Process Modules Research Articles

Sustainable management of end of life crystalline silicon solar panels in Australia: Advancing circular economy practices

The worldwide adaptation of Photovoltaic (PV) technology as a sustainable alternative to fossil fuels, has experienced exponential growth in recent years. However, the lack of effective waste management policies has hindered efficient PV panel disposal and recycling practices. In the absence of effective policies, the worldwide End-of-Life (EoL) PV module accumulation is predicted to reach a critical stage in the early 2030s. This study examines the environmental impacts of different EoL management practices using Life Cycle Assessment (LCA), based on a comprehensive database generated from both literature and industrial data. Five different EoL scenarios were considered for 1000 kg of Crystalline Silicon (c-Si) PV modules with a focus on Australia as a case study, while considering the energy recovery options and emphasizing the economic benefits. From a comprehensive LCA study, it is found that upcycling options reduce the environmental impacts significantly compared to downcycling, while chemical treatment emerges as a preferred option, demonstrating a reduced environmental burden. Nevertheless, the utilization of toxic chemicals during chemical treatment-based PV recycling needs to be reconsidered. Additionally, the usage of chemicals during the metal recovery process of PV module recycling caused the highest environmental burden, necessitating the importance of moving to greener treatment practices. This research study will enable the identification of optimum EoL c-Si module recycling options, contributing to sustainable waste management.

Theoretical investigation of two ideal radiative cooling materials and radiative sky water-cooling module with ideal selective radiative materials

Radiative sky cooling (RSC) is a passive approach to cool an object by emitting infrared thermal radiation to the cold outer space without any energy input and any pollutant produced. It has the potential to meet the rapidlygrowingdemandfor cooling. Radiative cooling materials and real-world applications are two concerns in RSC field. In this study, the cooling performance of two types of ideal radiative cooling materials are compared in term of the cooling power. The critical temperature at which broadband radiative materials exhibit cooling effect outside the atmospheric window is expressed as a fuction of the ambient temperature and the average atmospheric emissivity outside the atmospheric window. The temperature range for the broadband radiative materials with cooling effect outside the atmospheric window is very small, and thus selective radiative materials should be prioritized. Heat transfer processes of radiative sky water-cooling (RSWC) module with ideal selective radiative materials, which has broad application prospect, are then investigated by a theoretical model. As for ten-hour cooling process of a RSWC module under reference conditions, the temperature difference between the environment and the radiative panel rises to 5.68 °C, the temperature difference between the environment and the water rises to 3.76 °C, and the cooling power decreases from 53.5 W/m2 to 38.5 W/m2.The impact of night-time air temperature on the cooling power may reach up to 48.3 % when the atmospheric emissivity within the atmospheric window is 0.5. If the average atmospheric emissivity within the atmospheric window increases from 0.2 to 0.5 the cooling power of RSWC module decreases by 29.2 % − 39.2 %.

Real‐time reliability evaluation method for IGBT module in MMC based on junction temperature and bond wire failure online monitoring

AbstractThe lack of an MMC reliability evaluation approach that incorporates data on essential components' health monitoring in the already related research prevents reliability from being further improved. Therefore, this article proposes a real‐time reliability evaluation method of the multi‐state IGBT module in MMC through iterative calculation of the Markov chain model. The degradation process of the IGBT module is divided into multiple states based on the monitored bond wire failure, and the failure rate of the IGBT module is updated in real time using the accumulated monitoring data of junction temperature. The proposed method can more accurately reflect the real state of MMC compared with the binary state evaluation method. Besides, a multi‐channel high‐speed data acquisition board is designed to measuring the gate voltage and collector voltage of the IGBT for the health evaluation of IGBT modules in MMC; the typically measured results validate the effectiveness of the data acquisition board.

