Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

First-Principles Study of the Charge Transport Mechanisms in Lithium Superoxide

Lithium–air batteries have attracted intense interest due to their high energy density, yet their practical applications are still severely hindered by the low conductivity of lithium peroxide (Li₂O₂). Here, we perform first-principles calculations on the recently synthesized lithium superoxide (LiO₂) which has the potential to replace its peroxide counterpart as the discharge product. Using HSE hybrid functional, we predict an electrical insulating behavior for LiO₂. Excess electrons and holes will be localized on the oxygen dimer, thus forming small polarons that can diffuse by hopping between lattice sites. With the calculated concentrations and mobilities of the intrinsic charge carriers, we show that the charge transportation in LiO₂ is governed by the migration of hole polarons and positively charged oxygen dimer vacancies. The electronic conductivity associated with polaron hopping (3 × 10^–12 S cm^–1) exceeds that of Li₂O₂ by 8 orders of magnitude, while a comparable value (4 × 10^–12 S cm^–1) is found for the ionic conductivity contributed by superoxide ions. Our calculations provide a detailed understanding of the role of small polarons in describing the charge transport properties of LiO₂

Generative models for inverse design of inorganic solid materials

Overwhelming evidence has been accumulating that materials informatics can provide a novel solution for materials discovery. While the conventional approach to innovation relies mainly on experimentation, the generative models stemming from the field of machine learning can realize the long-held dream of inverse design, where properties are mapped to the chemical structures. In this review, we introduce the general aspects of inverse materials design and provide a brief overview of two generative models, variational autoencoder and generative adversarial network, which can be utilized to generate and optimize inorganic solid materials according to their properties. Reversible representation schemes for generative models are compared between molecular and crystalline structures, and challenges in regard to the latter are also discussed. Finally, we summarize the recent application of generative models in the exploration of chemical space with compositional and configurational degrees of freedom, and potential future directions are speculatively outlined

A Class of Auxiliary Passivators for Polymer Dielectrics

Abstract High‐electrical‐strength polymer dielectrics are essential for advanced devices with high power and/or high integration densities and film capacitors with high energy‐storage densities. Key factors affecting the polymer dielectric electrical strength are deep‐level defect states, which lead to electron and hole accumulation. Numerous deep‐level defect states lead to charge accumulation in the polymer dielectric during operation, contributing to local electric field distortion and resulting in flashover or breakdown. In this work, first‐principles calculations and experiments reveal that VH (i.e., H vacancies) in the polymer dielectric molecular chain can create defect states deep in the bandgap. RCl (R = Li, Na, K) can be used for passivating the deep‐level polymer dielectric defect states. In addition, the passivation mechanisms are analyzed. The RCl cations can passivate deep‐level defect states into shallow‐level acceptor defect states because the RCl dipole moment regulates the deep‐level defect state energy. The RCl anions can passivate deep‐level defect states into shallow‐level donor defect states by forming a stable covalent bond between carbon and lone‐pair electrons. This work supports the design of high‐electrical‐strength polymer dielectrics

First-Principle Study of Li-Ion Storage of Functionalized Ti₂C Monolayer with Vacancies

Two-dimensional transition metal carbides are notable as promising anode materials for Li-ion batteries (LIBs). Using first-principle calculations, we investigate the effect of vacancies on the Li adsorption and diffusion on Ti₂C and Ti₂CT₂ (where T denotes surface terminations, F or OH) monolayers. Interestingly, we find that the carbon vacancies (V_C) tend to enhance the adsorption of Li in Ti₂C monolayer, whereas the titanium vacancies (V_Ti) play a similar role in Ti₂CT₂ when functional groups present. The presence of vacancies further leads to a change in the diffusion behavior of Li atoms. In this context, we propose an idea to mitigate the adverse effects on Li diffusion performance by regulating the functional groups. In the presence of V_C, the surface of Ti₂C monolayer is suggested to be modified with OH– groups due to its relatively low diffusion barrier in the range of 0.025–0.037 eV when Li diffuses around V_C, whereas in the presence of V_Ti, the surface is suggested to remove the functional groups, resulting in a decrease of energy barrier by about 1 eV when Li atom diffuses around V_Ti. The present study may provide a guideline to improve the Li-ion storage performance of Ti₂C monolayers as electrode materials in LIBs, with atomic vacancies being taken into consideration

