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A Cost-Effective Balancing Model for Human-Robot Collaborative Assembly Lines
No full textThe increase in the world's human population has led assembly lines to seek new solutions to meet increasing human needs and demands. At this point, Industry 4.0 and Industry 5.0 paradigms can create new solutions for assembly lines. Human-robot interactive designs are a revolutionary change for assembly lines especially. One of the crucial parts of this change is collaborative robots (cobots) that can share the same working environment with humans. Inspired by human-robot interactive designs, this paper investigates the balancing problem of an assembly line using human-cobot collaboration. Human, cobot, and gripper workstations are assigned to fulfill the assembly tasks. It also aims to build a cost-effective model by taking into account costs. A mixed integer linear programming model is developed for the problem, and an illustrative example is presented to understand the developed model better. This study shows how traditional assembly lines can be transformed into a cost-effective design without ignoring the costs when cobots with different abilities and appropriate grippers interact with humans, share the same working environment, and perform tasks within a given cycle time. © 2024 The Authors. Published by Elsevier B.V
Effect of Synthesis Conditions on the Size and Morphology of Magnetic Nickel Particles
No full textThis study compares the properties of nickel (Ni) particles synthesized through the chemical-reduction-reactions (CRRs) under open-atmosphere and pressurized (solvothermal) conditions. The primary objective was to produce Ni particles with sizes below 100 nm with smooth surfaces, single-phase composition, highly crystalline, mono-disperse, and magnetic which are essential for constructing nanostructured Ni suitable for diverse applications. CRRs were conducted in a glass beaker for ambient pressure synthesis and a solvothermal reactor for pressurized conditions. The structural, morphological, and magnetic characteristics of the samples were investigated in detail. The findings demonstrated that the manipulation of the synthesis conditions in both methods allowed the formation of Ni particles with a wide range of morphologies, crystallinity, and purity. Besides, particle sizes varied from nanometer to micrometer scale, depending on the synthesis approach and processing conditions. Moreover, the relation between magnetic characteristics and morphological features was discussed in detail. Therefore, this research provides a comparative evaluation of two different synthesis methods, offering insight into the optimization of conditions for producing phase-pure, magnetic, and equiaxed Ni nanoparticles (NPs). By addressing the challenge of achieving mono-disperse Ni NPs, this study contributes to the understanding of synthesis techniques and elucidating the mechanisms underlying the formation of magnetic Ni NPs.This study was produced from the PhD thesis of Burak KIVRAK. This work was supported by the Scientific and Technological Research Council of Turkiye (TUB ; Idot;TAK) under the Grant Number 121F367. The authors thank TUB ; Idot;TAK for the financial support.Scientific and Technological Research Council of Turkiye (TUBIdot;TAK) [121F367]; TUBIdot;TA
Fault Diagnosis in Thermal Images of Transformer and Asynchronous Motor Through Semantic Segmentation and Different Cnn Models
No full textTransformers are crucial power equipment that play an important role in changing voltage levels to meet consumer needs and in transmitting electricity. A fault in a transformer can cause significant economic losses and social problems. Similarly, asynchronous motors are widely used in industry, and faults in these motors can have substantial negative effects on both the economy and human life. Early detection of faults in both types of power equipment can save time and costs, as well as allow for remedial measures to prevent the failure of the entire system. Traditional fault diagnosis methods, which integrate various monitoring and measurement equipment into power systems, are not sufficient for early fault detection. Therefore, modern solutions have evolved towards more reliable and risk-free artificial intelligence (AI)-based automatic fault diagnosis methods. In our application, we aim to determine faults based on AI in thermal images of asynchronous motors and transformers in operation. Specifically, we propose a semantic segmentation application that highlights fault areas on thermal images, setting other pixels as background. This approach allows the region where the fault occurred to be taken as a reference for later fault diagnosis. As a result of semantic segmentation, the winding of the transformer and the stator region of the asynchronous motor are automatically segmented. Data augmentation techniques are then applied to these segmented images. Augmented and segmented motor and transformer images are classified using seven different Convolutional Neural Network (CNN) models. The results show that CNN models provide fault classification with accuracy reaching 100% for transformers and 96.49% for asynchronous motors
