Device Configuration Research Articles

Functionalized nickel oxide as a hole transport layer for organic solar cells with simultaneous enhancement of efficiency and stability

2PACz-modified NiOx thin films successfully replace PEDOT:PSS as hole transport layers, and achieve a high PCE of 16.7% in the PM6:Y6-based organic solar cells with simultaneous enhancement of efficiency, stability and reproducibility.

Full-F turbulent simulation in a linear plasma device using a gyro-moment approach

Simulations of plasma turbulence in a linear plasma device configuration are presented. These simulations are based on a simplified version of the gyrokinetic (GK) model proposed by Frei et al. [J. Plasma Phys. 86, 905860205 (2020)], where the full-F distribution function is expanded on a velocity-space polynomial basis allowing us to reduce its evolution to the solution of an arbitrary number of fluid-like equations for the expansion coefficients, denoted as the gyro-moments (GM). By focusing on the electrostatic and neglecting finite Larmor radius effects, a full-F GM hierarchy equation is derived to evolve the ion dynamics, which includes a nonlinear Dougherty collision operator, localized sources, and Bohm sheath boundary conditions. An electron fluid Braginskii model is used to evolve the electron dynamics, coupled to the full-F ion GM hierarchy equation via a vorticity equation where the Boussinesq approximation is used. A set of full-F turbulent simulations are then performed using the parameters of the LArge Plasma Device (LAPD) experiments with different numbers of ion GMs and different values of collisionality. The ion distribution function is analyzed illustrating the convergence properties of the GM approach. In particular, we show that higher-order GMs are damped by collisions in the high-collisional regime relevant to LAPD experiments. The GM results are then compared with those from two-fluid Braginskii simulations, finding qualitative agreement in the time-averaged profiles and statistical turbulent properties.

Architecture of the system for vulnerabilities detection and prediction in information systems based on artificial intelligence methods

Network security is one of the most active research directions in the field of information security. This direction includes many approaches, one of which is the construction of attack graphs. When building attack graphs, each device in the network is a node of the graph, while the ability to move across the graph is defined by a network policy as well as by the intruder’s possibility to compromise the corresponding devices. In turn, the possibility of compromising the device is determined by the presence of vulnerabilities in them. The exploitation of vulnerabilities leads to the impact on the attacked system and/or the obtaining of user or admin access rights by the intruder. At the same time, open database data is used to analyze if devices are vulnerable. The problem is that data on many devices is not described in open databases, while the information in such databases may contain errors, be inconsistent and incomplete. The solution to this issue lies in the use of artificial intelligence methods to detect and predict the vulnerabilities of information systems. This paper presents the original architecture of the system that solves this task. The key features of the proposed solution are the use of artificial intelligence methods for predicting unknown results of vulnerability metrics based on known ones, as well as for predicting vulnerability categories for not known as vulnerable devices configurations based on their configuration similarity with vulnerable devices.

Heterointerface engineering of layered double hydroxide/MAPbBr3 heterostructures enabling tunable synapse behaviors in a two-terminal optoelectronic device.

Solution-processable semiconductor heterostructures enable scalable fabrication of high performance electronic and optoelectronic devices with tunable functions via heterointerface control. In particular, artificial optical synapses require interface manipulation for nonlinear signal processing. However, the limited combinations of materials for heterostructure construction have restricted the tunability of synaptic behaviors with simple device configurations. Herein, MAPbBr3 nanocrystals were hybridized with MgAl layered double hydroxide (LDH) nanoplates through a room temperature self-assembly process. The formation of such heterostructures, which exhibited an epitaxial relationship, enabled effective hole transfer from MAPbBr3 to LDH, and greatly reduced the defect states in MAPbBr3. Importantly, the ion-conductive nature of LDH and its ability to form a charged surface layer even under low humidity conditions allowed it to attract and trap holes from MAPbBr3. This imparted tunable synaptic behaviors and short-term plasticity (STP) to long-term plasticity (LTP) transition to a two-terminal device based on the LDH-MAPbBr3 heterostructures. The further neuromorphic computing simulation under varying humidity conditions showcased their potential in learning and recognition tasks under ambient conditions. Our work presents a new type of epitaxial heterostructure comprising metal halide perovskites and layered ion-conductive materials, and provides a new way of realizing charge-trapping induced synaptic behaviors.

