Odor is a type of sensory pollution that can stimulate the human sense of smell when it occurs, causing discomfort and making it difficult to create a pleasant environment. For this reason, there is a high possibility of complaints regarding odors if odors occur in pigsties near residential properties, and the number of such complaints is also increasing. In addition, odors emanating from pigsties around military installations can cause physical and psychological harm, not only to the soldiers living in these type of facilities but also to the families belonging to military personnel living there as well. Because the concentration of odors varies due to diverse factors such as temperature, humidity, wind direction, wind speed, and interaction between causative materials, predicting odors based on only one factor is not proper or appropriate. Therefore, in this work, we sought to construct models that are based on several regression techniques of machine learning using data collected in field. And we selected and utilized the model that has the highest-accuracy in order to notify and warn residents of odors in advance. In this work, 3672 data items were used to train and test the model. The several machine learning algorithms to build the models are polynomial regression, ridge regression, K-nearest neighbor regression (KNN Regression), and random forest. Comparing the performance of models based on each algorithm, the study found that KNN Regression was the most suitable model, and the result obtained from KNN regression was significant.

Hydrogen is one of the main candidates in replacing fossil fuels in the forthcoming years. However, hydrogen technologies must deal with safety aspects due to the specific sub�stance properties. This study aims to provide an overview on the loss of mechanical properties of cryogenic materials, which may lead to serious consequences, such as fires and explosions. The hydrogen embrittlement of cryogenic steels was investigated through slow strain rate tensile tests (SSRTs) and thermal desorption analyses of electrochemically H-charged specimens. As a prior study to confirm mechanical properties under liquid hydrogen conditions, the amount of diffusive hydrogen that causes hydrogen embrittlement was confirmed after charging hydrogen using an electrochemical method for 4 types of steel materials applied as cryogenic materials did. When exposed to the same hydrogen charging conditions, the amount of hydrogen diffused into the 9% nickel steel is the highest compared to the austenitic steel type. It is considered that this is because the diffusion and integration of hydrogen into the interior is easy. It is necessary to analyze the relationship between hydrogen loading and mechanical properties, and this will be carried out in a follow-up study.

본 연구에서는 비용매 유도 상분리법을 이용하여 폴리에테르이미드 계열의 중공사형 분리막을 제조하였다. 제조 된 중공사막의 모폴로지 조절을 위해 첨가제로는 THF, Ethanol, LiNO3를 사용하였다. 또한 높은 수소분리막의 개발을 위해 모폴로지와 기체투과성능을 특성평가를 통해 방사조건을 최적화하였다. 그 결과 THF의 함량이 증가할수록 수소/이산화탄소 선택도가 증가하였다. 하지만 trade-off 관계로 인하여 투과율은 감소하였다. Ethanol을 첨가하였을 때는 finger-like 구조를 나타냈고, LINO3를 첨가하였을 때 Sponge 구조를 보였다. 특히, PDMS 코팅층을 최적화한 중공사막의 경우, 투과율은 40 GPU, 수소/이산화탄소 선택도는 5.6을 나타냈다.

Due to global warming and environmental pollution, environmental regulations are getting stronger, and the International Maritime Organization announced regulations to reduce CO2 emissions in 2018. In order to respond to this, interest in hydrogen energy is growing, and research on liquid hydrogen is spotlighted for storage and transport of large amounts of hydrogen. Hydrogen reduces in volume to 1/800 when liquefied, but its boiling point is close to absolute zero(-253°C), and hydrogen embrittlement that penetrates other materials and weakens mechanical properties. In this study, the change of mechanical properties under cryogenic conditions (-196 degrees below zero) was confirmed after charging hydrogen into existing cryogenic materials (Stainless steel, High Manganese steel, 9% Nickel steel). In Part I, hydrogen was charged using an electrochemical method and quantitative evaluation was performed. In all four materials, as the changing time increased, the diffusible hydrogen concentration increased. After 24 hours charging, the hydrogen loading of 20 wppm in 9% Ni steel and 15 wppm in high-Mn steel was confirmed. In a follow-up study, we plan to study the effect of hydrogen charging by comparing the results of the mechanical properties test with the above results.