Search for Long-Lived Heavy Neutral Leptons in Proton-Proton Collision Events With a Lepton-Jet Pair Associated With a Secondary Vertex at √s=13 Tev
No full textBenato, Lisa/0000-0001-5135-7489; Heikkila, Jaana/0000-0002-0538-1469; Niedziela, Jeremi/0000-0002-9514-0799; Selvaggi, Michele/0000-0002-5144-9655; Meena, Meena/0000-0003-4536-3967; Cappati, Alessandra/0000-0003-4386-0564; Sagir, Sinan/0000-0002-2614-5860; Konecki, Marcin/0000-0001-9482-4841; Chokheli, Davit/0000-0001-7535-4186; Gomez-Ceballos, Guillelmo/0000-0003-1683-9460; Blumenfeld, Barry/0000-0003-1150-1735; Yoo, Hwidong/0000-0002-3892-3500; Haller, Johannes/0000-0001-9347-7657; Fernandez Bedoya, Cristina/0000-0001-8057-9152; Waltenberger, Wolfgang/0000-0002-6215-7228; Verdier, Patrice/0000-0003-3090-2948; Sarkar, Tanmay/0000-0003-0582-4167; Canelli, Florencia/0000-0001-6361-2117; Cousins, Robert/0000-0002-5963-0467; Dutta, Valentina/0000-0001-5958-829X; Dozen, Candan/0000-0002-4301-634X; Padula, Sandra S./0000-0003-3071-0559; Jafari, Abideh/0000-0001-7327-1870; D'Enterria, David/0000-0002-5754-4303; Heath, Helen/0000-0001-6576-9740; Rinkevicius, Aurelijus/0000-0002-7510-255X; 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Rabbertz, Klaus/0000-0001-7040-9846; Calligaris, Luigi/0000-0002-9951-9448; Costa, Salvatore/0000-0001-9919-0569; Schroder, Matthias/0000-0001-8058-9828; Lee, Sung-Won/0000-0002-3388-8339; Amendola, Chiara/0000-0002-4359-836X; Cassese, Antonio/0000-0003-3010-4516; Noll, Dennis Daniel Nick/0000-0002-0176-2360; Bermudez Martinez, Armando/0000-0001-8822-4727; Reis, Thomas/0000-0003-3703-6624; Wuchterl, Sebastian/0000-0001-9955-9258; Yazgan, Efe/0000-0001-5732-7950; Sharma, Varun/0000-0003-1287-1471; Rieger, Marcel/0000-0003-0797-2606; Tytgat, Michael/0000-0002-3990-2074; Wittich, Peter/0000-0002-7401-2181; Meola, Sabino/0000-0002-8233-7277; Mora Herrera, Maria Clemencia/0000-0003-3915-3170; Ruiz, Jose/0000-0002-3306-0363; Taylor, Lucas/0000-0002-6584-2538; Androsov, Konstantin/0000-0003-2694-6542; Kole, Gouranga/0000-0002-3285-1497; Dogra, Sunil Manohar/0000-0002-0812-0758; Sauvan, Jean-Baptiste/0000-0001-5187-3571; Ha, Seungkyu/0000-0003-2538-1551; Zorbakir, Ibrahim Soner/0000-0002-5962-2221; Robert, Schoefbeck/0000-0002-2332-8784; Elmetenawee, Walaa/0000-0001-7069-0252; Goldouzian, Reza/0000-0002-0295-249X; Kogler, Roman/0000-0002-5336-4399; Kyberd, Paul/0000-0002-7353-7090; Ferencek, Dinko/0000-0001-9116-1202; Leon Holgado, Jaime/0000-0002-4156-6460; Consuegra Rodriguez, Sandra/0000-0002-1383-1837; Cardini, Andrea/0000-0003-1803-0999; Usai, Emanuele/0000-0001-9323-2107; Piccinelli, Andrea/0000-0003-0386-0527; Lee, Sehwook/0000-0002-1028-3468; Watson, Ian James/0000-0003-2141-3413; Yang, Seungjin/0000-0001-6905-6553; Meridiani, Paolo/0000-0002-8480-2259; Erdmann, Wolfram/0000-0001-9964-249X; Carrillo Montoya, Camilo/0000-0002-6245-6535; Diaz, Daniel/0000-0001-6834-1176; Viliani, Lorenzo/0000-0002-1909-6343; Ivanov, Andrew/0000-0002-9270-5643; Tedeschi, Tommaso/0000-0002-7125-2905; Barman, Soumyadip/0000-0001-8891-1674; Arneodo, Michele/0000-0002-7790-7132; Mrenna, Stephen/0000-0001-8731-160X; Duarte, Javier Mauricio/0000-0002-5076-7096; Castilla-Valdez, Heriberto/0009-0005-9590-9958; Walsh, Roberval/0000-0002-3872-4114; Tonelli, Guido Emilio/0000-0003-2606-9156; Sharma, Vivek/0000-0003-1736-8795; Tao, Junquan/0000-0003-2006-3490; Zuolo, Davide/0000-0003-3072-1020; Malik, Sudhir/0000-0002-6356-2655; Mantilla, Cristina/0000-0002-0177-5903; Tinoco Mendes, Andre David/0000-0001-5854-7699; Asilar, Ece/0000-0001-5680-599X; Fontanesi, Elisa/0000-0002-0662-5904; Clement, Emyr/0000-0003-3412-4004; Botta, Cristina/0000-0002-8072-795X; Dolek, Furkan/0000-0001-7092-5517; Lucchini, Marco Toliman/0000-0002-7497-7450; Elmer, Peter/0000-0001-6830-3356; Klanner, Robert/0000-0002-7004-9227; Ford, William/0000-0001-8703-6943; Benaglia, Andrea Davide/0000-0003-1124-8450; Dallavalle, Gaetano Marco/0000-0002-8614-0420; Belforte, Stefano/0000-0001-8443-4460; Salvatico, Riccardo/0000-0002-2751-0567; Fernandez Perez Tomei, Thiago Rafael/0000-0002-1809-5226; Hernandez Calama, Jose Maria/0000-0001-6436-7547; Gershtein, Yuri/0000-0002-4871-5449; Tok, Ufuk Guney/0000-0002-3039-021X; Sahasransu, Abanti Ranadhir/0000-0003-1505-1743; Torres Da Silva De Araujo, Felipe/0000-0002-4785-3057; Das, Pallabi/0000-0002-9770-1377; Lu, Meng/0000-0002-6999-3931; Pasztor, Gabriella/0000-0003-0707-9762; Migliore, Ernesto/0000-0002-2271-5192; Long, Kenneth/0000-0003-0664-1653; Geurts, Frank/0000-0003-2856-9090; Novak, Andrzej/0000-0002-0389-5896; Kaur, Amandeep/0000-0002-1640-9180; Attia Mahmoud, Mohammed/0000-0001-8692-5458; Garcia, Francisco/0000-0002-4023-7964; Fiorendi, Sara/0000-0003-3273-9419; Feld, Lutz/0000-0001-9813-8646; Klyukhin, Vyacheslav/0000-0002-8577-6531; Cuffiani, Marco/0000-0003-2510-5039; Bernardes, Cesar Augusto/0000-0001-5790-9563; Spagnolo, Paolo/0000-0001-7962-5203; Beaudette, Florian/0000-0002-1194-8556; Mitra, Soureek/0000-0002-3060-2278; Ecklund, Karl/0000-0002-6976-4637; Titov, Maxim/0000-0002-1119-6614; Skovpen, Kirill/0000-0002-1160-0621; Santpur, Sai