazardous condition prevails at each point of the slope. The application of the new Cadanav methodology is illustrated for both a theoretical case of simple topography underlying a linear cliff and a real configuration involving a complex topography, characterised by strong three-dimensional features affecting the paths of the blocks. For all topographic models, results obtained for several scenarios involving either localised or diffuse source areas proved that the methodology performs extremely well, providing objective and reproducible results based on a rigorous combination of rock fall energy and return period. Additional tests and real case studies are currently under investigation, for strengthening even further the validation of the approach and extend its applicability to even more complex rock fall scenarios.

Fractional quantum Hall physics and higher-order momentum correlations in a few spinful fermionic contact-interacting ultracold atoms in rotating traps

The fractional quantum Hall effect (FQHE) is theoretically investigated, with numerical and algebraic approaches, in assemblies of a few spinful ultracold neutral fermionic atoms, interacting via repulsive contact potentials and confined in a single rapidly rotating two-dimensional harmonic trap. Going beyond the commonly used second-order correlations in the real configuration space, the methodology in this paper will assist the analysis of experimental observations by providing benchmark results for $N$-body spin-unresolved, as well as spin-resolved, momentum correlations measurable in time-of-flight experiments with individual particle detection. Our analysis shows that the few-body lowest-Landau-level (LLL) states with good magic angular momenta exhibit inherent ordered quantum structures in the $N$-body correlations, similar to those associated with rotating Wigner molecules (WMs), familiar from the field of semiconductor quantum dots under high magnetic fields. The application of a small perturbing stirring potential induces, at the ensuing avoided crossings, formation of symmetry broken states exhibiting ordered polygonal-ring structures, explicitly manifest in the single-particle density profile of the trapped particles. Away from the crossings, an LLL state obtained from exact diagonalization of the microscopic Hamiltonian, found to be well-described by a (1,1,1) Halperin two-component variational wavefunction, represents also a spinful rotating WM. Analysis of the calculated LLL wavefunction enables a two-dimensional generalization of the Girardeau one-dimensional 'fermionization' scheme, originally invoked for mapping of bosonic-type wave functions to those of spinless fermions.

Enhancement of the electrochemical reduction of CO2 to methanol and suppression of H2 evolution over CuO nanowires

A highly efficient copper-catalyst (noble-metal free) was developed for the electrochemical reduction of CO2 (ERCO2) to methanol. Due to the nanowire structure of the catalyst, a remarkable ERCO2 selectivity was achieved, while the competing H2 evolution reaction (HER) was significantly suppressed for the overall range of potential tested. The developed copper-catalyst (CuO NWs) outperforms the single metal Cu-catalysts in aqueous environment. Under atmospheric conditions, methanol was produced at an overpotential of 410 mV with a faradaic efficiency (FE) of 66%, and 1.27 × 10−4 mol m−2 s−1 of production yield; which represents a 6.7% improvement over the previously reported value of 1.19 × 10−4 mol m−2 s−1. Interestingly, when the developed CuO NWs was used as a gas diffusion electrode (GDE) in a filter-press cell (more real industrial configuration), methanol remained as the major ERCO2 product with the same FE (66%).