The adsorption of molecular hydrogen on the monolayer graphene sheet under varied temperature and pressure was studied using molecular dynamics simulations (MDS). A novel method for obtaining potential energy distributions (PEDs) of systems was developed to estimate the gravimetric density or weight percentage of hydrogen. The Tersoff and Lennard–Jones (LJ) potentials were used to describe interatomic interactions of carbon–carbon atoms in the graphene sheet and the interactions between graphene and hydrogen molecules, respectively. The results estimated by the use of novel method in conjunction with MDS developed herein were found to be in excellent agreement with the existing experimental results. The effect of pressure and temperature was studied on the adsorption energy and gravimetric density for hydrogen storage. In particular, we focused on hydrogen adsorption on graphene layer considering the respective low temperature and pressure in the range of 77–300 K and 1–10 MPa for gas storage purpose which indicate the combination of optimal extreme conditions. Adsorption isotherms were plotted at 77 K, 100 K, 200 K, and 300 K temperatures and up to 10 MPa pressure. The simulation results indicate that the reduction in temperature and increase in pressure favor the gravimetric density and adsorption energies. At 77 K and 10 MPa, the maximum gravimetric density of 6.71% was observed. Adsorption isotherms were also analyzed using Langmuir, Freundlich, Sips, Toth, and Fritz–Schlunder equations. Error analysis was performed for the determination of isotherm parameters using the sum of the squares of errors (SSE), the hybrid fractional error function (HYBRID), the average relative error (ARE), the Marquardt’s percent standard deviation (MPSD), and the sum of the absolute errors (SAE).

Deuterium is a crucial clean energy source required for nuclear fusion and is a future resource needed in various industries and scientific fields. However, it is not easy to enrich deuterium because the proportion of deuterium in the hydrogen mixture is scarce, at approximately 0.016%. Furthermore, the physical and chemical properties of the hydrogen mixture and deuterium are very similar. Therefore, the efficient separation of deuterium from hydrogen mixtures is often a significant challenge when using modern separation technologies. Recently, to effectively separate deuterium, studies utilizing the ‘Kinetic Quantum Sieving Effect (KQS)’ of porous materials are increasing. Therefore, in this review, two different strategies have been discussed for improving KQS efficiency for hydrogen isotope separation performance using nanoporous materials. One is the gating effect, which precisely controls the aperture locally by adjusting the temperature and pressure. The second is the breathing phenomenon, utilizing the volume change of the structure from closed system to open system. It has been reported that efficient hydrogen isotope separation is possible using these two methods, and each of these effects is described in detail in this review. In addition, a specific-isotope responsive system (e.g., 2nd breathing effect in MIL-53) has recently been discovered and is described here as well.

Ni–Cr–Al metal-foam-supported catalysts for steam methane reforming (SMR) are manufactured by applying a catalytic Ni/Al2O3 sol–gel coating to powder alloyed metallic foam. The structure, microstructure, mechanical stability, and hydrogen yield efficiency of the obtained catalysts are evaluated. The structural and microstructural characteristics show that the catalyst is well coated on the open-pore Ni–Cr–Al foam without cracks or spallation. The measured compressive yield strengths are 2–3 MPa at room temperature and 1.5–2.2 MPa at 750oC regardless of sample size. The specimens exhibit a weight loss of up to 9–10% at elevated temperature owing to the spallation of the Ni/Al2O3 catalyst. However, the metal-foam-supported catalyst appears to have higher mechanical stability than ceramic pellet catalysts. In SMR simulations tests, a methane conversion ratio of up to 96% is obtained with a high hydrogen yield efficiency of 82%.

Two lab-scale trickle-bed type biofilters with a single fungal species (Aspergillus fumigatus, Acidomyces acidophilus, respectively) have been studied to investigate the simultaneous removal of inorganic (hydrogen sulfide) and organic (butyl acetate) compounds. The biofilter with Aspergillus fumigatus treated simultaneously two different compounds with removal capacity of 1,511 mgS/m3/hr and 6,324 mgC/m3/hr; and the biofilter inoculated with Acidomyces acidophilus had the removal capacity of 1,254 mgS/m3/hr and 6,045 mgC/m3/hr. Stable operational performance was observed in both biofilters under an acidic condition of pH 2 to 4. Based on pseudo-first-order removal rates as a function of depth in the biofilter, Aspergillus fumigatus showed a twice faster rate of hydrogen sulfide removal than Acidomyces acidophilus, 15.9% (Aspergillus fumigatus) and 17.9% (Acidomyces acidophilus) of total sulfur removed were oxidized to produce sulfates, and 77.8% (Aspergillus fumigatus) and 79.4% (Acidomyces acidophilus) were accumulated in the form of S0 through the bed in both biofilters, respectively.