Neha/0000-0001-6467-9970; Novaes, Sergio/0000-0003-0471-8549; Lipton, Ronald/0000-0002-6665-7289; Stepennov, Anton/0000-0001-7747-6582; Abbiendi, Giovanni/0000-0003-4499-7562; Collard, Caroline/0000-0002-5230-8387; Belyaev, Alexander/0000-0002-1733-4408; Ptochos, Fotios/0000-0002-3432-3452; De La Cruz Burelo, Eduard/0000-0002-7469-6974; Hinzmann, Andreas/0000-0002-2633-4696; Levchuk, Leonid/0000-0001-5889-7410; Lange, Clemens/0000-0002-3632-3157; Milosevic, Vukasin/0000-0002-1173-0696; Steggemann, Jan/0000-0003-4420-5510; Janssen, Tahys/0000-0002-3998-4081; Haddad, Yacine/0000-0003-4916-7752; Tiras, Emrah/0000-0002-5628-7464; Kasemann, Matthias/0000-0002-0429-2448; Simone, Federica Maria/0000-0002-1924-983X; Schulte, Jan-Frederik/0000-0003-4421-680X; Cepeda, Maria/0000-0002-6076-4083; Rappoccio, Salvatore/0000-0002-5449-2560; Starodumov, Andrey/0000-0001-9570-9255; Massironi, Andrea/0000-0002-0782-0883; Verdini, Piero Giorgio/0000-0002-0042-9507; Erice Cid, Carlos Francisco/0000-0002-6469-3200; Lizzo, Mattia/0000-0001-7297-2624; Naskar, Kousik/0000-0003-0638-4378; Diotalevi, Tommaso/0000-0003-0780-8785; Tosi, Silvano/0000-0002-7275-9193; Leonardo, Nuno/0000-0002-9746-4594; Donega, Mauro/0000-0001-9830-0412; Dharmaratna, Welathantri/0000-0002-6366-837X; Brigljevic, Vuko/0000-0001-5847-0062; Mousa, Jehad/0000-0002-2978-2718; Hahn, Kristian/0000-0001-7892-1676; Rolandi, Luigi (Gigi)/0000-0002-0635-274X; Delgado Peris, Antonio/0000-0002-8511-7958; You, Zhengyun/0000-0001-8324-3291; Mudholkar, Tanmay/0000-0002-9352-8140; Sandeep, Kaur/0000-0002-3220-3668; Grandi, Claudio/0000-0001-5998-3070; Goy Lopez, Silvia/0000-0001-6508-5090; Argiro', Stefano/0000-0003-2150-3750; De Leo, Ksenia/0000-0002-8908-409X; Ochando, Christophe/0000-0002-3836-1173; Smith, Wesley/0000-0003-3195-0909; Belloni, Alberto/0000-0002-1727-656X; Pigazzini, Simone/0000-0002-8046-4344; Staiano, Amedeo/0000-0003-1803-624X; Vilela Pereira, Antonio/0000-0003-3177-4626; Lethuillier, Morgan/0000-0001-6185-2045; Parida, Bibhuti/0000-0001-9367-8061; /0000-0002-1153-816X; Gerosa, Raffaele/0000-0001-8359-3734; Azzurri, Paolo/0000-0002-1717-5654; Bortignon, Pierluigi/0000-0002-5360-1454; Li, Qiang/0000-0002-8290-0517; De Souza Lemos, Dener/0000-0003-1982-8978; Fedi, Giacomo/0000-0001-9101-2573; Ravera, Fabio/0000-0003-3632-0287; Fernandez Ramos, Juan Pablo/0000-0002-0122-313X; Dragicevic, Marko/0000-0003-1967-6783; Hurtado Anampa, Kenyi/0000-0002-9779-3566; Urda, Lourdes/0000-0002-7865-5010; Heredia De La Cruz, Ivan/0000-0002-8133-6467; Redondo, Ignacio/0000-0003-3737-4121; Vai, Ilaria/0000-0003-0037-5032; Painesis, Haris/0000-0001-5061-7031; Blekman, Freya/0000-0002-7366-7098; Grab, Christophorus/0000-0002-6182-3380; Reimers, Arne Christoph/0000-0002-9438-2059; Bury, Florian/0000-0002-3077-2090; Mondal, Spandan/0000-0003-0153-7590; Bloom, Kenneth/0000-0002-4272-8900; Gutsche, Oliver/0000-0002-8015-9622; Purohit, Arnab/0000-0003-0881-612X; Pastrone, Nadia/0000-0001-7291-1979; Colaleo, Anna/0000-0002-0711-6319; Saka, Halil/0000-0001-7616-2573; Singh, Jasbir/0000-0001-9029-2462; Alverson, George/0000-0001-6651-1178; Galli Mercadante, Pedro/0000-0001-8333-4302; Thachayath Sugunan, Aravind/0000-0001-6545-0350; Yagil, Avi/0000-0002-6108-4004; Kalbhor, Pritam/0000-0002-5892-3743; Ebrahimi, Aliakbar/0000-0003-4472-867X; Meuser, Danilo/0000-0002-2722-7526; Kumar, Arun/0000-0002-5180-6595; Tiwari, Praveen Chandra/0000-0002-3667-3843; Csanad, Mate/0000-0002-3154-6925; Jabeen, Shabnam/0000-0002-0155-7383; Sharma, Ram Krishna/0000-0003-1181-1426; Andrea, Jeremy/0000-0002-8298-7560; Wen, Yiwen/0000-0002-8724-9604; Pfeiffer, Andreas/0000-0001-5328-448X; Alcaraz Maestre, Juan/0000-0003-0914-7474; Caminada, Lea/0000-0001-5677-6033; Missiroli, Marino/0000-0002-1780-1344; Li, Jingyan/0000-0001-5245-2074; Jayatilaka, Bodhitha/0000-0001-7912-5612; Everaerts, Pieter/0000-0003-3848-324X; Fiorina, Davide/0000-0002-7104-257X; Konstantinou, Sotiroulla/0000-0003-0408-7636; Chernyavskaya, Nadezda/0000-0002-2264-2229; Petrucciani, Giovanni/0000-0003-0889-4726; Acosta, Darin/0000-0001-5367-1738; Alibordi, Muhammad/0000-0002-7535-7149; Dini, Paolo/0000-0001-7375-4899; Hamel De Monchenault, Gautier/0000-0002-3872-3592; Aarrestad, Thea/0000-0002-7671-243X; Sandro, Fonseca De Souza/0000-0001-7830-0837; Garutti, Erika/0000-0003-0634-5539; Aruta, Caterina/0000-0001-9524-3264; Legger, Federica/0000-0003-1400-0709; Moraes, Arthur/0000-0002-5157-5686; Vami, Tamas Almos/0000-0002-0959-9211; Malgeri, Luca/0000-0002-0113-7389; Manca, Elisabetta/0000-0001-8946-655X; Flaecher, Henning/0000-0002-5371-941X; Kanuganti, Ankush Reddy/0000-0002-0789-1200; Evdokimov, Olga/0000-0002-1250-8931; Martinez Ruiz Del Arbol, Pablo/0000-0002-7737-5121; Gonzalez Caballero, Isidro/0000-0002-8087-3199; Zghiche, Amina/0000-0002-1178-1450; Tully, Christopher/0000-0001-6771-2174; Sculac, Toni/0000-0002-9578-4105; Bakhshiansohi, Hamed/0000-0001-5741-3357; Bhowmik, Sandeep/0000-0003-1260-973X; Brooke, James/0000-0003-2529-0684; De