Hybrid Organic-Si C-MOSFET Image Sensor Designed with Blue-, Green-, and Red-Sensitive Organic Photodiodes on Si C-MOSFET-Based Photo Signal Sensor Circuit.

The resolution of Si complementary metal-oxide-semiconductor field-effect transistor (C-MOSFET) image sensors (CISs) has been intensively enhanced to follow the technological revolution of smartphones, AI devices, autonomous cars, robots, and drones, approaching the physical and material limits of a resolution increase in conventional Si CISs because of the low quantum efficiency (i.e., ~40%) and aperture ratio (i.e., ~60%). As a novel solution, a hybrid organic-Si image sensor was developed by implementing B, G, and R organic photodiodes on four n-MOSFETs for photocurrent sensing. Photosensitive organic donor and acceptor materials were designed with cost-effective small molecules, i.e., the B, G, and R donor and acceptor small molecules were Coumarin6 and C_60, DMQA and MePTC, and ZnPc and TiOPc, respectively. The output voltage sensing margins (i.e., photocurrent signal difference) of the hybrid organic-Si B, G, and R image sensor pixels presented results 17, 11, and 37% higher than those of conventional Si CISs. In addition, the hybrid organic-Si B, G, and R image sensor pixels could achieve an ideal aperture ratio (i.e., ~100%) compared with a Si CIS pixel using the backside illumination process (i.e., ~60%). Moreover, they may display a lower fabrication cost than image sensors because of the simple image sensor structure (i.e., hybrid organic-Si photodiode with four n-MOSFETs).

Potassium Iodide Doping for Vacancy Substitution and Dangling Bond Repair in InP Core-Shell Quantum Dots.

This work highlights the novel approach of incorporating potassium iodide (KI) doping during the synthesis of In0.53P0.47 core quantum dots (QDs) to significantly reduce the concentration of vacancies (i.e., In vacancies; VIn-) within the bulk of the core QD and inhibit the formation of InPOx at the core QD-Zn0.6Se0.4 shell interfaces. The photoluminescence quantum yield (PLQY) of ~97% and full width at half maximum (FWHM) of ~40 nm were achieved for In0.53P0.47/Zn0.6Se0.4/Zn0.6Se0.1S0.3/Zn0.5S0.5 core/multi-shell QDs emitting red light, which is essential for a quantum-dot organic light-emitting diode (QD-OLED) without red, green, and blue crosstalk. KI doping eliminated VIn- in the core QD bulk by forming K+-VIn- substitutes and effectively inhibited the formation of InPO4(H2O)2 at the core QD-Zn0.6Se0.4 shell interface through the passivation of phosphorus (P)-dangling bonds by P-I bonds. The elimination of vacancies in the core QD bulk was evidenced by the decreased relative intensity of non-radiative unpaired electrons, measured by electron spin resonance (ESR). Additionally, the inhibition of InPO4(H2O)2 formation at the core QD and shell interface was confirmed by the absence of the {210} X-ray diffraction (XRD) peak intensity for the core/multi-shell QDs. By finely tuning the doping concentration, the optimal level was achieved, ensuring maximum K-VIn- substitution, minimal K+ and I- interstitials, and maximum P-dangling bond passivation. This resulted in the smallest core QD diameter distribution and maximized optical properties. Consequently, the maximum PLQY (~97%) and minimum FWHM (~40 nm) were observed at 3% KI doping. Furthermore, the color gamut of a QD-OLED display using R-, G-, and B-QD functional color filters (i.e., ~131.1%@NTSC and ~98.2@Rec.2020) provided a nearly perfect color representation, where red-light-emitting KI-doped QDs were applied.

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome.

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 µL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

A framework for quality control in quantitative proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.

Diel metabolic patterns revealed by in situ transcriptome and proteome in a vertically migratory copepod.

