Main Processes Research Articles

The formation and adsorption mechanism studies of 3D hydrangea-like ZnFe-LDHs/FeOOH for the highly efficient removal of phosphate

Phosphate in water can cause a series of problems such as overgrowth of algae and other aquatic organisms, foul-smelling, turbid water and lower dissolved oxygen concentrations, thereby posing a serious threat to human health and environment. To efficiently remove phosphate from water, three-dimensional hydrangea-like ZnFe-layered double hydroxides/FeOOH composites (3D hydrangea-like ZnFe-LDHs/FeOOH) were designed and prepared by a facile urea hydrothermal method. The maximum adsorption capacity of phosphate by 3D hydrangea-like ZnFe-LDHs/FeOOH reached about 200 mg·g−1, much higher than that of ZnFe-LDHs prepared by co-precipitation method (53 mg·g−1) and other reported adsorbents, which confirmed that 3D morphology contributed to the improvement of adsorption capacity. Time-dependent experiments were designed to explore the formation mechanism of 3D hydrangea-like structure and the results indicated directional aggregation and epitaxial growth were two main processes. Batch experiments were conducted to investigate adsorption behavior of phosphate. The adsorption kinetics and isotherms showed that the adsorption process followed the quasi-first-order kinetics and Langmuir model. Besides, 3D hydrangea-like ZnFe-LDHs/FeOOH could be regenerated effectively and recycled at least three times. 3D hydrangea-like ZnFe-LDHs/FeOOH possessed fascinating performance in phosphate removal from real river samples and laundry detergent samples, with the removal rates of 66–100 % and 80–100 %, respectively. Furthermore, 3D hydrangea-like ZnFe-LDHs showed good adsorption performance towards other anionic dyes, including Congo Red and Orange Yellow II, with the maximum adsorption capacity of 867 mg·g−1 and 225 mg·g−1, indicating its widespread applicability. The adsorption mechanism of phosphate by 3D hydrangea-like ZnFe-LDHs was furtherly investigated, mainly containing metal coordination, anion exchange between layers and electrostatic interactions.

Performance analysis and optimization of a solar assisted heat pump-driven vacuum membrane distillation system for liquid desiccant regeneration

Liquid desiccant air-conditioning (LDAC) system is one of the excellent alternatives to conventional vapor compression refrigeration system due to its great energy-saving potential. However, regeneration of diluted liquid desiccant is the main energy-consuming process, and its performance plays a significant role in LDAC system. Recently vacuum membrane distillation (VMD) is becoming an emerging and promising separation process rely on the advantage of high permeate flux and low energy losses. The interest of usage solar energy techniques for feed solution heating in VMD systems is regarded as a sustainable path for membrane distillation process. In this work, a solar-driven VMD system incorporating a vapor-compression heat pump for liquid desiccant regeneration is introduced. An adapted solar/heat pump hybrid heating strategy has been devised to establish a connection between the heat-demanding process and the solar thermal supply. A comprehensive multicriteria assessment of energy, exergy, and environmental evaluation is conducted, and the influences of crucial parameters on both key components and system performance are evaluated to ensure a systematic examination. Results show that both the COP and STEC decrease obviously with the growth of the inlet solution temperature, whereas SEEC is improved abviously from 410.6 kW·h/m3 to 566.1 kW·h/m3 due to the effect of heat pump. The exergy analysis indicates that exergy losses in solar collector and stratified heat storage tank accounted for over 80 % of the total exergy losses. Additionally, single-objective optimization and multi-objective optimization are employed to explore the optimum operating conditions of key componets and whole system. Results show the ideal optimal solution can be obtained with a COP of 19.92 and a SEEC of 142.89 kW·h/m3 when the weights of COP and SEEC are taken as [0.5, 0.5].