Scheduling Cluster Tools with Multi-Space Process Modules and a Multi-Finger-Arm Robot in Wafer Fabrication Subject to Wafer Residency Time Constraints

Scheduling Cluster Tools with Multi-Space Process Modules and a Multi-Finger-Arm Robot in Wafer Fabrication Subject to Wafer Residency Time Constraints

From data silos to seamless integration and coordination: a data-asset centric approach to smart hospital facility management

PurposeExisting hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.Design/methodology/approachThis study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.FindingsThe capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.Originality/valueThe initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

Sequential Recommendation Model Based on Deep Residual Recurrent Neural Network

In order to solve the problem that the sequence recommendation model based on RNN (Recurrent Neural Network) is prone to gradient vanishing or exploding when processing long sequences, which leads to the instability of the recommendation model training process, residual connection, layer normalization and feedforward neural network modules are introduced on the basis of the traditional gated recurrent unit (GRU), and a sequence recommendation model DeepGRU based on deep residual recurrent neural network is proposed. It is verified on 3 public datasets. The experimental results show that the DeepGRU has obvious advantages over the most advanced sequence recommendation methods (the average recommendation accuracy is improved 8.68%). The ablation experiment verifies the effectiveness of the introduced residual connection and other modules under the DeepGRU framework. In addition, the DeepGRU effectively alleviates the problem of unstable training process when processing long sequences.

Optimization of laser patterning process for eco-friendly tin-halide perovskite solar module – with a nanosecond green laser

The tin-based perovskite solar cells are promising future eco-friendly photovoltaic technology with increasing efficiency, which relies on fluorine-doped tin oxide (FTO) or indium tin oxide (ITO) as a transparent conducting oxide (TCO) for front contact. In the monolithic module fabrication process interconnections are executed by a series of three scribes with two different lasers 1064 nm and 532 nm. This study aims to simplify the interconnection process in tin-based perovskite solar modules by using a single visible laser source to perform all three scribes. The study uses an inverted device structure of Glass/TCO/ Poly(3,4-ethylenedioxythiophene): Polystyrene sulfonate (PEDOT: PSS)/Formamidinium-tin-iodide (FASnI3)/C60/Bathocuproine (BCP)/Ag and a 532 nm nanosecond pulsed laser source to pattern the ITO and FTO (P1 scribe), the PEDOT: PSS/FASnI3/C60/BCP stack (P2 scribe), and the PEDOT: PSS/FASnI3/C60/BCP/Ag (P3 scribe). The quality of the P1 scribe is assessed by examining the edges, completeness of film removal, cracking, film delamination, and elemental mapping using a stylus profiler, optical microscope, and energy dispersive x-ray spectroscopy. The P1 scribe is completely removed with line widths of 70 µm and 110 µm of ITO and FTO, respectively, without damage to the glass substrate. The profiles are steep, and the electrical isolation is greater than 40 MΩ. The same 532 nm laser is used for P2 and P3 scribes. The ablation of PEDOT: PSS during P2 and P3 scribe is studied by Raman spectroscopy. The results show that the use of a single 532 nm laser source can simplify the patterning process of monolithic tin-based perovskite solar modules, and potentially reduce production costs.

Presence of meaning in life and subjective well-being as mediators of association between sense of community and academic engagement

We examined the associations between sense of community (SoC) and multidimensional academic engagement, including whether meaning in life and subjective well-being mediate the relationships. Participants were Nigerian students who completed the Classroom Sense of Community Inventory–School Form (CSCI-SF), Meaning in Life Questionnaire’s (MLQ) Presence subscale, Brief Adolescent Subjective Well-being in School Scale (BASWSS), and Utrecht Work Engagement Scale – Student Version (UWES-S-9). Data was analysed using Model 6 of Hayes’ regression-based PROCESS module. Results showed that both presence of meaning and subjective well-being mediated the effects of aspects of SoC on vigour, dedication and overall academic engagement. The effects of SoC on absorption was only mediated by subjective wellbeing. Mediation pathways were not significant for the effects of learning SoC on absorption. In all cases, the strongest mediation existed in the paths linking social SoC to academic engagement through subjective wellbeing. Promotion of classroom SoC may facilitate presence of meaning in life and subjective wellbeing thereby enhancing academic engagement