Zooplankton undergo a diel vertical migration (DVM) which exposes them to gradients of light, temperature, oxygen, and food availability on a predictable daily schedule. Disentangling the co-varying and potentially synergistic interactions on metabolic rates has proven difficult, despite the importance of this migration for the delivery of metabolic waste products to the distinctly different daytime (deep) and nighttime (surface) habitats. This study examines the transcriptomic and proteomic profiles of the circumglobal migratory copepod, Pleuromamma xiphias, over the diel cycle. The transcriptome showed that 96% of differentially expressed genes were upregulated during the middle of the day - the period often considered to be of lowest zooplankton activity. The changes in protein abundance were more spread out over time, peaking (42% of comparisons) in the early evening. Between 9:00 and 15:00, both the transcriptome and proteome datasets showed increased expression related to chitin synthesis and degradation. Additionally, at 09:00 and 22:00, there were increases in myosin and vitellogenin proteins, potentially linked to the stress of migration and/or reproductive investment. Based on protein abundances detected, there is an inferred switch in broad metabolic processes, shifting from electron transport system in the day to glycolysis and glycogen mobilization in the afternoon/evening. These observations provide evidence of the diel impact of DVM on transcriptomic and proteomic pathways that likely influence metabolic processes and subsequent excretion products, and clarify how this behaviour results in the direct rapid transport of waste metabolites from the surface to the deep ocean.

Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population.

Alzheimer's disease (AD) is a prevalent and costly age-related dementia. Heritable factors account for 58-79% of variation in late-onset AD, but substantial variation remains in age-of- onset, disease severity, and whether those with high-risk genotypes acquire AD. To emulate the diversity of human populations, we utilized the AD-BXD mouse panel. This genetically diverse resource combines AD genotypes with multiple BXD strains to discover new genetic drivers of AD resilience. Comparing AD-BXD carriers to noncarrier littermates, we computed a novel quantitative metric for resilience to cognitive decline in the AD-BXDs. Our quantitative AD resilience trait was heritable and genetic mapping identified a locus on chr8 associated with resilience to AD mutations that resulted in amyloid brain pathology. Using a hippocampus proteomics dataset, we nominated the mitochondrial glutathione S reductase protein (GR or GSHR) as a resilience factor, finding that the DBA/2J genotype was associated with substantially higher GR abundance. By mapping protein QTLs (pQTLs), we identified synaptic organization and mitochondrial proteins coregulated in trans with a cis-pQTL for GR. We found four coexpression modules correlated with the quantitative resilience score in aged 5XFAD mice using paracliques, which were related to cell structure, protein folding, and postsynaptic densities. Finally, we found significant positive associations between human GSR transcript abundance in the brain and better outcomes on AD-related cognitive and pathology traits in the Religious Orders Study/Memory and Aging project (ROSMAP). Taken together, these data support a framework for resilience in which neuronal antioxidant pathway activity provides for stability of synapses within the hippocampus.

Efficient polyhydroxybutyrate production using acetate by engineered Halomonas sp. JJY01 harboring acetyl-CoA acetyltransferase.

Polyhydroxybutyrate (PHB) is a well-known biodegradable bioplastic synthesized by microorganisms and can be produced from volatile fatty acids (VFAs). Among VFAs acetate can be utilized by Halomonas sp. YLGW01 for growth and PHB production. In this study, Halomonas sp. JJY01 was developed through introducing acetyl-CoA acetyltransferase (atoAD) with LacIq-Ptrc promoter into Halomonas sp. YLGW01. The effect of expression of atoAD on acetate was investigated by comparison with acetate consumption and PHB production. Shake-flask study showed that Halomonas sp. JJY01 increased acetate consumption rate, PHB yield and PHB production (0.27 g/L/h, 0.075 g/g, 0.72 g/L) compared to the wild type strain (0.17 g/L/h, 0.016 g/g, 0.11 g/L). In 10 L fermenter scale fed-batch fermentation, the growth of Halomonas sp. JJY01 resulted in higher acetate consumption rate, PHB yield and PHB titer (0.55 g/L/h, 0.091 g/g, 4.6 g/L) than wild type strain (0.35 g/L/h, 0.067 h/h, 2.9 g/L). These findings demonstrate enhanced acetate utilization and PHB production through the introduction of atoAD in Halomonas strains.