Application Scopes of Miniaturized MXene-Functionalized Electrospun Nanofibers-Based Electrochemical Energy Devices.

Exploring combinatorial materials, as well as rational device configuration design, are assumed to be the key strategies for deploying versatile electrochemical devices. MXene sheets have revealed a high hydrophilic surface with proper mechanical and electrical characteristics, rendering them supreme additive candidates to integrate in electrospun electrochemical power tools. The synergetic effects of MXene 2D layers with the nanofibrous networks can boost actuator responsive ability, battery capacity retention, fuel cell stability, sensor sensitivity, and supercapacitor areal capacitance. Their superior mechanical features can be endowed to the electrospun layers through the embedding of the MXene additive. In this review, the preparation and inherent features of the MXene configurations are briefly evaluated. The fabrication and overall performance of the MXene-loaded nanofibers applicable in electrochemical actuators, batteries, fuel cells, sensors, and supercapacitors are comprehensively figured out. Eventually, an outlook on the future development of MXene-based electrospun composites is presented. A substantial focus has been devoted to date to engineering conjugated MXene and electrospun fibrous frames. The potential performance of the MXene-decorated nanofibers presents a bright future of nanoengineering toward technological growth. Meanwhile, a balance between the pros and cons of the synthesized MXene composite layers is worthwhile to consider in the future.

Enhancing BYOD mobile device security in a hybrid environment

Research on enhancing Bring Your Own Device (BYOD) security in hybrid environments is critically relevant and important to protect data and ensure customer and organizational trust through the development of strong security policies. The study aims to develop and implement effective strategies and interventions that will help ensure that corporate data and resources are protected when employees use personal mobile devices in an environment where both on-premises and cloud-based resources are present. The methods used include analytical, deduction, modeling, statistical, and synthesis methods. This research identified specific vulnerabilities of potential threats to BYOD mobile devices in a hybrid environment and developed security strategies that include recommendations for creating a security policy and using a mobile device management system. The research led to the development of specific technical solutions, such as recommendations for mobile device configuration. This included educating employees and managers about security rules and the importance of adhering to security policies, and updated lists of current BYOD security threats and challenges given the changing threat environment. The practical value of the work lies in providing practical relevance to organizations by providing robust protection of sensitive data and resources, increasing employee comfort and confidence in the security of personal devices, easing IT departments’ tasks of device management and threat detection, and increasing customer and partner confidence in a security-layer organization.

Investigation on Sensitivity Amplification Factor of DGFET Electrochemical Sensors for pH Detection

There has been an increasing interest in the development of chemical and biological FET- based sensors due to their remarkable benefits in label-free detection that has been commonly used in both pH and DNA sensing respectively. In this work, recent Double-Gated Field Effect Transistor (DGFET) as transducers is investigated to understand the super- Nernstian response by amplifying the sensitivity capability in back-gate operations. The BioSensorLab tool was employed to evaluate pH-sensitivity amplification by studying the electrolyte screening and conduction modulation mechanisms which modeled by using Poisson-Boltzmann and Drift-Diffusion equations. The pH sensitivity amplification factors were investigated based on different geometrical configurations of DGFET devices, biasing conditions, and top oxide-electrolyte interfaces. pH sensitivity beyond Nernst limit was observed and increased linearly with the back oxide thickness of the DGFETs. DGFET with a sensitivity of 32.1 mV/pH operated through front-gate operation can be amplified to 195.4 mv/pH through the back-gate operation with a drain voltage of 0.5 V when the back gate oxide thickness increased to 150 nm. Higher pH-sensitivity responses of more than 200 mV/pH were observed where Al2O3 and Ta2O5 are used for the top oxide-electrolyte. It can be concluded that pH sensing of back gate operation ensures the DGFET transducers operated beyond the Nernst limit.