A spiking neuron model of moral judgment in trolley dilemmas

People will make different moral judgments in similar moral dilemmas where one can act to sacrifice some number of lives to save several more. Research has shown that although people can reason that an action would save more lives, automatic processes can overwrite deliberate reasoning. Having participants imagine hypothetical moral dilemmas, researchers have discovered that factors such as action/omission, means/side-effect, and personal/impersonal can affect judgment. Joshua Greene suggests that these features do not affect people’s judgment because they are morally relevant but are instead a result of the myopic nature of the automatic moral process. Greene hypothesizes that there is some myopic module or domain-general process that attaches a negative emotional response to an action when one is contemplating violent actions. In the present research a model of this myopic automatic process is paired with an analytic system to replicate deontological and utilitarian responses to moral dilemmas. Our system, MERDJ, models this in simulated spiking neurons. The system takes in representations of specific moral dilemmas as inputs and outputs judgments of appropriate or inappropriate.

Collaborative Structure-Preserved Missing Data Imputation for Single-Cell RNA-Seq Clustering.

Clustering of the single-cell RNA-seq (scRNA-seq) transcriptome profiles is able to identify cell types, which is beneficial to improve the understanding of disease progression. However, in practice, the single-cell expression data often contains a significant number of missing values as a result of technical variability. Missing data is a critical challenge in scRNA-seq clustering analysis since the unknown value does not reflect the underlying true expression level and makes it difficult to discovering cell types by applying clustering algorithms directly. Various approaches have been developed to overcome missing data issue in scRNA-seq clustering. Most of them recover missing expression values by borrowing observed data from similar cells or synthesizing data via generative adversarial networks. Such that the biologically meaningful cluster structure has not been sufficiently exploited. In this work, we introduce ColImpute, a collaborative structure-preserved missing data imputation approach for the scRNA-seq clustering. Specifically, a cluster structure-preserved imputation module and a subspace clustering module, which respectively perform missing data imputation and cell subtypes identification, are integrated into a unified optimization framework to train the two networks in a collaborative manner. Consequently, the clustering module effectively contributes cluster-structure information to guide the trainning process of the missing data imputation module. Simultaneously, the cluster structure-preserved imputation module reciprocally enhances the performance of the clustering module by generating more precise recovered samples. Promising experimental results show that the proposed method is effective for both the data imputation and the cell types identification.

Characterization and Control of Carbon Nanotube Doping

Carbon nanotube FETs show great promise for beyond-Si and monolithic 3D electronics, however there are still fundamental questions to explore. In particular, controlled N- and P- doping is a fundamental process module which can be used to engineer semiconductor resistance in un-gated regions such as the contact or extension, as well as optimize band-to-band tunneling leakage [1-4]. To-date both N- and P- doping has been demonstrated for CNT, but the optimal strategies for doping control and carrier density quantification have not been determined. In this work, we present a study of N- and P- doping using solid-state dopants and doping control strategy using a dielectric barrier of tunable thickness. A TCAD evaluation reveals the tradeoffs between carrier density and mobility for increasing dielectric barrier thickness, and reveals the critical role of dielectric constant in optimizing performance of spacer doping [5]. Multiple characterization approaches under evaluation help to correlate doping strength to experimentally measurable quantities with insight into the doping mechanisms. Finally, we will summarize potential approaches for improving doping control and quantification, and progress towards integration of the doping in highly-scaled high-performance carbon nanotube FETs [6].[1] Z. Zhang, et al., “Complementary carbon nanotube metal-oxide-semiconductor field-effect transistors with localized solid-state extension doping,” Nature Electronics, 2023.[2] Q. Lin, et al., “Band-to-band Tunneling Leakage Current Characterization and Projection in Carbon Nanotube Transistors,” ACS Nano, 2023.[3] G. Zeevi, et al., “PN Junction and band to band tunneling in carbon nanotube transistors at room temperature,” Nanotechnology, 2021.[4] L. Liyanage, et al., “VLSI-compatible carbon nanotube doping technique with low work-function metal oxides,” Nano Letters, 2014.[5] C. Gilardi et al., “Barrier Booster for Remote Extension Doping and its DTCO for 1D & 2D FETs”, IEDM 2023[6] S.Li, et al., “High-performance and low parasitic capacitance CNT MOSFET: 1.2 mA/μm at VDS of 0.75 V by self-aligned doping in sub-20 nm spacer,” IEDM 2023.