A contact-electro-catalysis process for producing reactive oxygen species by ball milling of triboelectric materials

Abstract Ball milling is a representative mechanochemical strategy that uses the mechanical agitation-induced effects, defects, or extreme conditions to activate substrates. Here, we demonstrate that ball grinding could bring about contact-electro-catalysis (CEC) by using inert and conventional triboelectric materials. Exemplified by a liquid-assisted-grinding setup involving polytetrafluoroethylene (PTFE), reactive oxygen species (ROS) are produced, despite PTFE being generally considered as catalytically inert. The formation of ROS occurs with various polymers, such as polydimethylsiloxane (PDMS) and polypropylene (PP), and the amount of generated ROS aligns well with the polymers’ contact-electrification abilities. It is suggested that mechanical collision not only maximizes the overlap in electron wave functions across the interface, but also excites phonons that provide the energy for electron transition. We expect the utilization of triboelectric materials and their derived CEC could lead to a field of ball milling-assisted mechanochemistry using any universal triboelectric materials under mild conditions

Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts

Copper-based electrocatalysts, which hold great promise in selectively reducing CO2 into multicarbon products, have attracted a lot of recent interest, both experimentally and theoretically. While many studies have suggested a strong dependence of catalytic selectivity on the concentration of the *CO reaction intermediate on Cu surface, it remains challenging for a direct experimental probe of the CO coverage. This necessitates a reliable computational method that can accurately establish the theoretical coverage-dependent phase diagram of CO adsorbates on the catalyst. Here we propose a scheme composed of density functional theory (DFT) calculations, machine-learning force fields (MLFF) and graph neural networks (GNN) as a solution. This method enables a fast screening of 7 million adsorption configurations based on a small set of DFT data, with a balance between accuracy and efficiency tuned by the combinatorial use of MLFF and GNN models. We have investigated 8 different Cu facets, and discovered that the high-index facets such as (310), (210) and (322) exhibit a much higher CO coverage than the low-index counterparts such as (111), leading to an increased opportunity for C-C coupling for the former. Our results can provide a new perspective for the understanding of the fundamental role of CO coverage on Cu surface for electrochemical CO2 reduction

Identifying a competency improvement strategy for infection prevention and control professionals: A rapid systematic review and cluster analysis

Abstract Remarkable progress has been made in infection prevention and control (IPC) in many countries, but some gaps emerged in the context of the coronavirus disease 2019 (COVID‐19) pandemic. Core capabilities such as standard clinical precautions and tracing the source of infection were the focus of IPC in medical institutions during the pandemic. Therefore, the core competences of IPC professionals during the pandemic, and how these contributed to successful prevention and control of the epidemic, should be studied. To investigate, using a systematic review and cluster analysis, fundamental improvements in the competences of infection control and prevention professionals that may be emphasized in light of the COVID‐19 pandemic. We searched the PubMed, Embase, Cochrane Library, Web of Science, CNKI, WanFang Data, and CBM databases for original articles exploring core competencies of IPC professionals during the COVID‐19 pandemic (from January 1, 2020 to February 7, 2023). Weiciyun software was used for data extraction and the Donohue formula was followed to distinguish high‐frequency technical terms. Cluster analysis was performed using the within‐group linkage method and squared Euclidean distance as the metric to determine the priority competencies for development. We identified 46 studies with 29 high‐frequency technical terms. The most common term was “infection prevention and control training” (184 times, 17.3%), followed by “hand hygiene” (172 times, 16.2%). “Infection prevention and control in clinical practice” was the most‐reported core competency (367 times, 34.5%), followed by “microbiology and surveillance” (292 times, 27.5%). Cluster analysis showed two key areas of competence: Category 1 (program management and leadership, patient safety and occupational health, education and microbiology and surveillance) and Category 2 (IPC in clinical practice). During the COVID‐19 pandemic, IPC program management and leadership, microbiology and surveillance, education, patient safety, and occupational health were the most important focus of development and should be given due consideration by IPC professionals