Structural investigation and thermal properties of Al2O3-PbO-B2O3 glasses

Two series of aluminum lead borate glasses, (Al2O3)y(PbO)35-y(B2O3)65 and (Al2O3)y(PbO)70-y(B2O3)30, were prepared and effect of PbO → Al2O3 substitution on their structure and thermal properties was studied. The semi-quantitative analysis of the Raman spectroscopy data was used to structural interpretation of glass transition behavior in the Al2O3-doped lead borate glasses. The mechanisms of structural reorganization of glassy network under PbO → Al2O3 substitution were found to differ for the studied series although Al3+ ions are incorporated in the glass network, mainly, in form of AlO4 units in the both cases. The formation of AlO4 tetrahedra is accompanied by transformation of various isolated borate anions into finite-sized metaborate chains as well as the conversion of four-fold coordinated [BØ3O−]− species with one non-bridging oxygen atom into fully polymerized [BØ4]− tetrahedra in the (Al2O3)y(PbO)70-y(B2O3)30 glasses. In the series of glasses with high concentration of B2O3, B[4] → B[3] transformation including the shift of [BØ4]− ↔ BØ2O− equilibrium toward the right side is the main process of structural reorganization caused by PbO → Al2O3 substitution. In this case, the change in the network connectivity is determined by competition between increasing the amount of Al-O-B bonds against the background of decreasing the amount of B-O-B bonds between borate structural species. In the B-poor series, the glass transition temperature increased with Al2O3 from 280 to 360 °C, and the crystallization peak onset occurs at 340 and 380 °C for the glasses with the 0 and 3 mol.% Al2O3 contents, respectively (higher aluminum oxide contents already prevent crystallization). In the B-rich series, Tg increases with the Al2O3 content from 430 to 490 °C, and the crystallization occurs at 560 °C only for the Al2O3-free glass. The structural relaxation behavior in the glass transition rage was described in terms of the Tool-Narayanaswamy-Moynihan model. The activation energy for the relaxation movements was found to be non-monotonous in case of both compositional series.

Carbon sequestration in the subsoil and the time required to stabilize carbon for climate change mitigation.

Soils store large quantities of carbon in the subsoil (below 0.2 m depth) that is generally old and believed to be stabilized over centuries to millennia, which suggests that subsoil carbon sequestration (CS) can be used as a strategy for climate change mitigation. In this article, we review the main biophysical processes that contribute to carbon storage in subsoil and the main mathematical models used to represent these processes. Our guiding objective is to review whether a process understanding of soil carbon movement in the vertical profile can help us to assess carbon storage and persistence at timescales relevant for climate change mitigation. Bioturbation, liquid phase transport, belowground carbon inputs, mineral association, and microbial activity are the main processes contributing to the formation of soil carbon profiles, and these processes are represented in models using the diffusion-advection-reaction paradigm. Based on simulation examples and measurements from carbon and radiocarbon profiles across biomes, we found that advective and diffusive transport may only play a secondary role in the formation of soil carbon profiles. The difference between vertical root inputs and decomposition seems to play a primary role in determining the shape of carbon change with depth. Using the transit time of carbon to assess the timescales of carbon storage of new inputs, we show that only small quantities of new carbon inputs travel through the profile and can be stabilized for time horizons longer than 50 years, implying that activities that promote CS in the subsoil must take into consideration the very small quantities that can be stabilized in the long term.

Analysis of the application of automated systems in mechanical engineering

Introducing off-the-shelf solutions for automated machine-building systems causes some difficulties related to attempts to change the algorithms of process participants, and also to the need to duplicate information transfer chains, as most systems operate autonomously within certain production units. The author proposes a new approach to organizing the interaction of automated systems of machine-building enterprises. Effective implementation of automated systems is possible only based on investigation and optimization of machine-building enterprise activities, and based on analysis and quality assessment of functions performance by participants of different enterprise processes. The method comprises identifying the process for preparing production and output of finished products, and processes of lower levels (auxiliary), but necessary for implementing the main, and functionally related to it. The main functional process defines a time parameter and auxiliary processes accompanying the main process. These auxiliary processes are financial, material, personnel, and organizational support processes. The article contains the basic principles of creating a complex of automated machine-building systems. The article analyzes the role and place of each of the main functional automated systems. The author gives considerations on the sequence of implementation of the project of digitalization of machine-building production.

