Systematic analysis of the impact of slurry coating on manufacture of Li-ion battery electrodes via explainable machine learning

The manufacturing process strongly affects the electrochemical properties and performance of lithium-ion batteries. In particular, the flow of electrode slurry during the coating process is key to the final electrode properties and hence the characteristics of lithium-ion cells, however it is given little consideration. In this paper the effect of slurry structure is studied through the physical and rheological properties and their impact on the final electrode characteristics, for a graphite anode. As quantifying the impact of the large number of interconnected control variables on the electrode is a challenging task via traditional trial-and-error approaches, an explainable machine learning methodology as well as a systematic statistical analysis method is proposed for comprehensive assessments. The analysis is based upon an experimental dataset in lab-scale involving 9 main factors and 6 interest variables which cover practical range of variables through various combinations. While the predictability of response variables is evaluated via linear and nonlinear models, complementary techniques are utilised for variables importance, contribution, and first and second order effects to increase the model transparency. While coating gap is identified as the most influential factor for all considered responses, other subtle relationships are also extracted, highlighting that dimensionless numbers can serve as strong predictors for models. The impact of slurry viscosity and surface tension on electrode thickness, coat weight and porosity are also extracted, demonstrating their importance for electrode quality. These variables have been rarely considered in previous works, as the relationships are difficult to extract by trial and error due to interdependencies. Here we demonstrate how model-based analysis can overcome these difficulties and pave the way towards an optimised electrode manufacturing process of next generation Lithium-ion batteries

MAC-Oriented Programmable Terahertz PHY via Graphene-based Yagi-Uda Antennas

Graphene is enabling a plethora of applications in a wide range of fields due to its unique electrical, mechanical, and optical properties. In the realm of wireless communications, graphene shows great promise for the implementation of miniaturized and tunable antennas in the terahertz band. These unique advantages open the door to new reconfigurable antenna structures which, in turn, enable novel communication protocols at different levels of the stack. This paper explores both aspects by, first, presenting a terahertz Yagi-Uda-like antenna concept that achieves reconfiguration both in frequency and beam direction simultaneously. Then, a programmable antenna controller design is proposed to expose the reconfigurability to the PHY and MAC layers, and several examples of its applicability are given. The performance and cost of the proposed scheme is evaluated through full-wave simulations and comparative analysis, demonstrating reconfigurability at nanosecond granularity with overheads below 0.02 mm$^{2}$ and 0.2 mW.Comment: Accepted for presentation in IEEE WCNC '1

Indicators Affecting the Urban Resilience with a Scenario Approach in Tehran Metropolis

Urban resilience refers to the capacity of an urban system to fully recover from unforeseen calamities. This study aims to assess the physical resilience indicators used to measure urban resilience in Tehran, the political and economic capital of Iran, and to pinpoint the most significant direct and indirect influences on urban resilience. The research process divided into two parts. The environmental scanning approach (reviewing papers and published sources, interviewing specialists, and monitoring conferences) and the literature review were employed in the first part to compile a database of the key information on the elements impacting physical resilience. The most significant factors impacting physical resilience over the next ten years were requested to be identified by specialists and intellectuals in the second part. Finally, the MicMac program was used to analyze the data after 29 variables were specified in Delphi. In light of the trace-analysis-dependence diagram, which depicts the instability of the influential factors and the persistence of their impact on other variables, the results demonstrate that Tehran’s physical resilience is in an unstable condition. According to the results, the factors that have the maximum impact on other variables are granularity drivers, emergency evacuation capacity, rescue and security spaces (emergency, fire station, and police station), impermeability, rate of the amendment and retrofitting measures in the buildings of each zone, building age, and the compatibility of land uses. The variables that are most susceptible to change from other variables include the distribution status of dangerous land uses, the quality of the buildings, the rate of historically vulnerable buildings, the vulnerability of internal and external roads, the rate of improvements and retrofitting measures in buildings in each zone, as well as historically vulnerable historical buildings