Fast Cycling Speed with Multimillion Cycling Endurance of Ultra‐Low Loss Phase Change Material (Sb2Se3) by Engineered Laser Pulse Irradiation

AbstractProgrammable and reconfigurable photonics is revolutionized the next generation of Si/SiN‐based photonics processors, optical signal processing, and neural and quantum networks. Ultra‐low loss phase‐change technology has the enormous potential to offer energy‐efficient, extra large‐scale integrated (ELSI) nonvolatile programmable photonics that can overcome the limitations of commonly used volatile and energy‐hungry programmable photonic systems. So far, most of the phase change materials (PCM) devices have already shown to be suitable for programmable and reconfigurable photonic circuit applications that do not require extreme endurance or ultra‐fast switching speeds. However, applications with ultra‐fast speed and multi‐million cycling requirements, such as memory cells, quantum computing, optical displays, and optical modulators necessitate enormous improvements in the existing cycling speed and endurance of PCMs, for high‐performance device configuration. Here, optical switching of an ultra‐low loss PCM (Sb2Se3) is demonstrated with an unprecedented combination of rapid cycling speed (0.6 × 105 cycles s−1) and extreme endurance (> 2 × 106 cycles) that pave the way for ultrafast, large‐scale, programmable, and reconfigurable integrated photonic circuits and devices.

Supported Iridium Catalysts for Water Electrolysers

It is essential to reduce iridium in water electrolysers without compromising performance to lower the cost of green hydrogen. One strategy often used in catalysis to reduce precious metal catalyst usage is to deposit catalysts on high surface area supports. However, the catalyst supports need to be stable under the reaction conditions and also economically viable. Additionally, the catalyst-support moieties need to be sufficiently conductive. In this project, we explore platinum coated titanium dioxide as supports for iridium catalysts. Platinum is necessary to improve conductivity of the support motifs. Without this conductive platinum layer, extremely high (75 wt%) iridium loadings are needed to prepare commercially viable supported iridium catalysts.1, 2 In this work we synthesise and characterise a systematic series of catalysts whereby the Pt loading is varied in order to understand the loading effect on conductivity, and thus, electrocatalytic activities and durabilities.Previously, we have demonstrated the efficacy of a Pt conductive layer as an effective strategy for boosting the mass activity of Iridium in a half-cell configuration.4 However, translating the performance, more critically durability, in a device remained to be demonstrated. Here, we also begin by rapidly assessing the electrochemical performance of the library of prepared catalysts in a half-cell configuration (rotating disk electrodes, RDEs). Subsequently, catalysts that show promising activity and durability in half-cell are integrated into a PEM electrolyser. This approach is economic and efficient since integrating catalysts into membrane electrode assemblies and running electrolyser tests are resource and time intensive. However, there are challenges associated with replicating activity and durability from half-cell to device performance.3 Thus, we also explore methodologies and strategies to optimise our half-cell investigations to mimic full device conditions more closely. We have demonstrated that our strategy to engineer iridium catalysts has led to greater than 50% reduction in iridium content necessary in water electrolysers. And yet, our devices show performance and durability comparable to state-of-the-art technology.In this presentation we will discuss remaining challenges for hydrogen production using proton exchange membrane water electrolysers. We will also present materials characterisations and electrochemical performance of our catalysts in half-cell and full device configuration.Reference: K. Ayers, N. Danilovic, R. Ouimet, M. Carmo, B. Pivovar and M. Bornstein, Annu Rev Chem Biomol Eng, 2019, 10, 219-239. M. Bernt, A. Hartig‐Weiß, M. F. Tovini, H. A. El‐Sayed, C. Schramm, J. Schröter, C. Gebauer and H. A. Gasteiger, Chemie Ingenieur Technik, 2020, 92, 31-39. T. Lazaridis, B. M. Stühmeier, H. A. Gasteiger and H. A. El-Sayed, Nature Catalysis, 2022, 5, 363-373. Y. N. Regmi, E. Tzanetopoulos, G. Zeng, X. Peng, D. I. Kushner, T. A. Kistler, L. A. King and N. Danilovic, ACS Catalysis, 2020, 10, 13125-13135.