Information technology: effects of application in the mining industry

The influence of information technology application in the main business processes on direct and indirect effects received by mining enterprises is considered. The purpose of the study was to develop a scientific and technical approach to assess the economic effects of information technology application in the mining industry, based on parametric and scenario modeling of discounted cash flows. The results were the development of a scientific and technical approach and an algorithm for its step-by-step implementation to assess the economic effects of information technology application for a particular enterprise in the mining industry.

Effect of Nutmeg Meal on Microbial Abundance of Biohydrogenation Process, and Fatty Acid Profile of Goat Rumen Fluid In Vitro

This study aimed to evaluate the effect of nutmeg meal as a source of phenol on the abundance of dominant microbes in the biohydrogenation process and the fatty acid profile of goat rumen fluid in vitro. This study used a randomized complete block design with four treatments and three replicates of in vitro batches, each replicate in duplicate. The dietary treatments consisted of elephant grass (40%), soybean meal (10%), with varying proportion of wheat pollard, canola oil and nutmeg meal hence, treatment P0 (40:10:45:5:0); P1 (40:10:40:5:5); P2 (40:10:35:5:15); P3 (40:10:30:5:10). Fermentation using the in vitro gas production method described by Menke and Steinggas with an incubation period of 48 hours. Parameters observed included microbial abundance and fatty acid profile of goat rumen fluid. The statistical analysis showed that adding nutmeg meal starting at the 5% level decreased the abundance of the main biohydrogenation process bacteria anaerovibrio, butyrivibrio fibrisolvens, and pseudobutyrivibrio. Total saturated fatty acid and stearate fatty acid concentrations decreased (P<0.05), while total unsaturated fatty acid, linoleic and oleic acid concentrations increased (P<0.05).

Разработка алгоритма классификации производств по типу внутризаводского кооперирования основных и вспомогательных процессов методом машинного обучения

The task of rational organization of auxiliary processes at the enterprise is to reduce their cost by deep integration into the main production process. The purpose of the article is to develop a classification analysis algorithm for assessing the dependencies between the main and auxiliary units and the typology of production processes according to the level of intra-factory cooperation. As a method for determining the type of production, the Random Forest machine learning method using the bagging machine learning meta-algorithm is proposed. Parameters have been developed that describe the costs of auxiliary operations, the costs of repair facilities and equipment maintenance, the level of technical efficiency of production. Approbation of the algorithm on the example of chemical enterprises made it possible to distinguish three types of production according to the nature of intraplant cooperation of processes according to the most informative parameters. To assess the usefulness and performance of the models, cumulative lift diagrams are constructed, where the most productive type is determined with an average level of intra-factory cooperation. The results are the primary diagnostics of the organization of auxiliary facilities, decision-making on the reengineering of processes in order to strengthen intra-factory cooperation and reduce costs.

Current Situation and Prospect in Urban Sewage Treatment Plants

Sewage is the carrier of resources and energy, which contains great chemical energy and heat energy. The traditional sewage treatment process consumes energy, and the energy consumption is high. Under the background of carbon neutrality, China’s urban sewage treatment plants have achieved carbon neutrality operation in terms of energy self-sufficiency and reduction of greenhouse gas emissions. To explore the feasibility of carbon neutrality in sewage treatment plants, the cases of carbon neutrality in sewage treatment plants at domestic and abroad were analyzed. And the implementation approaches and main emission reduction processes to achieve carbon neutrality were summarized. The technical challenges and research directions of future sewage treatment plants in China from the perspective of carbon neutrality are proposed.