Modelling of friction stir welding of 304 stainless steel

A 3-D Eulerian steady-state CFD model has been developed to simulate the Friction Stir Welding (FSW) of 6mm plate 304 stainless steel (304SS). The Polycrystalline BoroNitride- Tungsten Rhenium (PCBN-WRe) hybrid tool was modelled with the workpiece in a fully sticking condition. The viscosity of stainless steel was calculated from the flow stress equation taken from a previous study of hot working carried out in a range of temperatures between 800oC-1200 oC and strain rates 0.001 s-1 to 5 s-1. The model predicted the temperature distribution in the Stirred Zone (SZ) for three welding cases including low, intermediate and high rotational speed/traverse speeds. The model also predicts that localised melting may occur if the tool rotational speed exceeds 400RPM. Finally, the model suggested a larger probe (12mm diameter at the shoulder base and 5.8mm length) with a stationary shoulder would prevent the localised melting and allow an increase in welding speeds without the associated introduction of stagnant zone related weld defects

An advanced numerical model of friction stir welding of DH36 steel

A numerical model of Friction Stir Welding (FSW) of DH36 steel plate (6mm thickness) has been developed using a CFD technique. Two welding speed conditions were used, a low welding speed of 200 RPM - 100mm/min, and a high welding speed of 550RPM- 400 mm/min. The heat generation, material flow and strain rate were calculated based on plastic deformation and frictional contact between the tool and workpiece. A CFD-based model has been produced to represent the asymmetry in temperature distribution between the advancing and retreating side, the material flow and the strain rate. The geometry of the model includes the tool plunged into the plate. The cooling system was also included in the simulation by calculating the heat flux lost for each part of the tool. The heat generated by viscous dissipation away from the tool was also taken into account. The total heat generated was divided into the individual tool parts (shoulder, probe side and probe end) and was found to be in good agreement with the experimental results for the areas affected by these parts. The maximum temperature obtained for the slow welding speed was 1012oC and for the high welding speed was 1250oC. Experimental metallographic examination has also been carried out on DH36 FSW steel plates to validate the CFD model. SEM analysis showed the formation of a fine microstructure of bainite, acicular ferrite and ferrite/cementite aggregate in the welded zone as compared to the ferrite/pearlite morphology in the base metal. It is found from the CFD and experimental results that the high speed welding conditions can produce defects such as wormholes and cracks in the welds associated with the probe side and probe end due to the lack of material flow especially on the advancing side. Tensile and fatigue testing were carried out for both slow and high welding speed samples, which broke outside the welded region in the tensile test, however, slow welding speed samples show more resistance to fatigue test and survived 644128 cycles, the high speed welding samples failed after 111,736 cycles under the same load

Association of chemosensory dysfunction and COVID-19 in patients presenting with influenza-like symptoms.

BackgroundRapid spread of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and concern for viral transmission by ambulatory patients with minimal to no symptoms underline the importance of identifying early or subclinical symptoms of coronavirus disease 2019 (COVID-19) infection. Two such candidate symptoms include anecdotally reported loss of smell and taste. Understanding the timing and association of smell/taste loss in COVID-19 may help facilitate screening and early isolation of cases.MethodsA single-institution, cross-sectional study evaluating patient-reported symptoms with a focus on smell and taste was conducted using an internet-based platform on adult subjects who underwent testing for COVID-19. Logistic regression was employed to identify symptoms associated with COVID-19 positivity.ResultsA total of 1480 patients with influenza-like symptoms underwent COVID-19 testing between March 3, 2020, and March 29, 2020. Our study captured 59 of 102 (58%) COVID-19-positive patients and 203 of 1378 (15%) COVID-19-negative patients. Smell and taste loss were reported in 68% (40/59) and 71% (42/59) of COVID-19-positive subjects, respectively, compared to 16% (33/203) and 17% (35/203) of COVID-19-negative patients (p < 0.001). Smell and taste impairment were independently and strongly associated with COVID-19 positivity (anosmia: adjusted odds ratio [aOR] 10.9; 95% CI, 5.08-23.5; ageusia: aOR 10.2; 95% CI, 4.74-22.1), whereas sore throat was associated with COVID-19 negativity (aOR 0.23; 95% CI, 0.11-0.50). Of patients who reported COVID-19-associated loss of smell, 74% (28/38) reported resolution of anosmia with clinical resolution of illness.ConclusionIn ambulatory individuals with influenza-like symptoms, chemosensory dysfunction was strongly associated with COVID-19 infection and should be considered when screening symptoms. Most will recover chemosensory function within weeks, paralleling resolution of other disease-related symptoms

