Processing Steps Research Articles

Novel Pressure-less Adhesive Dispensing Strategy for Thin Die Applications

The automotive electronics market is facing increasingly demanding reliability requirements, along with restrictive European and international environmental legislations targeting the elimination of lead-based materials in electronics packages. As a result, pressure-less Ag-sinter adhesives have been identified as one of the most mature lead-free bonding materials, with thermal and electrical performances comparable or superior to lead-tin alloys, as well as reliability performances compliant with automotive mission profiles. Simultaneously, there is a clear trend towards using thinner dice (<200 µm) in the semiconductor packaging industry for automotive applications, driven primarily by the demand for devices with higher electrical performance. This poses a challenge for the use of pressure-less adhesives, as they have a natural tendency to climb up the vertical sides of the die, potentially causing adhesive to flow over the die surface and resulting in short circuits or yield loss during subsequent IC assembly process steps. Currently, one of the most established processes for controlling the rise of adhesive on the vertical sides of thin dice is 2D screen printing (also known as stencil printing). This process involves selectively printing a complete pattern of adhesive material onto a substrate, onto which the die can then be placed without the need to forcibly spread the pressure-less adhesive to achieve full die backside coverage. However, this process is associated with significant material wastage and is only applicable to flat substrates. The aim of this paper is to introduce an innovative dispensing strategy for thin dice, which dispenses the adhesive in a spiral pattern shape. This technique can be applied to both flat (2D) and non-flat (3D or downset) substrates and minimizes material waste by utilizing a standard time-pressure dispensing system. The paper provides an overview of the concept and the underlying dispensing strategy developed by Besi, as well as an example of its application for die thicknesses down to 110um and 3D substrates in some power packages manufactured by STMicroelectronics. Process capability is validated, and package reliability is demonstrated up to MSL3 + 1000 thermal cycles through scanning acoustic microscopy.

Positive Psychotherapy tools in groups

In Positive group therapy, certain tools can be used to moderate and guide the process and interactions, directing them toward specific topics: the use of stories and proverbs as narrative tools; visualization tools like the four areas of body, achievement, contact, and fantasy application in groups; actual capacities to describe group processes and interaction pattern; the group process as a matter of treatment, connotation and contents; positive group psychotherapy moderated in a five steps process; positive group theory to understand the internal and external group dynamics will be presented; sociodynamics and psychodynamic descriptions of the upcoming dynamic in groups.

Separation of Ethanol–Water Azeotrope Using Waste Carrageenan Filter‐Cake Adsorbent

ABSTRACTThe final step in the downstream processing of bioethanol is typically the removal of water from the ethanol–water azeotrope (95.6 wt.% ethanol) to obtain fuel‐grade ethanol (> 99 wt.%). This can be done by various techniques including distillation (azeotropic or extractive), membrane‐based separation, and adsorption using molecular sieves or bio‐based adsorbents. In this work, a waste by‐product of carrageenan production is studied for its efficacy as water adsorbent. This waste carrageenan filter‐cake (CFC) material is primarily composed of organics (22 wt.% cellulose and carrageenan) and ash (78 wt.% perlite) as inferred from the proximate analysis. The functional groups present in the material were identified by FTIR analyses, and the surface morphology was checked by FESEM. Liquid phase water adsorption isotherms at 30°C, 40°C, and 50°C were established and were found to be adequately described by both Langmuir (R2 = 0.93 to 0.97) and Brouers‐Sotolongo (R2 = 0.96 to 0.97) models. An enthalpy change of adsorption of about −17 kJ/mol was computed through the van't Hoff equation. An azeotropic mixture (95.6 wt.% ethanol) was successfully purified to above 99.2 wt.% ethanol in a CFC‐packed column. The CFC adsorbent was used in three adsorption–desorption cycles without much loss in capacity. Moreover, the Thomas model adequately described the breakthrough curves.