Neurodegeneration in diabetic retinopathy: An insight on its main signalling pathways

Aims/Purpose: In the latest years neurodegeneration has been considered as one of the main pathological processes involved in proliferative diabetic retinopathy's (PDR) onset and progression. We aimed to increase the understanding on the role of the main signalling molecules that participate in this phenomenon, including apoptotic, excitotoxic and neurotrophic factor pathways.Methods: Participants of both sexes were selected and programmed for vitrectomy by its diabetes mellitus 2 (DM2)‐derived vitreoretinal complications (PDR group, PDRG; n = 20), or by suffering macular hole, epiretinal membrane or rhegmatogenous retinal detachment (as the surrogate control group, SCG; n = 26). Vitreous body (VIT) and plasma (PLS) samples were collected and processed to determine the glutamate, caspase‐3 (CAS‐3) and brain‐derived neurotrophic factor (BDNF) levels. Next‐Generation Sequencing (NGS) techniques were applied to characterize the miRNA expression pattern in both groups.Results: Significantly higher VIT glutamate (p < 0.05) and CAS‐3 (p < 0.05), and significantly lower BDNF (p < 0.05) levels were detected in the PDRG. Significantly higher PLS glutamate (p < 0.05) and CAS‐3 (p < 0.05) levels were found in diabetics. However, PLS levels of BDNF showed no differences between groups (p = 0.80). NGS analysis showed a different miRNA expression pattern between both groups.Conclusions: Diabetes‐induced changes in retinal neurons/glia may be the key to discover preclinical biomarkers for better managing diabetic eyes. Glutamate, caspase‐3 and BDNF, playing important roles in the neurodegenerative processes occurring in PDR, are pivotal candidates to identify diabetics at high risk of sight‐threatening complications. Additionally, certain miRNAs could be playing an important role in these signalling pathways, being involved in PDR's neurodegenerative phenomenon.

Udokan hearth of mineral resources: Factors shaping the quality of atmospheric air

The consequences of the impact of mining and ore processing industries on atmospheric air are acutely negative. Polluted atmospheric air entails a significant environmental risk to human health. The identification of factors that negatively affect the air quality of a mining enterprise and nearby territories actualizes the problem under consideration. The object of the study is the territory of the Udokan hearth of mineral resources. The subject of the study is the factors that shape the quality of atmospheric air. The purpose of the study is to analyze the negative effects of the main factors determining the ecological state of atmospheric air in the conditions of the Udokan hearth of mineral resources. The methodological basis of the research is the complex, structural, factual principles and approaches. The work uses general research methods (analysis, synthesis, generalization), as well as private scientific - factor analysis, which is understood as a method of complex and systematic study of the interaction of factors on the magnitude of performance indicators. The main factors shaping the ecological situation of the study area are identified: climatic, qualitative and quantitative indicators of polluting emissions. The necessity of constant monitoring of the state of the atmosphere for the development and implementation of a set of measures to reduce the negative impact of polluting emissions into the atmosphere is justified. Conclusions. The practical uniformity of the chemical composition of harmful emissions during the implementation of the main technological processes of mining and mining processing industries makes it possible to develop preventive measures to minimize the negative consequences of the development of mineral deposits in the mine atmospheric space.

Effect of electroacupuncture on global cerebral ischemia-reperfusion injury in rats: A urine proteome analysis.