Guio, Federico/0000-0001-5927-8865; Chatterjee, Suman/0000-0003-2660-0349; Vischia, Pietro/0000-0002-7088-8557; Ko, Sanghyun/0000-0003-4377-9969; Sharma, Ashish/0000-0002-0688-923X; Hatakeyama, Kenichi/0000-0002-6012-2451; Cumalat, John/0000-0002-6032-5857; Figueiredo, Diego/0000-0003-2514-6930; Yoon, Inseok/0000-0002-3491-8026; Felcini, Marta/0000-0002-2051-9331; Litov, Leandar/0000-0002-8511-6883; Gadallah, Mahmoud Moussa Abdelkhalek/0000-0002-8305-6661; Dubinin, Mikhail/0000-0002-7766-7175; Theofilatos, Konstantinos/0000-0001-8448-883XA search for long-lived heavy neutral leptons (HNLs) using proton-proton collision data corresponding to an integrated luminosity of 138 fb(-1) collected at root s = 13TeV with the CMS detector at the CERN LHC is presented. Events are selected with a charged lepton originating from the primary vertex associated with the proton-proton interaction, as well as a second charged lepton and a hadronic jet associated with a secondary vertex that corresponds to the semileptonic decay of a long-lived HNL. No excess of events above the standard model expectation is observed. Exclusion limits at 95% confidence level are evaluated for HNLs that mix with electron and/or muon neutrinos. Limits are presented in the mass range of 1-16.5 GeV, with excluded square mixing parameter values reaching as low as 2 x 10(-7). For masses above 11 GeV, the presented limits exceed all previous results in the semileptonic decay channel, and for some of the considered scenarios are the strongest to date.We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.).r Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - EOS" -be.h project n. 30820817; the Beijing Municipal Science ; Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC -National Research Center for High Performance Computing, Big Data and Quantum Computing and FAIR -Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF "a way of making Europe", and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MoST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF; Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the "Excellence of Science - EOS [30820817]; Beijing Municipal Science AMP; Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22-985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Council of Science and Industrial Research, India; ICSC -National Research Center for High Performance Computing, Big Data and Quantum Computing - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para
Alteration Mineralogy and Fluid Inclusion Microthermometry of the Hes-Daba Area in Gagade, Republic of Djibouti
No full textThis study focuses on fluid inclusions from the Hes-Daba area. Microthermometric measurements were conducted on quartz collected from surface veins that hosted inclusions in two phases: liquid and vapor. The mean homogenization temperature ranged from 150 °C to 367 °C and the melting point of ice ranged from −0.05 °C to −1.14 °C, indicating that the inclusion solutions consisted of 0.1 to 1.9 eq. wt% NaCl. The thermal history and thermal structure were evaluated to estimate the formation temperature. Selected samples were analyzed via x-ray diffraction to provide direct data on geothermal reservoirs; this was necessary because geothermal fluids, through their interactions, can alter the composition and properties of rocks. The main alteration minerals were quartz, calcite, alunite, epidote, hematite, illite, smectite, and chlorite. Therefore, the clay constituted a transition to a hightemperature environment, as evidenced by high temperature hydrothermal alteration minerals such as quartz (>180 °C) and epidote (~250 °C). © 2025, Murat Yakar. All rights reserved.Office Djiboutien de Développement de l'Energie Géothermiqu
Overview of High-Density QCD Studies With the CMS Experiment at the LHC
No full textRuiz, Jose/0000-0002-3306-0363; Dewanjee, Dr. Ram Krishna/0000-0001-6645-6244; Demiroglu, Zuhal Seyma/0000-0001-7977-7127; Tytgat, Michael/0000-0002-3990-2074; Giammanco, Andrea/0000-0001-9640-8294; Tornago, Marta/0000-0001-6768-1056; Evdokimov, Olga/0000-0002-1250-8931; Mora Herrera, Maria Clemencia/0000-0003-3915-3170; Tarricone, Cristiano/0000-0001-6233-0513; Cardini, Andrea/0000-0003-1803-0999; Murillo Quijada, Javier Alberto/0000-0003-4933-2092;We review key measurements performed by CMS in the context of its heavy ion physics program, using event samples collected in 2010-2018 with several collision systems and energies. These studies provide detailed macroscopic and microscopic probes of the quark-gluon plasma (QGP) created at the LHC energies, a medium characterized by the highest temperature and smallest baryon-chemical potential ever reached in the laboratory. Numerous observables related to high-density quantum chromodynamics (QCD) were studied, leading to some of the most impactful and qualitatively novel results in the 40-year history of the field. Using a dedicated high-multiplicity trigger in the first pp run, CMS discovered that small collision systems can exhibit signs of collectivity, a generic phenomenon with significant implications