(Keynote) High-Performance Carbon Nanotube Transistors for Logic Platform

Low-dimensional 1D and 2D materials hold promise as candidate channel materials for highly scaled and high-performance transistors beyond the limits of silicon-based transistors. This talk will first motivate transistors built on low-dimensional channels due to the significant speed, energy efficiency, and transistor density benefits enabled by their electronic and physical properties. This talk will focus on 1D carbon nanotube (CNT) semiconductors and describe the advanced device component process modules that have been demonstrated, explaining both the fundamental mechanisms of operation and device-level performance objectives. Single-CNT FET experimental studies give insight into the quality of (1) low resistance N- and P- contacts down to 10 nm contact length, (2) high-capacitance gate dielectrics optimized for deposition on SP2 carbon surfaces, and (3) controlled N- and P- remote dielectric doping. To achieve high current density each transistor must contain multiple CNTs, therefore we will review state-of-the-art strategies to assemble densely aligned arrays of CNT with controlled CNT spacing between 2-10 nm and uniform electronic bandgap. The final portion of the talk will highlight recent advances from our team and others to integrate the best device components together to demonstrate high-performance carbon nanotube MOSFETs. We will elaborate on the remaining challenges and provide a summary of device design tradeoffs that will help guide future studies.We are grateful for support and collaboration from TSMC Corporate Research, DoD, Stanford SystemX Alliance, Stanford Nanofabrication Facility, Stanford Nano Shared Facility, and the University of California at San Diego.

(Electronics and Photonics Division Award) Research Advances Wide- and Ultrawide-Bandgap Power Switching Devices

Wide bandgap semiconductors such as SiC and GaN (WBG) and emerging ultrawide-bandgap materials such as Ga2O3, AlGaN, and Diamond (UWBG) represent the next-generation materials for high performance medium voltage and high voltage power switch technology. Such devices have a wide range of immediate Naval applications, including high-power satellite communications and radar, unmanned underwater and aerial vehicles, ship drive components, and hybrid vehicle inverters. Vertical SiC power device technology has matured rapidly over the past two decades, owing to advances in substrates, a fundamental understanding of epitaxial growth to eliminate performance-limiting defects, as well as device design breakthroughs. This has enabled breakthroughs in highly integrated module design for medium voltage power conversion with switching frequency >100 kHz. In parallel, lateral GaN-based high electron mobility transistor (HEMT) technology has been highly successful for RF power amplifiers and is well positioned to supersede GaAs-based microwave circuits. Recently, GaN-based vertical and lateral power devices have attracted significant interest due to promising device results coupled with progress in native substrate, epitaxial growth, and processing technology developments. This seminar will present an overview of the WBG/UWBG power device efforts at NRL. This research has four primary focus areas – 1) thermal management in III-N power device structures by diamond thin film integration, 2) characterization of substrate materials and homoepitaxial layers used for drift regions of power devices identify appropriate specifications and benchmark performance, 3) process module development, particularly for selective area doping by ion implantation, and 4) pilot production manufacturing of 1.2kV-class PiN diodes including reliability assessments to identify and mitigate performance limiting defects.