Regio‐ and Diastereoselective Cascade Synthesis of 5‐Alkylidene‐γ‐Lactams via Copper‐Catalyzed Hydro‐Oxycarbonylation

AbstractTransition metal‐catalyzed hydrofunctionalization of alkynes and, more precisely, the intramolecular hydro‐oxycarbonylation (cycloisomerization) of acetylenic acids, has been widely employed as a key step in cascade processes for the construction of valuable and complex molecules. However, in contrast with other aminonucleophiles, no method has been reported for the reaction between primary monoamines and non‐activated alkynoic acids. Hence, a procedure has been devised for the regio‐ and diastereoselective preparation of 5‐alkylidene‐γ‐lactams via a copper‐catalyzed cascade reaction between alkynoic acids and amines. The developed protocol proves to be scalable and demonstrates significant tolerance to a wide range of structurally diverse alkynoic acids and amines bearing various functional groups, as evidenced by 60 high‐yielding examples. An exhaustive experimental and computational analysis of the reaction is also provided to unravel the nature and role of the copper catalyst, the observed regioselectivity and the mechanism of the reaction.

Enhanced YOLOv8-based method for space debris detection using cross-scale feature fusion

Optical observations play a crucial role in monitoring space debris, and long exposure large field-of-view telescopes exhibit robust detection capabilities for identifying space debris. Nevertheless, a substantial volume of data, intricate noise, nonlinearity, and target discontinuities significantly affect the observational process. To address these intricate celestial background conditions, an enhanced YOLOv8-based method for spatial debris detection is introduced into this study. Initially, a cross-scale feature fusion module is incorporated into the neck network, followed by a subtle processing step for the feature fusion component. Finally, the content-aware reassembly of features module is employed to replace the original upsampling module, which enhances the efficiency and accuracy of feature reconstruction, thereby achieving effective detection and identification of spatial debris targets. The study utilized a dataset comprising astronomical images captured by an open-source large-field-of-view optical telescope. The experimental results show that the detection accuracy and speed of the method are improved, and that they can meet the requirements of space debris detection in complex backgrounds.

The prevalence of gas exchange data processing methods: a semi-automated scoping review.

Cardiopulmonary exercise testing involves collecting variable breath-by-breath data, sometimes requiring data processing of outlier removal, interpolation, and averaging before later analysis. These data processing choices, such as averaging duration, affect calculated values such as VO2max. However, assessing the implications of data processing without knowing popular methods worth comparing is difficult. In addition, such details aid study reproduction. We conducted a semi-automated scoping review of articles with exercise testing that collected data breath-by-breath from three databases. Of the 8,344 articles, 376 (mean 4.5%, 95% CI: 4.1-5.0%) and 581 (7.0%, 6.4-7.5%) described outlier removal and interpolation, respectively. A random subset of 1,078 articles revealed 60.9% (57.9-63.7%) reported averaging methods. Commonly documented outlier cutoffs were ± 3 or 4 SD (39.1% and 51.6%, respectively). The dominating interpolation duration and procedure were one second (93.9%) and linear interpolation (92.5%). Averaging methods commonly described were 30 (30.9%), 60 (12.4%), 15 (11.6%), 10 (11.0%), and 20 (8.1%) second bin averages. This shows that studies collecting breath-by-breath data often lack detailed descriptions of data processing methods, particularly for outlier removal and interpolation. While averaging methods are more commonly reported, improved documentation across all processing steps will enhance reproducibility and facilitate future research comparing data processing choices.

Barriers and facilitators to the implementation of the Assessment of Burden of Chronic Conditions tool in Dutch primary care: a context analysis

ObjectivesThe Assessment of Burden of Chronic Conditions (ABCC) tool is developed to facilitate a personalised approach to care through assessment and visualisation of a patient’s experienced burden of disease, and...

The Effect of Memorizing The Quran on Improving Students' Academic Achievement

In higher education institutions, the academic achievement of students is an important thing. Various activities and maximizing campus facilities are part of students' efforts to realize their best achievements. Against low academic achievement, a teacher is required to innovate learning and the various approaches used. One strategy that is often recommended by experts is through the strategy of memorizing the Qur'an. As the first step in the learning process, appropriate steps and techniques are needed and support the elements that influence it. The Qur'an and Tafsir Study Program at IAIN Palu has implemented a memorization system for its students to improve their academic achievement and the relationship of memorizing the Qur'an for Students of Qur'anic Science and Tafsir IAIN Palu.