and presently understood to affect essentially all soft physics processes. This observation opened new paths to understand how fluidity and plasma properties emerge in QCD matter as a function of system size. Measurements of jet quenching have reached a completely new level of detail by directly assessing, for the first time, the medium modification of parton showers, as opposed to simply observing leading hadrons or di-hadrons. The first fully reconstructed beauty hadron and heavy-flavor jet nuclear modifications were also measured. The large size of the event samples, the precision of the measurements, and the extension of the probed kinematical phase space, allowed many other hard probes of the QGP medium to be explored in detail, leading to multiple groundbreaking findings. In particular, the seminal measurements of bottomonium suppression patterns answer fundamental questions that have been actively pursued, both theoretically and experimentally, by the community since the mid-1980s. We conclude by outlining the opportunities offered by the continuation of this physics program at the LHC. (c) 2024 CERN for the benefit of the CMS Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: the Armenian Science Committee, project no. 22rl-037; the Austrian Federal Ministry of Education, Science and Research and the Austrian Science Fund; the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP); the Bulgarian Ministry of Education and Science, and the Bulgarian National Science Fund; CERN, Switzerland; the Chinese Academy of Sciences, Ministry of Science and Technology, the National Natural Science Foundation of China, and Fundamental Research Funds for the Central Universities, China; the Ministerio de Ciencia Tecnologia e Innovacion (MINCIENCIAS), Colombia; the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research and Innovation Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Estonian Research Council, Estonia via PRG780, PRG803, RVTT3 and the Ministry of Education and Research TK202; the Academy of Finland, Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics, Finland; the Institut National de Physique Nucleaire et de Physique des Particules CNRS, and Commissariat a l'Energie Atomique et aux Energies Alternatives CEA, France; the Shota Rustaveli National Science Foundation, Georgia; the Bundesministerium fur Bildung und Forschung, Germany, the Deutsche Forschungsgemeinschaft (DFG), Germany, under Germany's Excellence Strategy -EXC 2121 ''Quantum Universe'' -390833306, and under project number 400140256 -GRK2497, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Innovation and the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288, Greece; the National Research, Development and Innovation Office (NKFIH), Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Ministry of Education and Science of the Republic of Latvia; the Research Council of Lithuania, agreement No. VS-19 (LMTLT); the Ministry of Education, and University of Malaya (Malaysia); the Ministry of Science of Montenegro; the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI); the Ministry of Business, Innovation and Employment, New Zealand; the Pakistan Atomic Energy Commission; the Ministry of Education and Science and the National Science Center, Poland; the Fundacao para a Ciencia e a Tecnologia, grants CERN/FIS-PAR/0025/2019 and CERN/FIS-INS/0032/2019, Portugal; the Ministry of Education, Science and Technological Development of Serbia; MCIN/AEI/10. 13039/501100011033, ERDF ''a way of making Europe'', Programa Estatal de Fomento de la Investigacion CientificayTecnica de Excelencia Maria de Maeztu, grant MDM2017-0765, projects PID2020-113705RB, PID2020-113304RB, PID2020-116262RB and PID2020-113341RB-I00, and Plan de Ciencia, Tecnologia e Innovacion de Asturias, Spain; the Ministry of Science, Technology and Research, Sri Lanka; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the Ministry of Science and Technology, Taipei; the Ministry of Higher Education, Science, Research and Innovation, and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Energy, Nuclear and Mineral Research Agency; the National Academy of Sciences of Ukraine; the Science and Technology Facilities Council, UK; the US Department of Energy, and the US National Science Foundation. Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union) the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation, Germany; the Belgian Federal Science Policy Office, Belgium; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the ''Excellence of Science -EOS'' -be.h project n. 30820817; the Beijing Municipal Science and Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Hungarian Academy of Sciences, the New National Excellence Program -UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Scientific and Industrial Research, India; ICSC -National Research Center for HighPerformance Computing, Big Data and Quantum Computing and FAIR -Future Artificial Intelligence Research, fundedby the EU NexGeneration program (Italy); the Latvian Council of Science, Latvia; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, Portugal, grant