Design of Fire Risk Estimation Method Based on Facility Data for Thermal Power Plants.

In this paper, we propose a data classification and analysis method to estimate fire risk using facility data of thermal power plants. To estimate fire risk based on facility data, we divided facilities into three states-Steady, Transient, and Anomaly-categorized by their purposes and operational conditions. This method is designed to satisfy three requirements of fire protection systems for thermal power plants. For example, areas with fire risk must be identified, and fire risks should be classified and integrated into existing systems. We classified thermal power plants into turbine, boiler, and indoor coal shed zones. Each zone was subdivided into small pieces of equipment. The turbine, generator, oil-related equipment, hydrogen (H2), and boiler feed pump (BFP) were selected for the turbine zone, while the pulverizer and ignition oil were chosen for the boiler zone. We selected fire-related tags from Supervisory Control and Data Acquisition (SCADA) data and acquired sample data during a specific period for two thermal power plants based on inspection of fire and explosion scenarios in thermal power plants over many years. We focused on crucial fire cases such as pool fires, 3D fires, and jet fires and organized three fire hazard levels for each zone. Experimental analysis was conducted with these data set by the proposed method for 500 MW and 100 MW thermal power plants. The data classification and analysis methods presented in this paper can provide indirect experience for data analysts who do not have domain knowledge about power plant fires and can also offer good inspiration for data analysts who need to understand power plant facilities.

Unveiling Resilience to Alzheimer's Disease: Insights From Brain Regional Proteomic Markers.

Studying proteomics data of the human brain could offer numerous insights into unraveling the signature of resilience to Alzheimer's disease. In our previous study with rigorous cohort selection criteria that excluded 4 common comorbidities, we harnessed multiple brain regions from 43 research participants with 12 of them displaying cognitive resilience to Alzheimer's disease. Based on the previous findings, this work focuses on 6 proteins out of the 33 differentially expressed proteins associated with resilience to Alzheimer's disease. These proteins are used to construct a decision tree classifier, enabling the differentiation of 3 groups: (i) healthy control, (ii) resilience to Alzheimer's disease, and (iii) Alzheimer's disease with dementia. Our analysis unveiled 2 important regional proteomic markers: Aß peptides in the hippocampus and PA1B3 in the inferior parietal lobule. These findings underscore the potential of using distinct regional proteomic markers as signatures in characterizing the resilience to Alzheimer's disease.

Optimization of polyhydroxyalkanoate production in Halomonas sp. YLGW01 using mixed volatile fatty acids: a study on mixture analysis and fed-batch strategy.

Polyhydroxyalkanoate (PHA) is one of the most promising materials for replacing petroleum-based plastics, and it can be produced from various renewable biomass sources. In this study, PHA production was conducted using Halomonas sp. YLGW01 utilizing mixed volatile fatty acids (VFAs) as carbon sources. The ratio and concentration of carbon and nitrogen sources were optimized through mixture analysis and organic nitrogen source screening, respectively. It was found that the highest cell dry weight (CDW) of 3.15 g/L and PHA production of 1.63 g/L were achieved when the ratio of acetate to lactate in the mixed VFAs was 0.45:0.55. Furthermore, supplementation of organic nitrogen sources such as soytone resulted in a ninefold increase in CDW (reaching 2.32 g/L) and a 22-fold increase in PHA production (reaching 1.60 g/L) compared to using inorganic nitrogen sources. Subsequently, DO-stat, VFAs consumption rate stat, and pH-stat fed-batch methods were applied to investigate and evaluate PHA productivity. The results showed that when pH-stat-based VFAs feeding was employed, a CDW of 7 g/L and PHA production of 5.1 g/L were achieved within 68 h, with a PHA content of 73%. Overall, the pH-stat fed-batch strategy proved to be effective in enhancing PHA production by Halomonas sp. YLGW01 utilizing VFAs.

Brain proteomic analysis implicates actin filament processes and injury response in resilience to Alzheimer's disease.