Compact Quantum Cascade Laser-Based Noninvasive Glucose Sensor Upgraded with Direct Comb Data-Mining.

Mid-infrared spectral analysis has long been recognized as the most accurate noninvasive blood glucose measurement method, yet no practical compact mid-infrared blood glucose sensor has ever passed the accuracy benchmark set by the USA Food and Drug Administration (FDA): to substitute for the finger-pricking glucometers in the market, a new sensor must first show that 95% of their glucose measurements have errors below 15% of these glucometers. Although recent innovative exploitations of the well-established Fourier-transform infrared (FTIR) spectroscopy have reached such FDA accuracy benchmarks, an FTIR spectrometer is too bulky. The advancements of quantum cascade lasers (QCLs) can lead to FTIR spectrometers of reduced size, but compact QCL-based noninvasive blood glucose sensors are not yet available. This work reports on two compact sensor system designs, both reaching the FDA accuracy benchmark. Each design commonly comprises a mid-infrared QCL for emission, a multiple attenuation total reflection prism (MATR) for data acquisition, and a computer-controlled infrared detector for data analysis. The first design translates the comb-like signals into conventional spectra, and then data-mines the resultant spectra to yield blood glucose concentrations. When a pressure actuator is employed to press the patient's hypothenar against the MATR, the sensor accuracy is considered to reach the FDA accuracy benchmark. The second design abandons the data processing step of translating combs-to-spectra and directly data-mines the "first-hand" comb signal. Beyond increasing the measurement accuracy to the FDA accuracy benchmark, even without a pressure actuator, direct comb data-mining upgrades the sensor system with speed and data integrity, which can impact the healthcare of diabetic patients. Specifically, the sensor performance is validated with 492 glucose absorption scans in the time domain, each with 20 million datapoints measured from four subjects with glucose concentrations of 3.9-7.9 mM. The sensor data-mines 164 sets of critical singularity strengths, each comprising 4 critical singularity strengths directly from the 9840 million raw signal datapoints, and the 656 critical singularity strengths are subjected to a machine-learning regression model analysis, which yields 164 glucose concentrations. These concentrations are correlated with those measured with a standard finger-pricking glucometer. An accuracy of 99.6% is confirmed from the 164 measurements with errors not more than 15% from the reference of the standard glucometer.

Benchmarking protein language models for protein crystallization

The problem of protein structure determination is usually solved by X-ray crystallography. Several in silico deep learning methods have been developed to overcome the high attrition rate, cost of experiments and extensive trial-and-error settings, for predicting the crystallization propensities of proteins based on their sequences. In this work, we benchmark the power of open protein language models (PLMs) through the TRILL platform, a be-spoke framework democratizing the usage of PLMs for the task of predicting crystallization propensities of proteins. By comparing LightGBM / XGBoost classifiers built on the average embedding representations of proteins learned by different PLMs, such as ESM2, Ankh, ProtT5-XL, ProstT5, xTrimoPGLM, SaProt with the performance of state-of-the-art sequence-based methods like DeepCrystal, ATTCrys and CLPred, we identify the most effective methods for predicting crystallization outcomes. The LightGBM classifiers utilizing embeddings from ESM2 model with 30 and 36 transformer layers and 150 and 3000 million parameters respectively have performance gains by 3- than all compared models for various evaluation metrics, including AUPR (Area Under Precision-Recall Curve), AUC (Area Under the Receiver Operating Characteristic Curve), and F1 on independent test sets. Furthermore, we fine-tune the ProtGPT2 model available via TRILL to generate crystallizable proteins. Starting with 3000 generated proteins and through a step of filtration processes including consensus of all open PLM-based classifiers, sequence identity through CD-HIT, secondary structure compatibility, aggregation screening, homology search and foldability evaluation, we identified a set of 5 novel proteins as potentially crystallizable.

A Comparison of the Dimensional Characteristics and Plasma Parameters of Different Centrifuges Used for the Preparation of Autologous Platelet Concentrates: A Randomized Correlational Study.