(Invited, Digital Presentation) Integration of 2D Material Characterization and Reliability into Device Manufacturing

After the unique properties of graphene were realized, scientists began seeking other types of atomically thin materials that exhibited similar attractive and exciting properties. There is now a range of materials including single element (e.g. phosphorene) and compounds (e.g, transitional metal dichalcogenides and MXenes) that show promise for electronic, quantum, superconducting and optoelectronic applications. As with any new material, understanding structure and inherent defects is an important part to optimizing performance in these materials for their intended applications.Manufacturing optimized devices that incorporate newly-emerging materials requires predictable performance throughout device lifetimes. Unexpected degradation in device performance, sometimes leading to failure, is often traceable to poor material reliability. Reliability is rooted in the stability of the atoms making up a material, and is determined by geometry, microstructure, chemistry, dimensional scale, proximity to other materials, and exposure to external stressors. Integration of powerful characterization techniques and reliability tests of materials under operational conditions improves fundamental understanding and accelerates development of highly-reliable materials and devices.This talk will cover recent work on 2D materials characterization and reliability testing of these materials with the ultimate goal of manufacturability. Characterization of defects, primarily with transmission-SEM, to characterize diverse 2D materials (e.g., topological insulators, transition metal dichalcogenides, semiconductors) will be demonstrated. Initial measurement results to understand the impact of reliability challenges (e.g. electrical, thermal) the material may experience during manufacturing will be discussed. The advancement of this work to identify potential device configurations, material interfaces and use conditions that will be problematic will be presented.

(Invited) Vertically Stacked Graphene Junction Diodes

Graphene is expected to be nanomaterial of the post-silicon era because of its numerous advantageous properties. The single crystal graphene thermally grown on SiC substrate is considered the most promising platform for future electric devices. Large area epitaxial graphene on SiC substrate has been successfully fabricated using high-temperature rapid thermal annealing [1]. In this study, we present vertically stacked graphene junction diodes fabricated using direct bonding technique [2–4]. Figure 1(a) shows the schematic of a stacked graphene junction diode. Two graphene layers on SiC are directly bonded to each other. Gold–coated contact pins are attached to the graphene surface to establish ohmic contact. The graphene samples and contact probes are fixed by acrylic molds. Strong nonlinear current–voltage (I-V) characteristics are observed for this simple device configuration, as shown in Fig. 1(b). In the low bias voltage (Vb) region, the resistance of the graphene diode is approximately 20 GΩ. The current abruptly increases when the bias voltage is increased to approximately 30 V. The two-terminal resistance at a high bias voltage (100 V) is approximately 21 kΩ. The vertically stacked graphene junction exhibits bidirectional thyristor-type characteristics with a high on-off ratio of approximately 106. The Fowler–Nordheim (F-N) tunneling phenomenon is observed in the sub-threshold region. The gap distance estimated from the F-N plot is approximately 6 nm, which can be attributed to the large off resistance. The Coulomb force generated by applying the bias voltage causes the two graphene layers to attract each other, resulting in an electrically conductive state. The junction voltage (Vj) of the device was measured using a four-terminal configuration. As shown in Fig. 1(c), negative resistance is observed in the low-resistance region. The effective internal resistance of the junction diode is reduced to approximately 450 Ω. The off resistance of the diodes is considerably modified by the initial distance between the graphene layers. However, the I-Vj characteristics in the negative resistance region are identical for each device. This result suggests that the cause of the negative resistance phenomena is closely related to the band structure of graphene. A vertically stacked graphene junction diode with a high on-off ratio was demonstrated. The main component of the diode comprised a pair of single-crystal graphene layers fabricated through direct bonding. The negative resistance of the graphene diode presents new possibilities for the application of functional devices, such as terahertz emitters.[1] T. Aritsuki, et al., Jpn. J. Appl. Phys. 55 (2016) 06GF03.[2] J. Du, eta al., Jpn. J. Appl. Phys. 58 (2019) SDDE01.[3] N. Murakami, et al., Jpn. J. Appl. Phys. 60 (2021) SCCD01.[4] M. Ohi, et al., Jpn. J. Appl. Phys. 62 (2023) to be published. Figure 1