Resilience to Alzheimer's disease is an uncommon combination of high disease burden without dementia that offers valuable insights into limiting clinical impact. Here we assessed 43 research participants meeting stringent criteria, 11 healthy controls, 12 resilience to Alzheimer's disease and 20 Alzheimer's disease with dementia and analyzed matched isocortical regions, hippocampus, and caudate nucleus by mass spectrometry-based proteomics. Of 7115 differentially expressed soluble proteins, lower isocortical and hippocampal soluble Aß levels is a significant feature of resilience when compared to healthy control and Alzheimer's disease dementia groups. Protein co-expression analysis reveals 181 densely-interacting proteins significantly associated with resilience that were enriched for actin filament-based processes, cellular detoxification, and wound healing in isocortex and hippocampus, further supported by four validation cohorts. Our results suggest that lowering soluble Aß concentration may suppress severe cognitive impairment along the Alzheimer's disease continuum. The molecular basis of resilience likely holds important therapeutic insights.

A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer's disease.

Alzheimer's disease (AD) is a looming public health disaster with limited interventions. Alzheimer's is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.

Fumed Silica-Based Ultra-High-Purity Synthetic Quartz Powder via Sol-Gel Process for Advanced Semiconductor Process beyond Design Rule of 3 nm.

Fumed silica-based ultra-high-purity synthetic quartz powder was developed via the sol-gel process to apply to quartz wares and quartz crucibles for use in advanced semiconductor processes. The process conditions of preparing potassium silicate solution, gelation, and cleaning were optimized, i.e., the relative ratio of fumed silica (10 wt%) to KOH (4 wt%) for potassium silicate solution, gelation time 3 h, and cleaning for 1 h with 5 wt% HCl solution. It was observed that the gelation time strongly affected the size distribution of the quartz powder; i.e., a longer gelation time led to a larger size (d50) of the synthesized quartz powder: 157 µm for 2 h and 331 µm for 5 h. In particular, it was found that the morphology of the as-synthesized quartz powder greatly depended on the pulverizing process; i.e., the shape of quartz powder was shown to be rod-shaped for the without-gel-pulverizing process and granular-shaped with the process. We expect that the fumed silica-based ultra-high-purity quartz powder with an impurity level of 74.1 ppb synthesized via the sol-gel process is applicable as a raw material for quartz wares and crucibles for advanced semiconductor processes beyond the design rule of 3 nm.

Simple Ge/Si bilayer junction-based doping-less tunnel field-effect transistor.

Tunnel field-effect transistors (TFETs) have garnered great interest as an option for the replacement of metal-oxide-semiconductor field-effect transistors owing to their extremely low off-current and fast switching suitable for low-power-consumption applications. However, conventional doped TFETs have the disadvantage of introducing undesirable random dopant fluctuation (RDF) events, which cause a large variance in the threshold voltage and ambipolar leakage current at negative gate voltages. In this study, a simple approach for charge plasma-based doping-less TFETs (DL-TFETs), including the Ge/Si bilayer frame, which affects the RDF and low on-current issues, was developed by the commercially available Silvaco Atlas device simulator. The use of the Ge/Si bilayer enhances the on-current and point subthreshold swing to 1.4 × 10-6A and 16.6 mV dec-1, respectively. In addition, the dependencies of the Ge/Si junction boundary position and Ge content were examined systematically to attain a firm understanding of the electrical features in DL-TFETs.

Serum plays an important role in reprogramming the seasonal transcriptional profile of brown bear adipocytes.

Understanding how metabolic reprogramming happens in cells will aid the progress in the treatment of a variety of metabolic disorders. Brown bears undergo seasonal shifts in insulin sensitivity, including reversible insulin resistance in hibernation. We performed RNA-sequencing on brown bear adipocytes and proteomics on serum to identify changes possibly responsible for reversible insulin resistance. We observed dramatic transcriptional changes, which depended on both the cell and serum season of origin. Despite large changes in adipocyte gene expression, only changes in eight circulating proteins were identified as related to the seasonal shifts in insulin sensitivity, including some that have not previously been associated with glucose homeostasis. The identified serum proteins may be sufficient for shifting hibernation adipocytes to an active-like state.