This study aimed to investigate dynamic urinary proteome changes of electroacupuncture (EP) on cerebral ischemia-reperfusion (CI/R) injured rats and to explore the therapeutic biological mechanisms of EP. First, changed urinary proteins were found in EP stimulation in healthy rats. Then, we used a CI/R injury rat model induced by Pulsinelli's four-vessel occlusion (4-VO) method to explore the function of EP on urinary proteome in CI/R injury. Urine samples were collected for proteome analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis. In total, 384 proteins were identified, among which 47 proteins (23 upregulated, 24 downregulated) were differentially expressed with 0.6-log FC and p<.05. Gene ontology analysis revealed that the cell redox homeostasis, acute-phase response, response to lipopolysaccharide, and cellular response to glucocorticoid stimulus were significantly enriched. The partially biologically connected differential proteins were found by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis in the EP group. With the CI/R rat model, 80 proteins (27 upregulated, 53 downregulated) were significantly changed in the CI/R rats compared to the controls. Among these differentially expressed proteins (DEPs), 23 proteins (17 upregulated, six downregulated) showed significant changes after EP treatment (0.6-log FC change, p<.05). The main related biological processes were aging, immune response, acute-phase response, liver regeneration, protein catabolic process, and response to oxidative stress. Many metabolic pathways were enriched by KEGG analysis. Our results indicate that the EP could alleviate cerebral damage induced by ischemia-reperfusion through an anti-inflammatory and metabolism regulation mechanism. The urinary proteome might reflect the pathophysiological changes in EP pretreatment in the treatment and prevention of CI/R injury.

Composition dependence of X-ray stability and degradation mechanisms at lead halide perovskite single crystal surfaces.

The multiple applications of lead halide perovskite materials and the extensive use of X-ray based techniques to characterize them highlight a need to understand their stability under X-ray irradiation. Here, we present a study where the X-ray stability of five different lead halide perovskite compositions (MAPbI3, MAPbCl3, MAPbBr3, FAPbBr3, CsPbBr3) was investigated using photoelectron spectroscopy. To exclude effects of thin film formation on the observed degradation behaviors, we studied clean surfaces of single crystals. Different X-ray resistance and degradation mechanisms were observed depending on the crystal composition. Overall, perovskites based on the MA+ cation were found to be less stable than those based on FA+ or Cs+. Metallic lead formed most easily in the chloride perovskite, followed by bromide, and only very little metallic lead formation was observed for MAPbI3. MAPbI3 showed one main degradation process, which was the radiolysis of MAI. Multiple simultaneous degradation processes were identified for the bromide compositions. These processes include ion migration towards the perovskite surface and the formation of volatile and solid products in addition to metallic lead. Lastly, CsBr formed as a solid degradation product on the surface of CsPbBr3.

Контроль качества огнезащитных работ при монтаже (нанесении), ремонте и эксплуатации, прогнозирование срока службы тонкослойных огнезащитных покрытий

Currently, fire-retardant treatment of materials, products and structures is widely used in the construction of industrial facilities. Fire protection technologies are constantly being improved, and the range of fire protection equipment is expanding annually. Due to the fact that the service life of building structures is estimated in tens of years, the question arises about the ability of fire-retardant means to perform tasks to ensure the fire safety of a building (structure) during long-term operation. Considering that there is currently no regulatory document in Russia to determine the service life of fire-retardant coatings, and research in this area is clearly insufficient, the importance and the need of solving this issue becomes obvious. The article considers the main regularities and processes occurring in the fire-retardant coating from the moment of its creation to the moment of loss of its main operational characteristics. Analysis of the methods for assessing the safety of fire-retardant properties of coatings showed that undoubtedly the most reliable data on the preservation of fire-retardant properties of the coatings can be obtained only by the results of full-scale tests. However, due to the labor-intensive and time-consuming nature of such tests, it is advisable to use accelerated tests of coatings on small-sized metal plates in climatic chambers to predict the service life of fire-retardant coatings for metal structures. The main criterion for predicting the service life of fire- retardant coatings is their preservation of fire- retardant properties over time. As methods for assessing the preservation of fire-retardant properties, the possibility is shown related to using express assessment methods and thermal analysis methods after accelerated climatic tests and directly at the facility after a certain period of operation. In addition, at the same time, the main provisions of GOST R 59637—2021 were considered and used in quality control of fire-retardant treatment, as well as during installation (application), maintenance and repair. Individual requirements and concepts of the specified standard may be partially modified and supplemented.