Chiral molecule candidates for trapped ion spectroscopy by ab-initio calculations: from state preparation to parity violation

Parity non-conservation (PNC) due to the weak interaction is predicted to give rise to enantiomer dependent vibrational constants in chiral molecules, but the phenomenon has so far eluded experimental observation. The enhanced sensitivity of molecules to physics beyond the Standard Model (BSM), has led to substantial advances in molecular precision spectroscopy, and these may be applied to PNC searches as well. Specifically, trapped molecular ion experiments leverage the universality of trapping charged particles to optimize the molecular ion species studied toward BSM searches, but in searches for PNC only a few chiral molecular ion candidates have been proposed so far. Importantly, viable candidates need to be internally cold and their internal state populations should be detectable with high quantum efficiency. To this end, we focus on molecular ions that can be created by near threshold resonant two-photon ionization and detected via state-selective photo-dissociation. Such candidates need to be stable in both charged and neutral chiral versions to be amenable to these methods. Here, we present a collection of suitable chiral molecular ion candidates we have found, including CHDBrI$^+$ and CHCaBrI$^+$, that fulfill these conditions according to our \textit{ab-initio} calculations. We find that organo-metallic species have a low ionization energy as neutrals and relatively high dissociation thresholds. Finally, we compute the magnitude of the PNC values for vibrational transitions for some of these candidates. An experimental demonstration of state preparation and readout for these candidates will be an important milestone toward measuring PNC in chiral molecules for the first time.Comment: 14 pages, 3 figures and supplementary informatio

Terahertz Dielectric Resonator Antenna Coupled to Graphene Plasmonic Dipole

This paper presents an efficient approach for exciting a dielectric resonator antenna (DRA) in the terahertz frequencies by means of a graphene plasmonic dipole. Design and analysis are performed in two steps. First, the propagation properties of hybrid plasmonic onedimensional and two-dimensional structures are obtained by using transfer matrix theory and the finite-element method. The coupling amount between the plasmonic graphene mode and the dielectric wave mode is explored based on different parameters. These results, together with DRA and plasmonic antenna theory, are then used to design a DRA antenna that supports the $TE_{y}^{112}$ mode at 2.4 THz and achieves a gain (IEEE) of up to 7 dBi and a radiation efficiency of up 70%. This gain is 6.5 dB higher than that of the graphene dipole alone and achieved with a moderate area overhead, demonstrating the value of the proposed structure.Comment: Accepted for presentation at EuCAP 201

GronOR:Massively parallel and GPU-accelerated non-orthogonal configuration interaction for large molecular systems

GronOR is a program package for non-orthogonal configuration interaction calculations for an electronic wave function built in terms of anti-symmetrized products of multi-configuration molecular fragment wave functions. The two-electron integrals that have to be processed may be expressed in terms of atomic orbitals or in terms of an orbital basis determined from the molecular orbitals of the fragments. The code has been specifically designed for execution on distributed memory massively parallel and Graphics Processing Unit (GPU)-accelerated computer architectures, using an MPI+OpenACC/OpenMP programming approach. The task-based execution model used in the implementation allows for linear scaling with the number of nodes on the largest pre-exascale architectures available, provides hardware fault resiliency, and enables effective execution on systems with distinct central processing unit-only and GPU-accelerated partitions. The code interfaces with existing multi-configuration electronic structure codes that provide optimized molecular fragment orbitals, configuration interaction coefficients, and the required integrals. Algorithm and implementation details, parallel and accelerated performance benchmarks, and an analysis of the sensitivity of the accuracy of results and computational performance to thresholds used in the calculations are presented