FCT CEECIND/01334/2018; the National Priorities Research Program by Qatar National Research Fund, Qatar; the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and projects PID2020-113705RB, PID2020-113304RB, PID2020-116262RB and PID2020-113341RB-I00, and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation, grant B37G660013 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).Armenian Science Committee [22rl-037]; Austrian Federal Ministry of Education, Science and Research; Austrian Science Fund; Belgian Fonds de la Recherche Scientifique; Fonds voor Wetenschappelijk Onderzoek; CAPES; FAPERJ; FAPERGS; (FAPESP); Bulgarian Ministry of Education and Science; Bulgarian National Science Fund; CERN, Switzerland; Chinese Academy of Sciences, Ministry of Science and Technology; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities, China; Ministerio de Ciencia Tecnologia e Innovacion; Croatian Ministry of Science, Education and Sport; Croatian Science Foundation; Research and Innovation Foundation, Cyprus; Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; Estonian Research Council, Estonia [PRG780, PRG803, TK202]; Helsinki Institute of Physics, Finland; Institut National de Physique Nucleaire et de Physique des Particules CNRS; Commissariat a l'Energie Atomique et aux Energies Alternatives CEA, France; Shota Rustaveli National Science Foundation [FR-22-985]; Bundesministerium fur Bildung und Forschung, Germany; Deutsche Forschungsgemeinschaft (DFG), Germany [400140256 -GRK2497]; Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; Hellenic Foundation for Research and Innovation [2288]; National Research, Development and Innovation Office (NKFIH), Hungary; Department of Atomic Energy; Istituto Nazionale di Fisica Nucleare, Italy; National Research Foundation (NRF), Republic of Korea; Research Council of Lithuania; Ministry of Education; University of Malaya (Malaysia); Ministry of Science of Montenegro; CONACYT; (UASLP-FAI); Ministry of Business, Innovation and Employment, New Zealand; Pakistan Atomic Energy Commission; National Science Center, Poland; Fundacao para a Ciencia e a Tecnologia [CERN/FIS-PAR/0025/2019, CERN/FIS-INS/0032/2019]; Ministry of Education, Science and Technological Development of Serbia; ERDF ''a way of making Europe [MDM2017-0765, PID2020-113705RB, PID2020-113304RB, PID2020-116262RB, PID2020-113341RB-I00]; Ministry of Science, Technology and Research, Sri Lanka; SNF; UniZH, Canton Zurich; (SER); Ministry of Science and Technology, Taipei; Ministry of Higher Education, Science, Research and Innovation; National Science and Technology Development Agency of Thailand; Scientific and Technical Research Council of Turkey; Turkish Energy, Nuclear and Mineral Research Agency; National Academy of Sciences of Ukraine; US Department of Energy; US National Science Foundation; Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation, Germany; Belgian Federal Science Policy Office, Belgium; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); FWO (Belgium) under the ''Excellence of Science -EOS [30820817]; Beijing Municipal Science and Technology Commission [Z191100007219010]; Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Council of Scientific and Industrial Research, India; ICSC -National Research Center for HighPerformance Computing, Big Data and Quantum Computing and FAIR -Future Artificial Intelligence Research; Latvian Council of Science, Latvia; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para a Ciencia e a Tecnologia, Portugal [FCT CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund, Qatar [PID2020-113705RB, PID2020-113304RB, PID2020-116262RB, PID2020-113341RB-I00, MDM-2017-0765]; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation [B37G660013]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (USA
Mimari Tasarım Sürecinde Yaratıcılığı Geliştirmeye Yönelik Bir Model Önerisi
No full textIn architectural education, which is based on interaction and communication, there is a dialog provided by using the tools of representation. In the past, there was a more monopolistic educational structure shaped by the influence of schools and movements, while in the process, individualization was seen in the educational structure with the increasing number of universities with formal education. Over time, the diversification of representation tools with digitalization and the inability to use these tools in a qualified manner have led to a weakening in the quality of education. One of the most important factors of this situation is that the new generation born into the digital world cannot use technology in a qualified way and cannot spend the architectural design process efficiently as a result of the decrease in focus periods. The fact that students skip the creative thinking stages of the architectural design process and turn directly to the final product has led to a decline in creativity in architectural design education. In this context, considering the 21st century competencies, architectural design education needs to be reconsidered. Architectural