(Invited) Selective Area Growth, Etching, and Doping of GaN By MOCVD for Power Electronics

Gallium Nitride (GaN) possesses a wide band gap and excellent transport properties, making it a highly promising material for high-power and high-frequency applications. Microwave power amplification for commercial and military purposes has already benefited from GaN-based high electron mobility transistors (HEMTs). However, currently available GaN optoelectronic and electronic devices use planar junctions and heterostructures prepared by epitaxy, typically via metalorganic chemical vapor deposition (MOCVD). To enable more sophisticated device configurations, in-plane lateral junctions are necessary. The most effective method for achieving this is through selective area etching (SAE) followed by selective area growth (SAG). In this talk, we will discuss the progress made at Yale in the selective-area etching, growth, and doping of GaN.Selective-area etching of GaN is the most challenging and critical step in this process. Instead of using conventional ICP etching, we have employed tertiarybutylchloride (TBCl) as an in-situ chemical etchant of GaN in MOCVD to create smooth trenches and remove plasma etching-generated damages on the surface. With electrical and material characterizations, we have confirmed that TBCl etching is a low-damage and clean etching process. We will also describe our recent efforts to bypass the constraint of dielectric masking during in-situ etching and perform maskless selective area etching (SAE) to create low-defect lateral p-n junctions for GaN power electronics. Additionally, we will discuss non-planar selective-area growth and doping, including the principles of growth evolution, non-uniform Mg distribution, and parasitic impurities.This work is supported by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. DOE, under DE-AR0000871 as part of the PNDIODES program managed by Dr. Isik Kizilyalli.

Novel Thermoelectric Fabric Structure with Switched Thermal Gradient Direction toward Wearable In-Plane Thermoelectric Generators.

Wearable thermoelectric generators (TEGs) have exhibited great potential to convert the temperature gradient between the human body and the environment into electrical energy for maintenance-free wearable applications. A 2D planar device structure is widely employed for fabricating flexible TEGs due to its simple structure and facile fabrication properties. However, this device configuration is more appropriate for utilizing in-plane temperature differences than the out-of-plane direction, which limits their application in wearable cases since the temperature difference between the human body and the environment is in the out-of-plane direction. To solve this problem, a novel fabric-based TEG structure that can utilize the out-of-plane temperature gradient is proposed in this work. By introducing thermally conductive components in the generator, the out-of-plane temperature difference can be switched to the in-plane direction, which can be further utilized for 2D planar devices in wearable applications. The prepared thermoelectric fabric prototype with only 12 p-type TE legs exhibits a maximum open-circuit voltage of 4.69mV and an output power of 39.7 nW at a temperature difference of 30 K. This strategy exhibits a high degree of versatility and can be readily applied to other 2D planar TEGs, thus expanding their potential application in wearable technology.