The objective of this study was to evaluate autologous platelet-rich fibrin (PRF) membrane weights and measurements after production by different centrifuges. Moreover, the values obtained with blood cellular components were correlated. Twelve systemically healthy participants underwent dental implant surgery associated with PRF membranes as the graft biomaterial at the implant site. Prior to the surgical procedure, the chosen participants underwent blood count and coagulogram tests and presented on the surgical day. Nine tubes containing 10 mL of venous blood were collected from each individual. The tubes were randomly distributed and positioned in three different centrifuges: (C1) the Intra-lock L-PRF Process, (C2) the Kasvi Digital, and (C3) the PRF Montserrat. PRF membrane processing was carried out as described by each manufacturer. After the processing steps, the prepared wet PRFs (initial) were placed in the container (box) designated by the manufacturer for the obtention of PRF membranes. The weights and measurements of the "wet" PRFs (initial) and membranes (final) were obtained using a precision scale and digital caliper in an aseptic environment. The data were compared, and the statistical differences were analyzed using the Friedman test and the Dunn post hoc test; Pearson correlation tests were performed between macroscopic data and data from serum tests; statistical significance was set at 5% (p < 0.05). 108 blood collection tubes were collected. The average harvest time for each tube individually was 21.5 ± 9.9 s. The average time for blood collection (nine tubes) from each of the 12 individuals was 193.1 ± 72.4 s (p = 0.728). The average values were very similar between the centrifuges, both for the measurements and weights of the "plugs" as well as for the linear measurements (p > 0.05). Regarding the wet weights and the linear averages of the PRF membranes, it was observed that the wet PRF weights varied from 0.22 to 0.25 mg and the linear measurements from 24.1 to 26.7 mm, with no statistical differences between centrifuges (p > 0.05). The data presented by centrifuges C1 and C2 were more homogeneous, delivering a value of less than 25% variability compared to the C3 centrifuge, which achieved values greater than 33%. The proposed macroscopic dimensional evaluation found no differences between the autologous platelet concentrates obtained by different centrifuges, and no correlation was found between these PRFs and the patients' blood counts.

Manganese(I)-Catalyzed Enantioselective Alkylation To Access P-Stereogenic Phosphines.

This work introduces a novel Mn(I)-catalyzed enantioselective alkylation methodology that efficiently produces a wide array of P-chiral phosphines with outstanding yields and enantioselectivities. Notably, the exceptional reactivity of Mn(I) complexes in these reactions is demonstrated by their effective catalysis with both typically reactive alkyl iodides and bromides, as well as with less reactive alkyl chlorides. This approach broadens the accessibility to various P-chiral phosphines and simplifies the synthesis of chiral tridentate pincer phosphines to a concise 1-2 step process, contrary to conventional, labor-intensive multistep procedures. Importantly, the development significantly expands the applicability of earth-abundant Mn(I)-based complexes beyond their recently established roles in catalytic hydrogenative and conjugate addition reactions, emphasizing the catalytic potential of Mn(I) complexes as a viable alternative to noble metal chemistry and, in some cases, even surpassing their performance.

Dietitian perspective and experience: Implementation of telenutrition in Indonesia and the challenge of performing the nutrition-focused physical examination (NFPE).

Nutrition assessment is the first step of the nutrition care process (NCP), which includes investigating physical status and malnutrition signs. With the widespread digitalization of healthcare in Indonesia, including telehealth in dietetic practice (telenutrition), evidence is required to address the barriers and improve the current practice of conducting remote physical assessments. This study aimed to explore the adaptation of nutrition-focused physical examination (NFPE) using telenutrition in Indonesia. This qualitative study recruited Indonesian registered dietitians (RD) with experience in performing NCP using video conferences, phone calls, or other remote/online platforms. The search for participants was conducted until the information was considered sufficient. Data were collected using semistructured in-depth interviews. Thematic analysis was used to analyze the data. Eleven RDs were interviewed via video conference. Three themes emerged from the analysis: (1) feasibility and practicality, (2) barriers, and (3) adaptations and pre-requisites of remote physical assessment. Remote physical assessment was considered not practical by the majority. Barriers were categorized into technological challenges, lack of NFPE training and practice, and challenges in involving patients. Pre-appointment preparations, guiding the patients through video calls, or asking patients to send images of their bodies are adaptations needed for remote physical assessment. Challenges in remote physical assessment could be minimized by establishing protocols to deliver standardized care and ensure session efficiency. Additionally, strengthening the implementation and training of NFPE for dietitians in Indonesia is of paramount importance.