Silicon Wafer CMP Slurry Using a Hydrolysis Reaction Accelerator with an Amine Functional Group Remarkably Enhances Polishing Rate.

Recently, as an alternative solution for overcoming the scaling-down limitations of logic devices with design length of less than 3 nm and enhancing DRAM operation performance, 3D heterogeneous packaging technology has been intensively researched, essentially requiring Si wafer polishing at a very high Si polishing rate (500 nm/min) by accelerating the degree of the hydrolysis reaction (i.e., Si-O-H) on the polished Si wafer surface during CMP. Unlike conventional hydrolysis reaction accelerators (i.e., sodium hydroxide and potassium hydroxide), a novel hydrolysis reaction accelerator with amine functional groups (i.e., 552.8 nm/min for ethylenediamine) surprisingly presented an Si wafer polishing rate >3 times higher than that of conventional hydrolysis reaction accelerators (177.1 nm/min for sodium hydroxide). This remarkable enhancement of the Si wafer polishing rate for ethylenediamine was principally the result of (i) the increased hydrolysis reaction, (ii) the enhanced degree of adsorption of the CMP slurry on the polished Si wafer surface during CMP, and (iii) the decreased electrostatic repulsive force between colloidal silica abrasives and the Si wafer surface. A higher ethylenediamine concentration in the Si wafer CMP slurry led to a higher extent of hydrolysis reaction and degree of adsorption for the slurry and a lower electrostatic repulsive force; thus, a higher ethylenediamine concentration resulted in a higher Si wafer polishing rate. With the aim of achieving further improvements to the Si wafer polishing rates using Si wafer CMP slurry including ethylenediamine, the Si wafer polishing rate increased remarkably and root-squarely with the increasing ethylenediamine concentration.

Super-Linear-Threshold-Switching Selector with Multiple Jar-Shaped Cu-Filaments in the Amorphous Ge3 Se7 Resistive Switching Layer in a Cross-Point Synaptic Memristor Array.

The learning and inference efficiencies of an artificial neural network represented by a cross-point synaptic memristor array can be achieved using a selector, with high selectivity (Ion /Ioff ) and sufficient death region, stacked vertically on a synaptic memristor. This can prevent a sneak current in the memristor array. A selector with multiple jar-shaped conductive Cu filaments in the resistive switching layer is precisely fabricated by designing the Cu ion concentration depth profile of the CuGeSe layer as a filament source, TiN diffusion barrier layer, and Ge3 Se7 switching layer. The selector performs super-linear-threshold-switching with a selectivity of > 107 , death region of -0.70-0.65 V, holding time of 300 ns, switching speed of 25 ns, and endurance cycle of > 106 . In addition, the mechanism of switching is proven by the formation of conductive Cu filaments between the CuGeSe and Ge3 Se7 layers under a positive bias on the top Pt electrode and an automatic rupture of the filaments after the holding time. Particularly, a spiking deep neural network using the designed one-selector-one-memory cross-point array improves the Modified National Institute of Standards and Technology classification accuracy by ≈3.8% by eliminating the sneak current in the cross-point array during the inference process.

Retinal microvasculature and vasoreactivity changes in hypertension using optical coherence tomography-angiography.