Utilizing ChatGPT to Create a Riva-Based Business Process Architecture: The Online Teaching Case Study

A Business Process Architecture (BPA) describes the main processes within an organization and the dynamic relationships between them. One of the methods used to create a business process architecture is called the Riva method. In this paper, we employ ChatGPT to assist domain experts in generating BPAs and expediting the steps that require significant amounts of time and effort. The paper investigates the extent to which ChatGPT can aid in generating a BPA by examining each step of the Riva method through a conversational style and utilizing the online teaching case study. The results from each step were compared to an already-created online teaching business process architecture generated using the traditional Riva method. The results indicated that ChatGPT was helpful in identifying essential business entities, as well as the units of work. Typically, these require multiple meetings and brainstorming activities. However, ChatGPT was unable to generate the final process architecture, despite being provided with the necessary rules and heuristics needed for architecture generation. This limitation was attributed to a lack of contextual understanding, rule ambiguity, and difficulties aligning with business goals.

Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations.

While nanoalloys are of paramount scientific and practical interest, the main processes leading to their formation are still poorly understood. Key structural features in the alloy systems, including the crystal phase, chemical ordering, and morphology, are challenging to control at the nanoscale, making it difficult to extend their use to industrial applications. In this contribution, we focus on the gold/silver system that has two of the most prevalent noble metals and combine experiments with simulations to uncover the formation mechanisms at the atomic level. Nanoparticles were produced using a state-of-the-art inert-gas aggregation source and analyzed using transmission electron microscopy and energy-dispersive X-ray spectroscopy. Machine-learning-assisted molecular dynamics simulations were employed to model the crystallization process from liquid droplets to nanocrystals. Our study finds a preponderance of nanoparticles with five-fold symmetric morphology, including icosahedra and decahedra which is consistent with previous results on mono-metallic nanoparticles. However, we observed that gold atoms, rather than silver atoms, segregate at the surface of the obtained nanoparticles for all the considered alloy compositions. These segregation tendencies are in contrast to previous studies and have consequences on the crystallization dynamics and the subsequent crystal ordering. We finally showed that the underpinning of this surprising segregation dynamics is due to charge transfer and electrostatic interactions rather than surface energy considerations.

Jasmonic acid improves barley photosynthetic efficiency through a possible regulatory module, MYC2-RcaA, under combined drought and salinity stress.

The combined stress of drought and salinity is prevalent in various regions of the world, affects several physiological and biochemical processes in crops, and causes their yield to decrease. Photosynthesis is one of the main processes that are disturbed by combined stress. Therefore, improving the photosynthetic efficiency of crops is one of the most promising strategies to overcome environmental stresses, making studying the molecular basis of regulation of photosynthesis a necessity. In this study, we sought a potential mechanism that regulated a major component of the combined stress response in the important crop barley (Hordeum vulgare L.), namely the Rubisco activase A (RcaA) gene. Promoter analysis of the RcaA gene led to identifying Jasmonic acid (JA)-responsive elements with a high occurrence. Specifically, a Myelocytomatosis oncogenes 2 (MYC2) transcription factor binding site was highlighted as a plausible functional promoter motif. We conducted a controlled greenhouse experiment with an abiotic stress-susceptible barley genotype and evaluated expression profiling of the RcaA and MYC2 genes, photosynthetic parameters, plant water status, and cell membrane damages under JA, combined drought and salinity stress (CS) and JA + CS treatments. Our results showed that applying JA enhances barley's photosynthetic efficiency and water relations and considerably compensates for the adverse effects of combined stress. Significant association was observed among gene expression profiles and evaluated physiochemical characteristics. The results showed a plausible regulatory route through the JA-dependent MYC2-RcaA module involved in photosynthesis regulation and combined stress tolerance. These findings provide valuable knowledge for further functional studies of the regulation of photosynthesis under abiotic stresses toward the development of multiple-stress-tolerant crops.