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling

Abstract Neuroscience studies face challenges in gathering large datasets, which limits the use of machine learning (ML) approaches. One possible solution is to incorporate additional data from large public datasets; however, data collected in different contexts often exhibit systematic differences called dataset shifts. Various factors, for example, site, device type, experimental protocol, or social characteristics, can lead to substantial divergence of brain signals that can hinder the success of ML across datasets. In this work, we focus on dataset shifts in recordings of brain activity using MEG and EEG. State-of-the-art predictive approaches on magneto- and electroencephalography (M/EEG) signals classically represent the data by covariance matrices. Model-based dataset alignment methods can leverage the geometry of covariance matrices, leading to three steps: re-centering, re-scaling, and rotation correction. This work explains theoretically how differences in brain activity, anatomy, or device configuration lead to certain shifts in data covariances. Using controlled simulations, the different alignment methods are evaluated. Their practical relevance is evaluated for brain age prediction on one MEG dataset (Cam-CAN, n = 646) and two EEG datasets (TUAB, n = 1385; LEMON, n = 213). Among the same dataset (Cam-CAN), when training and test recordings were from the same subjects but performing different tasks, paired rotation correction was essential (δR2=+0.13 (rest-passive) or +0.17 (rest-smt)). When in addition to different tasks we included unseen subjects, re-centering led to improved performance (δR2=+0.096 for rest-passive, δR2=+0.045 for rest-smt). For generalization to an independent dataset sampled from a different population and recorded with a different device, re-centering was necessary to achieve brain age prediction performance close to within dataset prediction performance. This study demonstrates that the generalization of M/EEG-based regression models across datasets can be substantially enhanced by applying domain adaptation procedures that can statistically harmonize diverse datasets.

Asymmetric supercapacitor device fabrication of pristine Zeolitic Imidazolate Framework-67 with ultrahigh performance and cyclic stability

Employing a simple stirring and cost-effective approach, the pristine Zeolitic Imidazolate Framework-67 (ZIF-67) material is prepared and utilized as an electrode in three- and two-electrode (asymmetric device) configurations. The synthesized material exhibits well-defined rhombic dodecahedral morphology, noteworthy porosity, and a high specific surface area (1109.54 m2g−1). In the three-electrode configuration, the electrochemical study reveals a high specific capacitance (CS) of 377.8 Fg−1 and an outstanding cyclic stability (118.2 %) in a 6 M NaOH aqueous electrolyte. Furthermore, a device with a voltage window of 1.2 V was built employing a positive electrode (ZIF-67) and a negative electrode of activated carbon (AC). Interestingly, the ASSC demonstrated a maximum device-specific capacitance (CS) of 222.40 Fg−1, high energy density (ED) of 21.45 WhKg−1, and the highest power density (PD) of 3231.07 Wkg−1. Afterward, the ASSC device demonstrated remarkable cyclic stability (178.7 %) over 4000 constant galvanostatic charge/discharge (GCD) cycles. Different colors of LEDs (Light Emitting Diodes) and their series combinations are lightened using three devices (connected in series). As a result of the exceptional presentation of ZIF-67, it acts as a possible choice for energy storage devices.

Defect-Engineered Semiconducting van der Waals Thin Film at Metal-Semiconductor Interface of Field-Effect Transistors.

The significance of metal-semiconductor interfaces and their impact on electronic device performance have gained increasing attention, with a particular focus on investigating the contact metal. However, another avenue of exploration involves substituting the contact metal at the metal-semiconductor interface of field-effect transistors with semiconducting layers to introduce additional functionalities to the devices. Here, a scalable approach for fabricating metal-oxide-semiconductor (channel)-semiconductor (interfacial layer) field-effect transistors is proposed by utilizing solution-processed semiconductors, specifically semiconducting single-walled carbon nanotubes and molybdenum disulfide, as the channel and interfacial semiconducting layers, respectively. The work function of the interfacial MoS2 is modulated by controlling the sulfur vacancy concentration through chemical treatment, which results in distinctive energy band alignments within a single device configuration. The resulting band alignments lead to multiple functionalities, including multivalued transistor characteristics and multibit nonvolatile memory (NVM) behavior. Moreover, leveraging the stable NVM properties, we demonstrate artificial synaptic devices with 88.9% accuracy of MNIST image recognition.

