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Enormous amounts of data are generated and analyzed in the latest semiconductor industry. Established yield prediction studies have dealt with one type of data or a dataset from one procedure. However, semiconductor device fabrication comprises hundreds of processes, and various factors affect device yields. This challenge is addressed in this study by using an expandable input data-based framework to include divergent factors in the prediction and by adapting explainable artificial intelligence (XAI), which utilizes model interpretation to modify fabrication conditions. After preprocessing the data, the procedure of optimizing and comparing several machine learning models is followed to select the best performing model for the dataset, which is a random forest (RF) regression with a root mean square error (RMSE) value of 0.648. The prediction results enhance production management, and the explanations of the model deepen the understanding of yield-related factors with Shapley additive explanation (SHAP) values. This work provides evidence with an empirical case study of device production data. The framework improves prediction accuracy, and the relationships between yield and features are illustrated with the SHAP value. The proposed approach can potentially analyze expandable fields of fabrication conditions to interpret multifaceted semiconductor manufacturing.

We demonstrated the way to improve the characteristics of quantum dot light emitting diodes (QD-LEDs) by adding a simple step to the conventional fabrication process. For instance, we can effectively deactivate the surface defects of quantum dot (QD) (e.g., CdSe/ZnS core-shell QDs in the current work) with the SiO bonds by simply mixing QDs with hexamethyldisilazane (HMDS) under atmospheric conditions. We observed the substantial improvement of device characteristics such that the current efficiency, the maximum luminance, and the QD lifetime were improved by 1.7–1.8 times, 15–18%, and nine times, respectively, by employing this process. Based on the experimental data (e.g., energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS)), we estimated that the growth of the SiOx on the surface of QDs is self-limited: the SiOx are effective to passivate the surface defects of QDs without deteriorating the intrinsic properties including the color-purity of QDs. Second, we proposed that the emission profiling study can lead us to the fundamental understanding of charge flow in each layer of QD-LEDs. Interestingly enough, many problems related to the charge-imbalance phenomenon were simply solved by selecting the combination of thicknesses of the hole transport layer (HTL) and the electron transport layer (ETL).

A catalytic combustible type single-chip micro gas sensor was fabricated by MEMS technology and responses with input powers and methane and hydrogen gas concentrations were characterized. The ranges of responses at Pt thickness of 450 nm and input power of 128 mW were 1.076–2.433 mV for methane concentrations of 2315–5787 ppm, and 0.965–2.514 mV for hydrogen concentrations of 282–706 ppm, respectively. The ranges of responses at Pt thickness of 150 nm and input power of 112 mW were 0.192–0.438 mV for methane concentrations of 2315–5787 ppm and 0.949 mV to 2.496 ppm for hydrogen concentrations of 282–706 ppm, respectively. The responses to H2 concentration ratios were 3.65 mV/103 ppm for a micro gas sensor with a 450 nm thick heater and 3.81 mV/103 ppm for a micro gas sensor with a 150 nm thick heater. But in the case of methane gas response, the response to concentration ratios of the micro gas sensor using the 150 nm thick Pt heater was remarkably different from the case of the 450 nm thick Pt heater. The ratios for CH4 were 3.51 mV/104 ppm for the micro gas sensor with a 450 nm thick heater and 0.6 mV/104 ppm for the micro gas sensor with a 150 nm thick heater, respectively. From these results, the micro gas sensor that has the thicker heater with a thickness of 450 nm showed higher sensitivity to methane gas than the micro gas sensor with a thinner heater with a thickness of 150 nm.

Here, we propose a novel DNA-based doping method on MoS 2 and WSe 2 films, which enables ultra-low n- and p-doping control and allows for proper adjustments in device performance. This is achieved by selecting and/or combining different types of divalent metal and trivalent lanthanide (Ln) ions on DNA nanostructures, using the newly proposed concept of Co-DNA (DNA functionalized by both divalent metal and trivalent Ln ions). The available n-doping range on the MoS 2 by Ln-DNA is between 6 × 10 9 and 2.6 × 10 10  cm −2 . The p-doping change on WSe 2 by Ln-DNA is adjusted between −1.0 × 10 10 and −2.4 × 10 10  cm −2 . In Eu 3+ or Gd 3+ -Co-DNA doping, a light p-doping is observed on MoS 2 and WSe 2 (~10 10  cm −2 ). However, in the devices doped by Tb 3+ or Er 3+ -Co-DNA, a light n-doping (~10 10  cm −2 ) occurs. A significant increase in on-current is also observed on the MoS 2 and WSe 2 devices, which are, respectively, doped by Tb 3+ - and Gd 3+ -Co-DNA, due to the reduction of effective barrier heights by the doping. In terms of optoelectronic device performance, the Tb 3+ or Er 3+ -Co-DNA (n-doping) and the Eu 3+ or Gd 3+ -Co-DNA (p-doping) improve the MoS 2 and WSe 2 photodetectors, respectively. We also show an excellent absorbing property by Tb 3+ ions on the TMD photodetectors.