Bridging the Digital Skills Gap in Accounting: The Process Mining Audit Professional Curriculum and Badge

SYNOPSIS We designed, implemented, and evaluated a curriculum that trains accounting students and professionals in process mining, an important emerging technology that is not extensively taught in most degree programs. We partnered with a leading provider of process mining software to create the “Process Mining Audit Professional Badge.” The badge’s curriculum combines modules focused on generic process mining skills and modules focused on process mining applications in auditing settings. In 22 months, 1,532 individuals completed the curriculum. Learners were highly satisfied with the training, ranked it among the most effective training modalities they had experienced, and perceived that they learned a great deal about both process mining and the auditing process. We demonstrate an approach to developing materials on emerging technologies that is perceived as useful by learners. If adopted more broadly, the approach could facilitate curricular integration of skills demanded by the profession.

Printed circuit board and printed circuit board assembly methods for testing and visual inspection: a review

Testing and visual inspection of printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) are important procedures in the manufacturing process of electronic modules and devices related to locating and identifying possible defects and failures. Earlier defects detection leads to decreasing expenses, time and used resources to produce high quality electronics. In this paper an exploration and analysis about the current research regarding methods for PCB and PCBA testing, techniques for defects detection and vusial inspection is performed. The impact of machine and deep learning for testing and visual inspection procedures is also investigated. The used methodology comprises bibliometric approach and content analysis of papers, indexed in scientific database Scopus, considering the queries: “PCB and testing” and “PCB and testing”, “printed circuit board assembly and testing” and “PCBA and testing”, “PCB defect detection” and “PCBA defect detection”, “PCB and visual inspection”, and “PCBA and visual inspection”. The findings are presented in the form of a framework, which summarizes the contemporary landscape of methods for PCBs and PCBAs testing and visual inspection.

Experimental study on frost growth patterns and surface wettability effects of precooler module

A thorough understanding of frosting and frost layer growth mechanisms inside the precooler of a hypersonic precooled engine is of crucial importance for controlling the deterioration of heat transfer and pressure loss caused by frosting, and ensuring the normal operation of the engine. In this study, ultra-fine thermocouples were used to measure temperature variations longitudinally during the frosting process of the precooler module. Combined with optical images, an investigation was conducted into the frost layer growth patterns of precooler heat exchange modules and the influence of surface wettability. The research results indicate that there are two different frosting patterns in the precooler: under low Reynolds numbers (≤1500), the pattern is CRT, while under high Reynolds numbers (≥2000), the pattern is ALT. Frosting at Re ≤1500 may cause serious deformation of the precooler tubes. The collapse phenomenon caused by the instability of the frost layer structure reduces the pressure loss coefficient relative to the local maximum by 4 % to 7 %. The higher the incoming Reynolds number, the later the collapse occurs. When Re is too low, collapse will not occur. The surface wetting characteristics reduce the pressure loss coefficient by 13.3 % to 24.2 % in the local range of Reynolds numbers from 1500 to 2800, and cause the pressure loss coefficient curve to rotate clockwise as a whole, enhancing heat transfer to some extent. Last but not least, the normal distribution of surface temperature cooling rates and the functionalization of axial temperature gradients of the tube indicate the possibility of a rapid prediction method for three-dimensional frosting under complex engineering conditions in precooler.

A study of expansion force propagation characteristics and early warning feasibility for the thermal diffusion process of lithium-ion battery modules

Research on thermal runaway warning and thermal propagation mechanism is of great importance for improving the thermal safety of lithium-ion batteries. This article focuses on the battery modules and examines the feasibility of using expansion force as thermal runaway warning signals. Results show that the utilization of the expansion force can detect battery failure 1314.61 s earlier and provide thermal runaway warnings 26 s earlier compared to that of temperature. This suggests that the use of the expansion force at the battery module level still shows good feasibility. In addition, the fluctuation mechanism of the expansion force during thermal propagation is further discussed by conducting experiments on the thermal propagation of modules with different sizes. Experimental results show that the superposition effect of adjacent battery expansion forces is the main influencing factor causing expansion force changes with two peaks. The fluctuation mechanism of expansion force can characterize the gas discharge behaviors of thermal runaway at different stages, such as the opening of pressure relief valves and multi-stage gas discharge during thermal runaway.