PURPOSE: To evaluate the retinal vasculature and vasoreactivity of patients with hypertension (HTN) using spectral domain optical coherence tomography angiography (SD-OCTA). METHODS: Patients with and without a diagnosis of HTN were included in this cross-sectional observational study. All eyes were imaged with SD-OCTA using 3 mm × 3 mm and 6 mm × 6 mm centered on both the fovea and optic disk. A second 6 mm × 6 mm scan was taken after a 30 s breath-hold. Vessel density (VD), vessel skeletonized density (VSD), and fractal dimension (FD) were calculated using customized MATLAB scripts. Vessel diameter index (VDI) was obtained by taking the ratio of VD to VSD. Vasoreactivity was measured by subtracting the VD or VSD before and after breath-hold (∆VD, ∆VSD). RESULTS: Twenty-three eyes with HTN (17 patients) and 17 control eyes (15 patients) were included. In the 6 mm × 6 mm angiogram centered on fovea, the superficial capillary plexus (SCP) VD (ß = - 0.029, p = 0.012), VSD (ß = - 0.004, p = 0.043) and the choriocapillaris VD (ß = - 0.021, p = 0.030) were significantly decreased in HTN compared to control eyes. Similarly, FD was decreased in both the SCP (ß = - 0.012, p = 0.013) and choriocapillaris (ß = - 0.009, p = 0.030). In the 3 mm × 3 mm angiogram centered on optic disk, SCP VDI (ß = - 0.364, p = 0.034) was decreased. ∆VD and ∆VSD were both reduced in the DCP (ß = - 0.034, p = 0.032; ß = - 0.013, p = 0.043) and ∆VSD was elevated in the choriocapillaris of HTN eyes (ß = 0.004, p = 0.032). CONCLUSIONS: The study used SD-OCTA to show significant differences in the retinal vasculature of hypertensive patients. It was also the first to demonstrate the potential of OCT-A to investigate retinal vascular reactivity in patients with HTN.

Polymer link breakage of polyimide-film-surface using hydrolysis reaction accelerator for enhancing chemical-mechanical-planarization polishing-rate.

In this study, the chemical decomposition of a polyimide-film (i.e., a PI-film)-surface into a soft-film-surface containing negatively charged pyromellitic dianhydride (PMDA) and neutral 4,4'-oxydianiline (ODA) was successfully performed. The chemical decomposition was conducted by designing the slurry containing 350 nm colloidal silica abrasive and small molecules with amine functional groups (i.e., ethylenediamine: EDA) for chemical-mechanical planarization (CMP). This chemical decomposition was performed through two types of hydrolysis reactions, that is, a hydrolysis reaction between OH- ions or R-NH3+ (i.e., EDA with a positively charged amine groups) and oxygen atoms covalently bonded with pyromellitimide on the PI-film-surface. In particular, the degree of slurry adsorption of the PI-film-surface was determined by the EDA concentration in the slurry because of the presence of R-NH3+, that is, a higher EDA concentration resulted in a higher degree of slurry adsorption. In addition, during CMP, the chemical decomposition degree of the PI-film-surface was principally determined by the EDA concentration; that is, the degree of chemical composition was increased noticeably and linearly with the EDA concentration. Thus, the polishing-rate of the PI-film-surface increased notably with the EDA concentration in the CMP slurry.

Surface Transformation of Spin-on-Carbon Film via Forming Carbon Iron Complex for Remarkably Enhanced Polishing Rate.

To scale down semiconductor devices to a size less than the design rule of 10 nm, lithography using a carbon polymer hard-mask was applied, e.g., spin-on-carbon (SOC) film. Spin coating of the SOC film produces a high surface topography induced by pattern density, requiring chemical-mechanical planarization (CMP) for removing such high surface topography. To achieve a relatively high polishing rate of the SOC film surface, the CMP principally requires a carbon-carbon (C-C) bond breakage on the SOC film surface. A new design of CMP slurry evidently accomplished C-C bond breakage via transformation from a hard surface with strong C-C covalent bonds into a soft surface with a metal carbon complex (i.e., C=Fe=C bonds) during CMP, resulting in a remarkable increase in the rate of the SOC film surface transformation with an increase in ferric catalyst concentration. However, this surface transformation on the SOC film surface resulted in a noticeable increase in the absorption degree (i.e., hydrophilicity) of the SOC film CMP slurry on the polished SOC film surface during CMP. The polishing rate of the SOC film surface decreased notably with increasing ferric catalyst concentration. Therefore, the maximum polishing rate of the SOC film surface (i.e., 272.3 nm/min) could be achieved with a specific ferric catalyst concentration (0.05 wt%), which was around seven times higher than the me-chanical-only CMP.