design education is based on learning by doing and is focused on developing creativity. The use of architectural representation tools at the right stage of the design process is an important factor in the development of creativity. This study proposes a model in which traditional and digital tools are used together to support the production of creative thinking in architectural design education. This model, limited to architectural design studios, aims to improve the production of creative thinking by redefining architectural education in the digital age. The study, which aims to improve the creativity level of the designer-student in the architectural design education process with the appropriate and correct use of representation tools, follows a mixed methodology in which qualitative and quantitative research methods are used together. The effect of the proposed training model on the production of creative thinking was analyzed and tested on two separate field studies. As a result of the quantitative and qualitative analyses, the model was validated and defined as an educational method that can be applied in architectural design studios. As a result of the field study, it was determined that creativity is a phenomenon that can be developed by learning intellectual, architectural and technical skills. The findings of the field study are as follows; The pre-test results show that the perception and creativity levels of the architecture students participating in the tests need to be improved in the context of architecture education. The use of traditional or digital representation tools by the architecture students participating in the tests is not at a qualified level. As defined in the design stages of the education model, the increase in the level of creativity is higher with the representation tools used on-site. The increase in the creativity level of the students who use the representation tool qualitatively in the design stages of the education model is higher than those who do not. The education model applied in the workshop format increased the ability to produce creative thinking more than the compulsory studio course. It was determined that the creativity levels of the first-year architecture students who participated in the tests -despite having less architectural knowledge- were higher than the second-year architecture students who participated in the tests. As a result of the study, it was determined that creativity in architectural design education is a phenomenon that can be developed by learning the intellectual, architectural and technical skills of architecture. For this purpose, it was concluded that contemporary and conventional representation tools should be used appropriately, accurately and qualitatively. In order for architectural design education to catch up with the requirements of the age and to keep up to date, while including digital representation tools in education, it should not cause the existing tools to lose their meaning. In the design process, representation tools should be considered as tools that support the process, including the generation of the design idea and the visualization of the final product. Applying an educational model that will support the production of creative thinking to architecture students at an early stage will produce more successful results.Temelinde etkileşim ve iletişimin olduğu mimarlık eğitiminde, temsil araçları kullanılarak sağlanan bir diyalog vardır. Geçmişte ekol ve akımların etkisi ile şekillenen, daha tekel ilerleyen bir eğitim yapısı mevcutken, süreçte formel eğitimle birlikte artan üniversite sayısı ile eğitim yapısında bireyselleşmeler görülmüştür. Zaman içerisinde dijitalleşme ile birlikte temsil araçlarının çeşitlenmesi ve bu araçların nitelikli kullanılamaması ise eğitimin niteliğinde zayıflamaya yol açmıştır. Bu durumun en önemli faktörlerinden biri dijitalin içine doğan yeni neslin, teknolojiyi nitelikli kullanamaması ve odak sürelerinin azalması sonucu mimari tasarım sürecinin verimli geçirememeleridir. Öğrencilerin mimari tasarım sürecinin yaratıcı düşünce üretme aşamalarının atlanarak, direk sonuç ürüne yönelmesi mimari tasarım eğitiminde yaratıcılığın gerilemesine neden olmuştur. Bu bağlamda, 21.yy yeterlilikleri göz önüne alındığında mimari tasarım eğitiminin yeniden ele alınması gerekmektedir. Mimari tasarım eğitimi, yaparak öğrenme üzerine kurguludur ve yaratıcılığı geliştirme odaklıdır. Tasarım sürecinde mimari temsil araçlarının tasarımın doğru aşamasında ve nitelikli kullanılması yaratıcılığın geliştirilmesinde önemli bir etkendir. Bu çalışma, mimari tasarım eğitiminde yaratıcı düşünce üretimini destekleyecek, geleneksel ve dijital araçlarının bir arada kullanıldığı bir model önerir. Mimari tasarım stüdyoları ile sınırlandırılan bu model, dijital çağda mimarlık eğitimini yeniden tanımlayarak yaratıcı düşünce üretimini iyileştirmeyi hedefler. Mimari tasarım eğitimi sürecinde, tasarımcı-öğrencinin yaratıcılık düzeyini, temsil araçlarının yerinde ve doğru kullanımı ile geliştirmeyi hedefleyen çalışmada, nitel ve nicel araştırma yöntemlerinin