Implementasi Model Pembelajaran Project Based Learning (PJBL) dalam Meningkatkatkan Kreativitas Siswa pada Mata Pelajaran Bahasa Indonesia Kelas IV SD IT Al Fikri Islamic Green School

This research aims to find out how the implementation of the Project Based Learning (PJBL) learning model increases student creativity in Indonesian language subjects for class IV SD IT Al Fikri Islamic Green School. This research uses descriptive qualitative research methods which were carried out at SD IT Al Fikri Islamic Green School for the 2023/2024 academic year. The research was carried out through the opening stages of learning, planning projects and determining groups, preparing activity schedules, supervising the progress of projects and assessments. The research subjects were class IV of SD IT Al Fikri Islamic Green School, totaling 28 people. The research showed that teachers planned project based learning according to standards. module process Data was collected using sheets, knowledge tests, observation of student activities, documentation and interviews. The data collected was analyzed using qualitative descriptive analysis.The results of the research show that the Project Based Learning (PJBL) learning model can increase the creativity of fourth grade students at SD IT Al Fikri Islamic Green School in learning Indonesian as evidenced by the increase in student scores which are better than before.

Heterogeneous Integration of Acoustic Microextraction with an Optoelectronic Sensor on Glass for Nucleic Acid Testing.

Lab-on-a-chip systems (LOCs), characterized by their high sensitivity, low sample consumption, and portability, have significantly advanced the field of on-site testing. Despite the evolution of integrated LOCs from qualitative to quantitative analyses, on-chip full integration of sample preparation, purification, and multiplexed detection remains a challenge. Here, we propose a strategy for the heterogeneous integration of a set of complementary metal oxide semiconductor-compatible devices including acoustic resonator, thin-film resistors, and temperature/photosensors as a new type of LOC for nucleic acid testing (NAT). Programmed acoustic streaming-based particles and fluid manipulations largely simplify the nucleic acid extraction process including cell lysis, nucleic acid capture, and elution. The design of the acoustic microextraction module and extraction process was thoroughly studied. Benefitted by the microelectromechanical system approach, the conventional mechanical actions and complex flow control are avoided, which enables a compact hand-held NAT instrument without complicated peripherals. Validation experiments conducted on plasma-harboring mutations in the epidermal growth factor receptor (EGFR) gene confirmed the robustness of the system, achieving an impressive nucleic acid (NA) extraction efficiency of approximately 90% within 5 min and a limit of detection of the target NA in the plasma of 1 copy/μL.

Real-time hybrid test method for floating wind turbines: Focusing on the aerodynamic load identification

Since the development of floating wind turbine (FWT) shows a rapid trend towards larger capacity and larger rotor size, the traditional full-model basin test method has encountered limits. Especially the balance between the wind generation system (WGS) size and scale ratio of the model FWT system. Under such circumstances, the hybrid model test method provides the possibility to improve the FWT model test. In the hybrid model test method, the original physical model system is divided into physical subsystem and numerical subsystem, and the data acquisition and process module between the 2 subsystems plays an important role. In this paper, a framework of real-time hybrid test (RTHT) system is setup firstly, which combines physical model wind turbine and motion platform. The damping modification to the corresponding numerical code is applied to improve the motion calculation accuracy. Delay implementation is employed to avoid motion divergence. Then a simulation loop is setup in numerical environment to study the identification of aerodynamic load. The influence of identification accuracy to the RTHT result is analyzed. Lastly, the dual-accelerometer method of aerodynamic load identification is employed in the proposed RTHT system. Decay tests and irregular wave only tests are carried out to validate the aerodynamic load identification method. The capability and potential of the RTHT method of floating wind turbine model test is preliminary proved in the work of this paper.