For keeping the safety of compressed natural gas-powered buses (CNG, CH 4 ), a small sized and low power consumption gas sensor is needed for the fuel leakage alarm system. So catalytic combustible micro gas sensors were designed and fabricated by microelectromechanical systems (MEMS) technology and the sensors were measured output voltage potential of the sensor circuit as sensitivities to methane. The sensor was consisted of a sensing platform and a compensation platform, and the length and width of the fabricated platform were 3 mm by 3 mm. The output voltage of a fabricated micro sensor were 0.727 mV, 0.548 mV, 0.45 mV, and 0.29 mV at methane concentrations of 4,630 ppm, 3,473 ppm, 2,315 ppm, and 1,158 ppm respectively, at the input power of 104 mW. Fabricated micro gas sensors could be operated at low power consumption and showed good selectivity. For further study, the long-term stability of micro sensors will be done before applying to CNG powered buses.

One of the main goals of DNA nanotechnology is to provide a viable solution to the limitations of top-down approaches in microfabrication schemes. Although a completely practical bottom-up approach is yet to be realized, there has been great progress in integrating the two approaches in the past few years. In this vein, we present a novel surface assisted fabrication scheme able to directly control the coverage rate, from 0 to 100%, of functionalized DNA nanostructures on centimeter-scaled silica (SiO_2) substrates which is one key to harnessing DNA's unique properties in electronics and photonics. Furthermore, electrostatic interactions between the DNA structures and the surface lead to dramatic topological changes of the structures, creating novel formations of the crystals. These results provide a direct route to applying fully functionalized layers of DNA nanostructures to current technologies in SiO_2-based electronics and photonics.

Modular construction is an innovative new construction method that minimizes waste and improves efficiency within the construction industry. However, practitioners are hampered by the lack of environmental and economic sustainability analysis methods in this area. This study analyzes the embodied carbon emissions and direct construction costs incurred during the production phase of a modular residential building and provides comparison to an equivalent conventional residential building. Major drawings and design details for a modular residential building in South Korea were obtained, and the quantity take-off data for the major construction materials were analyzed for a modular construction method and a conventional construction method using a reinforced concrete structure under the same conditions. Focusing on major construction materials during the production phase, the embodied carbon emissions assessment revealed that adopting a modular construction approach reduced the environmental impact by approximately 36%, as compared to the conventional reinforced concrete method. However, in terms of the direct construction cost, the modular construction was approximately 8% more expensive than the conventional reinforced concrete construction method.

Autism spectrum disorders (ASDs) are four times more common in males than in females, but the underlying mechanisms are poorly understood. We characterized sexually dimorphic changes in mice carrying a heterozygous mutation in Chd8 (Chd8+/N2373K) that was first identified in human CHD8 (Asn2373LysfsX2), a strong ASD-risk gene that encodes a chromatin remodeler. Notably, although male mutant mice displayed a range of abnormal behaviors during pup, juvenile, and adult stages, including enhanced mother-seeking ultrasonic vocalization, enhanced attachment to reunited mothers, and isolation-induced self-grooming, their female counterparts do not. This behavioral divergence was associated with sexually dimorphic changes in neuronal activity, synaptic transmission, and transcriptomic profiles. Specifically, female mice displayed suppressed baseline neuronal excitation, enhanced inhibitory synaptic transmission and neuronal firing, and increased expression of genes associated with extracellular vesicles and the extracellular matrix. Our results suggest that a human CHD8 mutation leads to sexually dimorphic changes ranging from transcription to behavior in mice.

Papillary thyroid carcinoma (PTC) is generally associated with favorable outcomes; however, intermediate-risk requires further evaluation. We therefore examined risk factors for posttreatment recurrence in patients with intermediate-risk PTC. This study involved 1782 patients who underwent thyroidectomy for intermediate-risk PTC. Univariate and multivariate Cox proportional hazard regression analyses were used to identify the significant factors predictive of posttreatment recurrence-free survival (RFS). Of intermediate-risk factors, univariate analyses showed that clinical and pathological cervical lymph node (LN) positivity (cN1 and pN1), aggressive histology, and multifocality with microscopic extrathyroidal extension were significantly associated with RFS outcomes (all P < 0.05). In multivariate analyses, cN1, >5 pN1, and posttreatment radioactive iodine (RAI)-avid metastatic foci of intermediate risk remained the independent factors predictive of RFS (all P < 0.05). The combination of any three or more of these intermediate-risk factors appeared to increase the posttreatment recurrence rate. Clinical nodal positivity, the number of positive LNs, and the presence of RAI-avid metastatic foci in the ATA intermediate-risk category might independently decrease RFS in patients with intermediate-risk PTC. •Microscopic ETE, multifocality with ETE, cN1, >5 pN1, lymphovascular invasion, RAI-avid foci, and aggressive histology were intermediate-risk factors.•cN1, >5 pN1, RAI-avid foci, aggressive histology, and multifocality w/ETE were associated with RFS.•cN1, >5 pN1, and RAI-avid metastatic foci remained independent factors for RFS.•Any three or more combined intermediate-risk factors significantly decreased RFS. This study evaluated risk factors for posttreatment recurrence in 1782 patients with intermediate-risk papillary thyroid carcinoma. Multivariate analyses determined clinical nodal positivity, >5 positive lymph nodes, and the presence of posttreatment radioactive iodine-avid metastatic foci in the ATA intermediate-risk category to be independent factors predictive of recurrence-free survival.