Quantum scale biomimicry of low dimensional growth: An unusual complex amorphous precursor route to TiO2 band confinement by shape adaptive biopolymer-like flexibility for energy applications

Crystallization via an amorphous pathway is often preferred by biologically driven processes enabling living species to better regulate activation energies to crystal formation that are intrinsically linked to shape and size of dynamically evolving morphologies. Templated ordering of 3-dimensional space around amorphous embedded non-equilibrium phases at heterogeneous polymer-metal interfaces signify important routes for the genesis of low-dimensional materials under stress-induced polymer confinement. We report the surface induced catalytic loss of P=O ligands to bond activated aromatization of C-C C=C and Ti=N resulting in confinement of porphyrin-TiO(2 )within polymer nanocages via particle attachment. Restricted growth nucleation of TiO2 to the quantum scale (˂= 2 nm) is synthetically assisted by nitrogen, phosphine and hydrocarbon polymer chemistry via self-assembly. Here, the amorphous arrest phase of TiO, is reminiscent of biogenic amorphous crystal growth patterns and polymer coordination has both a chemical and biomimetic significance arising from quantum scale confinement which is atomically challenging. The relative ease in adaptability of non-equilibrium phases renders host structures more shape compliant to congruent guests increasing the possibility of geometrical confinement. Here, we provide evidence for synthetic biomimicry akin to bio-polymerization mechanisms to steer disorder-to-order transitions via solvent plasticization-like behaviour. This challenges the rationale of quantum driven confinement processes by conventional processes. Further, we show the change in optoelectronic properties under quantum confinement is intrinsically related to size that affects their optical absorption band energy range in DSSC.This work was supported by the National Research Foundation of Korea (NRF) grant funded by Korea government (MEST) NRF-2012R1A1A2008196, NRF 2012R1A2A2A01047189, NRF 2017R1A2B4008801, 2016R1D1A1A02936936, (NRF-2018R1A4A1059976, NRF-2018R1A2A1A13078704) and NRF Basic Research Programme in Science and Engineering by the Ministry of Education (No. 2017R1D1A1B03036226) and by the INDO-KOREA JNC program of the National Research Foundation of Korea Grant No. 2017K1A3A1A68. We thank BMSI (A*STAR) and NSCC for support. SJF is funded by grant IAF25 PPH17/01/a0/009 funded by A* STAR/NRF/EDB. CSV is the founder of a spinoff biotech Sinopsee Therapeutics. The current work has no conflicting interests with the company. We would like to express our very great appreciation to Ms. Hyoseon Kim for her technical expertise during HRTEM imaging

Multimedia distributions, bioaccumulation, and trophic transfer of microcystins in the Geum River Estuary, Korea: Application of compound-specific isotope analysis of amino acids

To determine distributions, bioaccumulation, and trophic transfer of freshwater cyanobacterial toxins such as microcystins (MCs), surface water, suspended solids, sediments, and coastal organisms were collected from seven stations in inner and outer regions of the estuary dam in the Geum River Estuary in June and July 2017. Concentrations of MC variants (MC-LR, -RR, and -YR) in the multimedia samples were analyzed using a HPLCMS/MS. Trophic position (TP) of organisms (fish, bivalve, gastropod, decapod, and polychaete) was determined by nitrogen stable isotope analyses of both bulk tissues and amino acids. From July to August 2017, great concentrations of MCs were detected in discharged freshwater ranging from 0.4 to 75 mu g L-1. Considerable amounts of MCs are delivered to the Geum River Estuary in summer season. MCs spread far away as dissolved phases (18.7-49.5 mu g L-1) in July when large amount of freshwater was discharged during the rainy season. Concentrations of MCs in marine organisms varied among species, ranging from 40 to 870 mu g g(-1) dw. Bioaccumulated MCs tend to decrease with increasing TP of organisms, suggesting that MCs are biodiluted through the marine food web. Compound-specific isotope analysis (nitrogen of amino acids) provides more reliable TPs compared with those by bulk isotope analysis in a closed estuary (such as the Geum River Estuary) with large fluctuations in the isotope ratio of primary producers.This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) (No. NRF-2016R1E1A1A01943004 & No. 2017R1A4A1015393)