Dengue Virus Fusion Peptide Promotes Hemifusion Formation by Disordering the Interfacial Region of the Membrane.

Membrane fusion is the first step in the infection process of the enveloped viruses. Enveloped viruses fuse either at the cell surface or enter the cell through endocytosis and transfer their internal genetic materials by fusing with the endosomal membrane at acidic pH. In this work, we have evaluated the effect of the Dengue virus fusion peptide (DENVFP) on the polyethylene glycol (PEG)-mediated lipid mixing of vesicles (hemifusion formation) at pH 5 and pH 7.4 with varying cholesterol concentrations. We have demonstrated that the DENVFP promotes hemifusion formation during the fusion of small unilamellar vesicles (SUVs) mainly at pH 5.0. Moreover, the fusion process demonstrates a strong correlation between fusogenicity and the amount of membrane cholesterol. We have further evaluated the partitioning ability of the peptide in three different membranes at pH 5.0 and pH 7.4. The fusogenic ability of the peptide at pH 5.0 is associated with the composition-dependent binding affinity of the peptide to the membrane. The depth-dependent fluorescence probes are used to evaluate membrane organization and dynamics utilizing steady-state and time-resolved fluorescence spectroscopic techniques. Our results show that the DENV FP promotes hemifusion formation by fluidizing the interfacial region of the membrane.

Establishment of a Rapid and Convenient Fluoroimmunoassay Platform Using Antibodies Against PDL1 and HER2.

The development of accurate and high-throughput tools for cancer biomarker detection is crucial for the diagnosis, monitoring, and treatment of diseases. In this study, we developed a simple and rapid fluorescence-linked immunosorbent assay (FLISA) using fluorescent dye-conjugated antibody fragments against programmed cell death ligand 1 (PDL1) and human epithelial growth factor receptor 2 (HER2). We optimized key steps in the FLISA process, including antigen immobilization, blocking, and antibody reaction, reading the assay time to 3 h-significantly faster compared to the 23 h duration of usual FLISA. The limit of detection for the rapid FLISA in detecting PDL1 was lower than that of FLISA, and the detection of HER2 was similar between the two methods, indicating that the rapid FLISA provides a fast and accurate approach for detecting PDL1 and HER2. This robust platform can be readily adapted for various fluoroimmunoassays targeting other antigens of interest.

Protocol for genetic analysis of population-scale ultra-low-depth sequencing data.

Non-invasive prenatal testing (NIPT) not only enables the detection of chromosomal anomalies in fetuses but also generates vast amounts of ultra-low-depth sequencing data, which can be leveraged for population genomic studies. Here, we present a protocol designed for massive ultra-low-depth sequencing datasets. We detail the steps for data processing, quality control, and genotype imputation, followed by genome-wide association study (GWAS) and post-GWAS analyses. This protocol applies to a wide range of ultra-low-depth sequencing studies, extending beyond data from NIPT. For complete details on the use and execution of this profile, please refer to Xiao etal.1.

Improved Ammonia Synthesis and Energy Output from Zinc-Nitrate Batteries by Spin-State Regulation in Perovskite Oxides.