Technology for obtaining a domestic catalyst for hydrogenation of vegetable oils

Vegetable oils are obtained from oil-containing sunflower seeds, burdock, flax, rapeseed, corn, soybeans, etc. The composition of vegetable oils contains esters (triglycerides) of fatty acids with varying degrees of unsaturation. One of the main processes of vegetable oil processing is the hydrogenation process. Hydrogenation of vegetable oils is a widespread technological process of obtaining raw materials for the production of confectionery fats, detergents, soaps, stearin and other products. It is the hydrogenation of vegetable oils that is of great importance, because it increases the volume of food production. Catalysts for hydrogenation of vegetable oils are not produced in Russia. The volume of the import market is about 250 tons per year. The development and production of domestic catalysts is a priority task in solving import substitution problems. The paper suggests the most environmentally friendly and economical way to obtain catalysts of various chemical compositions is the method through an ammonia-carbonate complex. The results of reserve tests of the developed samples of nickel catalyst for hydrogenation of vegetable oils, as well as the conclusion of potential consumers are presented.

Optimization of Historic Buildings Recognition: CNN Model and Supported by Pre-processing Methods

Several cities in Indonesia, such as Cirebon, Bandung, and Bogor, have several historical buildings that date back to the Dutch colonial period. Several Dutch colonial heritage buildings can be found in several areas. The existence of historical buildings also would attract foreign or local tourists who visit one of an area. We need a technology or model that would support the recognition and identification of buildings, including their characteristics. However, recognizing and identifying them is a problem in itself, so technology would be needed to help them. The technology or model that would be implemented in this research is the Convolutional Neural Network model, a derivative of Artificial Intelligent technology focused on image processing and pattern recognition. This process consists of several stages. The initial stage uses the Gaussian Blur, SuCK, and CLAHE methods which are useful for image sharpening and recognition. The second process is feature extraction of the image characteristics of buildings. The results of the image process will support the third process, namely the image retrieval process of buildings based on their characteristics. Based on these three main processes, they would facilitate and support local and foreign tourists to recognize historic buildings in the area. In this experiment, the Euclidean distance and Manhattan distance methods were used in the retrieval process. The highest accuracy in the retrieval process for the feature extraction process with the DenseNet 121 model with the initial process is Gaussian Blur of 88.96% and 88.46%, with the SuCK method of 88.3 and 87.8%, and with CLAHE of 87.7%, and 87.6%. We hope that this research can be continued to identify buildings with more complex characteristics and models.

Studi Awal Sintesis ZnO/SiO2 dengan Silika dari Limbah Padat Geothermal dan Uji Performansinya dalam Penghilangan Metilen Biru

Industrial development impacts environmental problems, such as the emergence of wastewater containing methylene blue. In this research, SiO2 was composited with ZnO to remove methylene blue. The steps of this study include SiO2 extraction from geothermal solid waste, ZnO/SiO2 synthesis, and methylene blue removal test. The process of extracting SiO2 from geothermal solid waste used the sol-gel method. The FTIR analysis showed that SiO2 contains siloxane group (Si-OH) and silanol group (Si-O-Si). ZnO/SiO2 synthesis was done by making SiO2 suspension and continued with adding the addition of several Zn(NO3)2.6H2O. The FTIR analysis of ZnO/SiO2 showed no absorption at the wavenumber 960 cm-1 and there is a shoulder around the number 950 cm-1 which indicates the vibration of Si-O-Zn. Meanwhile, methylene blue removal tests were carried out on artificial wastewater. Based on the research results, the highest percent removal (99%) was obtained under operating conditions, including a dose of 500 mg/L, pH 10, and contact time of 30 minutes. Based on box-benkhen analysis, it is known that dose and pH singularly affect the percent removal, while contact time does not affect the percent removal. The optimization results obtained optimum conditions for methylene blue removal at a dose of 581.952 mg/L, pH of 10, and contact time of 30 minutes. Percent removal in conditions without irradiation and with irradiation of UV light were 98.758% and 99.178%. It shows that the adsorption process is the main process in removing methylene blue, while the photocatalytic process has little effect because it is possible that only a small amount of ZnO can attach to the surface of SiO2.