LDA-Based Model for Defect Management in Residential Buildings

This study systematically analyzes various defect patterns that occur during the warranty period of residential buildings using the loss distribution approach (LDA). This paper examines 16,108 defects from 133 residential buildings where defect disputes occurred between 2008 and 2018 in South Korea. The analysis results showed that the defect losses were relatively high in reinforcement concrete (RC) work (3/5/10 years), waterproof work (5 years), and finish work (2 years). It is shown that RC work has a high frequency of defects, such as cracks in concrete in public spaces affected by external factors. In addition, it was analyzed that the type of defect needed high repair cost because the area where the defect—such as incorrect installation and missing task—occurred, needed construction again. According to the level of frequency and severity, losses were divided within four zones to provide detailed strategies (by period). This will effectively contribute to minimizing unnecessary losses from defects as quantifying the losses of defects.This research was supported by a grant (19CTAP-C152020-01) from Technology Advancement Research Program (TARP) funded by Ministry of Land, Infrastructure and Transport of Korean government

Graphical Model to Diagnose Product Defects with Partially Shuffled Equipment Data

The diagnosis of product defects is an important task in manufacturing, and machine learning-based approaches have attracted interest from both the industry and academia. A high-quality dataset is necessary to develop a machine learning model, but the manufacturing industry faces several data-collection issues including partially shuffled data, which arises when a product ID is not perfectly inferred and yields an unstable machine learning model. This paper introduces latent variables to formulate a supervised learning model that addresses the problem of partially shuffled data. The experimental results show that our graphical model deals with the shuffling of product order and can detect a defective product far more effectively than a model that ignores shuffling.This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2019R1A2C1088255)

Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process

This study aimed at developing SBPCI (Sidewalk Block Pavement Condition Index) with sidewalk pavement condition survey data of Seoul city in order to attain a quantitative evaluation method of sidewalk pavement condition. The distress patterns of sidewalk pavement were classified into four groups of Crack/Loss, Roughness, Aging, and Corner Break. AHP (Analytic Hierarchy Process) technique was employed on the basis of the raking process of 31 pavement managers in order to analyze the influence of the distress patterns on the sidewalk pavement condition. The AHP analysis result indicated the weight of pop out, roughness, surface abrasion, and corner break were 0.521, 0.244, 0.164, and 0.070, respectively, by distress type. A model equation was derived by using the sidewalk pavement condition data from 420 sections. The correlation analysis between the result of the model equation and distress type revealed that the correlation of corner break was low to be excluded from SBPCI model; while pop out, roughness, and surface abrasion were statistically significant to be used as three variables of the developed SBPCI model

A Graphical Model to Diagnose Product Defects with Partially Shuffled Equipment Data

The diagnosis of product defects is an important task in manufacturing, and machine learning-based approaches have attracted interest from both the industry and academia. A high-quality dataset is necessary to develop a machine learning model, but the manufacturing industry faces several data-collection issues including partially shuffled data, which arises when a product ID is not perfectly inferred and yields an unstable machine learning model. This paper introduces latent variables to formulate a supervised learning model that addresses the problem of partially shuffled data. The experimental results show that our graphical model deals with the shuffling of product order and can detect a defective product far more effectively than a model that ignores shuffling.This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2019R1A2C1088255)

Organophosphate esters in indoor dust from 12 countries: Concentrations, composition profiles, and human exposure

A total of 20 organophosphate triesters (OPEs), including seven alkyl-OPEs, three chlorinated (Cl)-OPEs, seven aryl-OPEs, and three oligomeric-OPEs were measured in 341 house dust samples collected from 12 countries during the period 2010-2014. OPEs were ubiquitous in indoor dust, and the total concentrations of OPEs (Sigma OPEs; sum of 20 OPEs) ranged from 49.4 to 249,000 ng/g dry weight (dw). Generally, Cl-OPEs were the predominant compounds (51% of total) in indoor dust samples, with a median concentration of 800 ng/g, followed by alkyl-OPEs (31%), aryl-OPEs (17%), and oligomeric-OPEs (1%), with median concentrations of 480, 270, and 21.9 ng/g, respectively. Sigma OPE concentrations in indoor dust from more industrialized countries (South Korea: median, 31,300; Japan: 29,800; and the United States: 26,500 ng/g dw) were one or two orders of magnitude higher than those from less industrialized countries (Greece: 7140, Saudi Arabia: 5310, Kuwait: 4420, Romania: 4110, Vietnam: 1190, China: 1120, Colombia: 374, India: 276, and Pakistan: 138 ng/g dw). Statistically significant positive correlations (0.114 < r < 0.748, p < 0.05) were found among the concentrations of 16 OPEs in dust samples, indicating similar sources of these compounds. The median estimated daily intakes of Sigma OPEs via dust ingestion for children and adults were in the ranges of 0.29-64.8 and 0.07-14.9 ng/kg bw/day, respectively

Temporal variation in riverine organic carbon concentrations and fluxes in two contrasting estuary systems: Geum and Seomjin, South Korea