Electrocatalytic nitrate reduction to ammonia (eNRA) is a promising route toward environmental sustainability and clean energy. However, its efficiency is often limited by the slow conversion of intermediates due to spin-forbidden processes. Here, we introduce a novel A-site high-entropy strategy to develop a new perovskite oxide (La0.2Pr0.2Nd0.2Ba0.2Sr0.2)CoO3-δ (LPNBSC) for eNRA. The LPNBSC possesses a higher concentration of high-spin (HS) cobalt-active centers, resulting from an increased concentration of [CoO5] structural motifs compared to conventional LaCoO3. Consequently, this material exhibits a significantly improved electrocatalytic performance toward ammonia (NH3) production, resulting in a 3-fold increase in yield rate (129 μmol h-1 mgcat.-1) and a 2-fold increase in Faradaic efficiency (FE, 76%) compared to LaCoO3 at the optimal potential. Furthermore, the LPNBSC-based Zn-nitrate battery reaches a maximum FE of 82% and an NH3 yield rate of 57 μmol h-1 cm-2. Density functional theory calculations reveal that A-site high-entropy management in perovskites facilitates nitrate activation and potentially optimizes the thermodynamic rate-determining step of the eNRA process, namely, *HNO3 + H+ + e- → *NO2 + H2O. This work presents an efficient concept for modulating the spin state of the B-site metal in perovskites and offers valuable insights for the design of high-performance eNRA catalysts.

Ultrasonic‐Assisted Adsorptive Uptake of Malachite Green Dye Onto Zn/Cu‐Layered Double Oxide: Spectrophotometric and Smartphone‐Based Detection

ABSTRACTIn this work, efforts have been made to synthesize novel Zn/Cu‐layered double oxide by performing calcination of Zn/Cu‐layered double hydroxide, which was later used as an adsorbent for the uptake of toxic azo dye. Malachite green (MG) was used as a model cationic dye for assessing the practicability of dye wastewater treatment. From batch experiments study, it was evident that ultrasonication‐assisted adsorption enables 90% of the MG to be removed from water within 30 min at neutral pH conditions. The ultrasound‐assisted sorption process was driven by the acoustic cavitation process, which facilitated a homogeneous distribution of active adsorption sites on surface of the adsorbent resulting efficient removal of dye molecules. As predicted by the Langmuir isotherm model, the sorbent exhibited maximum adsorption capacity of 128.20 mg/g, and based on kinetic measurements, the pseudo‐second‐order adsorption model was found to be most accurate. The kinetic studies also revealed that intraparticle diffusion is the rate‐limiting step of the adsorption process. The current study also demonstrates smartphone‐assisted estimation of adsorbed MG dye in order to provide a simple, convenient, cost‐effective, and instrument‐free method to quantify dye concentration. A smartphone‐based app called “ColorPicker” was used to calculate MG dye adsorption rate in real time based on RGB values and colorimetric responses. The percent removal obtained using smartphone app (87%) was in agreement with the data obtained using UV–vis spectroscopy (90%). As a result of its excellent properties, Zn/Cu‐LDO appears to be a potential candidate for wastewater remediation.

Simple and cost-effective method to measure the length of optical fibers.

Precise and accurate length measurements of optical fibers are increasingly needed across various applications. However, many commercially available devices are either too inaccurate or, conversely, too advanced and costly for basic fiber length determinations. In this Letter, we present a simple and relatively inexpensive method to measure the length of optical fibers with a precision of 1.06 ps (∼212 μm). This method exploits the relationship between the phase difference of a fiber under test (FUT) and a calibrated reference path as a function of frequency, measured by a phase-locked loop during a frequency sweep. We highlight key processing steps to achieve reproducible results and important considerations regarding environmental conditions.

An Ontology‐Augmented Digital Twin for Fiber‐Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades

A methodology for establishing a structural digital twin is proposed to facilitate the lifetime prediction of fiber‐reinforced polymer (FRP) structures, in this case, a wind turbine rotor blade. The digital twin incorporates production peculiarities and imperfections occurring during the manufacturing process of the FRP component. The methodology involves the computation of process‐defined effective elastic properties and residual stresses through numerical simulation of the resin cure cycle. The results are then transferred to a structural finite‐element model. By applying local wind conditions to this model, a comprehensive state of stress is obtained. This serves as a basis for a practical evaluation of material fatigue within the composite, leading to the prediction of the component's lifetime. The entire workflow is implemented in a Jupyter‐based application that uses an ontology with an appertaining knowledge graph to facilitate the transfer of intermediate results between the observation scales and process steps of the digital twin. In line with the principles of open science, the methodology utilizes open‐source software.