Recent progress in device designs and dual‐functional photoactive materials for direct solar to electrochemical energy storage

AbstractEfficient solar energy utilization technologies are expected to promote the development of a carbon‐neutral and renewable energy society. Photovoltaic cells (PVs) have played an important role in the harvest and conversion of solar energy. Due to the intermittent instability of solar energy, however, PVs must be connected with energy storage systems (EESs). Newly developed photoelectrochemical energy storage devices (PESs) are proposed to directly convert solar energy into electrochemical energy. Initial PESs focused on the external and internal integration of PVs and EESs. However, the voltage mismatch between PVs and EESs leads to massive energy loss and unsatisfactory overall performances of PESs. PESs using dual‐functional photoactive materials (PAMs), which have simplified device configuration, decreased costs, and external energy loss, have recently emerged for realization of solar‐to‐electrochemical‐energy conversion and storage in a single device. The review summarizes the designing concepts, integrated configurations, and overall performances of different types of PESs, particularly PESs utilizing dual‐functional PAMs. Based on the classifications, working principles, basic requirements, and design principles, this review discusses various types of PESs cathodes. Finally, some perspectives are provided for further developing excellent performances of PESs.

Direct Seawater Electrolysis: From Catalyst Design to Device Applications.

Direct seawater electrolysis (DSE) for hydrogen production, using earth-abundant seawater as the feedstock and renewable electricity as the driving source, paves a new opportunity for flexible energy conversion/storage and smooths the volatility of renewable energy. Unfortunately, the complex environments of seawater impose significant challenges on the design of DSE catalysts, and the practical performance of many current DSE catalysts remains unsatisfactory on the device level. However, many studies predominantly concentrate on the development of electrocatalysts for DSE without giving due consideration to the specific devices. To mitigate this gap, the most recent progress (mainly published within the year 2020-2023) of DSE electrocatalysts and devices are systematically evaluated. By discussing key bottlenecks, corresponding mitigation strategies, and various device designs and applications, the tremendous challenges in addressing the trade-off among activity, stability, and selectivity for DSE electrocatalysts by a single shot are emphasized. In addition, the rational design of the DSE electrocatalysts needs to align with the specific device configuration, which is more effective than attempting to comprehensively enhance all catalytic parameters. This work, featuring the first review of this kind to consider rational catalyst design in the framework of DSE devices, will facilitate practical DSE development.

Event-oriented model of data flow control between embedded devices of a ground-based robotic vehicle

This paper discusses methods for extracting significant events from data streams generated by actuating and sen-sory devices built into robotic means. An event-oriented model for managing data streams between embedded devices of a ground-based robotic vehicle using a knowledge base that stores information about embedded de-vices and their configurations has been developed. To isolate significant events from the streams of data generat-ed by devices, the restrictions described in the device configurations are used. The proposed model also takes into account possible device failures. The generated events initiate the selection and launch of a certain process by a robotic means, for the description of which BPMN notation is used. The results of simulation modeling are shown, which confirm the effectiveness of the proposed event-oriented model, which provides a 41.8% reduction in data volumes processed by the central computer due to the distribution of calculations to the intermediate microcontrol-lers of embedded devices.

CFD Analysis of Airborne Pathogen Disinfection in a UV-C Air Purification Device

Abstract Numerical simulations of the airflow inside a portable air purification device have been carried out. The simplified system geometry is comprised of key components – fans, particle filters and UV lamps for disinfection, which are included in the model. The study investigates the velocity distribution, UV irradiance, and its impact on air disinfection. The effects of the flow rate and UV dose on the purification efficacy have been investigated. The findings provide valuable insights for optimising the design and configuration of air purification devices, and their potential role in reducing the transmission of airborne diseases.