In this study, surface water samples were collected at sites located in the lowest reaches of closed (Geum) (i.e. with an estuary dam at the river mouth) and open (Seomjin) estuary systems between May 2016 and May 2018. We analyzed concentrations and stable isotopes of particulate organic carbon (POC) and dissolved organic carbon (DOC) to assess OC sources, to estimate fluxes of riverine OC, and to assess some of the factors driving OC exports in these two contrasting Korean estuary systems. Our geochemical results suggest that the contribution of the phytoplankton-derived POC to the total POC pool was larger in the Geum River than in the Seomjin River. Notably, a heavy riverine algae bloom occurred in the Geum River in August 2016, resulting in a high carbon isotopic composition (-19.4%) together with low POC/PN ratio (˂ 10) and POC/Chl-a ratio (˂ 100). In contrast, potential DOC sources in both the Geum River and the Seomjin River were a mixture of C3-derived forest soils and cropland organic matter. During the study period, the catchment area-normalized fluxes of POC and DOC were 0.40x10(-3) tC/km(2)/yr and 6.5x10(-2) tC/km(2)/yr in the Geum River and 5.2x10(-4) tC/km(2)/yr and 8.6x10(-4) tC/km(2)/yr in the Seomjin River, respectively. It appears that the POC flux was more weakly associated with the water discharge in the Geum River than in the Seomjin River, but the DOC fluxes were in general controlled by the water discharges in both rivers. Accordingly, the estuary dam of the Geum River might be one of the most strongly influencing factors on seasonal patterns in POC fluxes into the adjacent coastal seas, strongly modifying water residence times and thus biogeochemical processes.We would like to thank Dokyun Kim, Ji Hwan Hwang, Jong-Ku Gal, Dong-Hun Lee, Dahae Kim, and Solbin Kim for their assistance during fieldwork. This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Ministry of Science and ICT (MSIT) -South Korea [NRF-2016R1A2B3015388, KOPRI-PN19100]

Design of a New Bilayer Multipole Electromagnetic Brake System for a Haptic Interface

This paper deals with the design, simulation and experimental verification of a new bilayer multipole electromagnetic brake. The design utilizes the superposition principle of magnetic flux across the inner and outer layers of axially-oriented electromagnetic poles to provide gradual braking about the single axis of rotation. The braking principle exploits the Coulomb friction between the two rigid contact surfaces. Compared with conventional, multi-pole, multi-layer type radial brakes in haptic applications, the proposed design provides high fidelity of free motion through an absolutely disconnected rotor. The design also provides a wide operating range by delaying the saturation limit of a magnetic circuit for a wide range of input power. In this paper, the analytical model of the brake is derived and compared with the FEM-based simulation results. The optimal design obtained from multi-objective optimization was experimentally verified for its capability in haptic applications.This work was supported by the Technology Innovation Program (or Industrial Strategic Technology Development Program-Artificial intelligence bio-robot medical convergence project) (20001257, Artificial intelligence algorithm based vascular intervention robot system for reducing radiation exposure and achieving 0.5 mm accuracy)—funded by the Ministry of Trade, Industry and Energy(MOTIE, Korea), the Ministry of Health and Welfare(MOHW), the Ministry of Science and ICT (MSIT) and the Korean Evaluation Institute of Industrial Technology (KEIT); the Technology Innovation Program (10052980, Development of micro-robotic system for surgical treatment of chronic total occlusion)—funded by the Ministry of Trade, Industry and Energy (MI, Korea); and the WC300 R&D Program (S2482672)—funded by the Small and Medium Business Administration (SMBA, KOREA)

A Luminance Compensation Method Using Optical Sensors with Optimized Memory Size for High Image Quality AMOLED Displays

This paper proposes a luminance compensation method using optical sensors to achieve high luminance uniformity of active matrix organic light-emitting diode (AMOLED) displays. The proposed method compensates for the non-uniformity of luminance by capturing the luminance of entire pixels and extracting the characteristic parameters. Data modulation using the extracted characteristic parameters is performed to improve luminance uniformity. In addition, memory size is optimized by selecting an optimal bit depth of the extracted characteristic parameters according to the trade-off between the required memory size and luminance uniformity. To verify the proposed compensation method with the optimized memory size, a 40-inch 1920x1080 AMOLED display with a target maximum luminance of 350 cd/m(2) is used. The proposed compensation method considering a 4cr range of luminance reduces luminance error from +/- 38.64%, +/- 36.32%, and +/- 43.12% to +/- 2.68%, +/- 2.64%, and +/- 2.76% for red, green, and blue colors, respectively. The optimal bit depth of each characteristic parameter is 6-bit and the total required memory size to achieve high luminance uniformity is 74.6 Mbits