bir arada kullanıldığı karma bir metodoloji izlenmiştir. Önerilen eğitim modelinin yaratıcı düşünce üretimine etkisi iki ayrı alan çalışması üzerinde incelenerek test edilmiştir. Yapılan nicel ve nitel analizler sonucunda modelin geçerliliği sağlanarak, mimari tasarım stüdyolarında uygulanabilecek bir eğitim metodu olarak tanımlanmıştır. Alan çalışması sonucunda, yaratıcılığın düşünsel, mimari ve teknik becerilerin öğrenilmesi ile geliştirilebilen bir olgu olduğu tespit edilmiştir. Alan çalışması bulguları şu şekildedir; Ön test sonuçları, testlere katılan mimarlık öğrencilerinin algı ve yaratıcılık düzeylerinin mimarlık eğitimi bağlamında geliştirilmesi gerekmektedir. Testlere katılan mimarlık öğrencilerinin geleneksel ya da dijital temsil aracı kullanımı nitelikli seviyede değildir. Eğitim modelinin tasarım aşamalarında tanımlandığı şekliyle yerinde kullanılan temsil araçları ile yaratıcılık düzeyinde yaşanan artış daha fazladır. Eğitim modelinin tasarım aşamalarında temsil aracını nitelikli kullanan öğrencilerin yaratıcılık düzeylerindeki artış, kullanmayanlara oranla daha fazladır. Atölye formatında uygulanan eğitim modeli, zorunlu stüdyo dersine göre yaratıcı düşünce üretme yetisini daha fazla arttırmıştır. Testlere katılan birinci sınıf mimarlık öğrencilerinin -daha az mimari bilgiye sahip olmalarına rağmen- yaratıcılık düzeylerinin testlere katılan ikinci sınıf mimarlık öğrencilerinden daha yüksek olduğu tespit edilmiştir. Çalışma sonucunda, mimari tasarım eğitiminde yaratıcılığın, mimarlığın düşünsel, mimari ve teknik becerilerinin öğrenilmesi ile geliştirilebilen bir olgu olduğu tespit edilmiştir. Bunun için çağdaş ve konvansiyonel temsil araçlarının yerinde, doğru ve nitelikli kullanılması gerektiği sonucuna ulaşılmıştır. Mimari tasarım eğitiminin çağın gerekliliklerini yakalaması ve güncelliğini koruması için dijital temsil araçlarını eğitime dâhil ederken, mevcut araçların anlamını yitirmesine sebep olmamalıdır. Tasarım sürecinde temsil araçları, tasarım fikrinin üretilmesinde ve sonuç ürünün görselleştirilmesinde olmak üzere, süreci destekleyen araçlar olarak ele alınmalıdır. Yaratıcı düşünce üretimini destekleyecek eğitim modelinin mimarlık öğrencilerine erken dönemde uygulanması daha başarılı sonuçlar ortaya çıkaracaktır
Enhancing Photodegradation of Malachite Green Using ZrO2 Nanoparticles Supported on Biochar Derived From Cornus Sanguinea L. Berry Seed Shells
No full textIn this study, malachite green (MG) was efficiently removed from an aqueous solution using a nanocomposite consisting of biochar (BC) loaded with zirconium oxide (ZrO2) nanoparticles. The nanocomposite (0.1ZrO(2)@BC) was prepared by mixing ZrO2 nanoparticles and BC in a 1:9 weight ratio, with the BC derived from the pyrolysis of Cornus sanguinea L. seeds. The nanocomposite was characterized in terms of its structure, morphology, and optical properties using X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscope (SEM), and UV- Visible (UV-Vis) spectroscopy. The XRD patterns and SEM images of the composite structure demonstrated that highly crystalline 0.1ZrO(2)@BC was successfully synthesized, with ZrO2 nanoparticles dispersed across the surface of BC. According to the results, at pH:4.8, discoloration of MG in the presence of the 0.1ZrO(2)@BC nanocomposite (76.6 +/- 3.2%) surpassed the performance of both the pristine BC (35.4 +/- 3.2%) and ZrO2 nanoparticles (57.0 +/- 3.5%). The apparent first-order rate constants (k(app)) of 0.1ZrO(2)@BC nanocomposite (0.0115 +/- 0.0002 min(-1)) is approximately 4 times higher than that of the pristine BC (0.0033 +/- 0.0002 min(-1)) and 2 times greater than that of the ZrO2 nanoparticles (0.0066 +/- 0.0001 min(-1)). The degradation efficiency of the 0.1ZrO(2)@BC nanocomposites was also investigated at pH:7.0 and 10.0. According to the results, MG dye degradation is more efficient at higher solution pH values after 120-minute UV light irradiation (pH: 10.0; 94.0 +/- 3.2%). The experimental results provide new insights into the use of nanocomposites for the treatment of wastewater contaminated with hazardous dye Moreover, the nanocomposites displayed the capability of being recycled up to 3 times without any noticeable decrease in stability.This study received partial financial support from the Turkish Academy of Sciences (TUBA).Turkish Academy of Sciences (TUBA
Cutting Force and Delamination Optimization of Nanoparticle-Reinforced Basalt/Epoxy Multi-Scale Composites in Dry Drilling by Taguchi Design
No full textPurposeThe real-time performance requirements of montage components and assembly features of structural parts are among the most critical factors for the utilization of polymer-matrix laminates in the aerospace industry. In this context, the present study provides a comprehensive perspective on the dry drilling optimization of nanographene-added basalt fiber-reinforced epoxy composite laminates, focusing on cutting force and surface delamination damage.Design/methodology/approachThe combined effects of feed rate (FR) (0.10, 0.15 and 0.20 mm/rev), tool diameter (3 and 5 mm) and nanographene ratio (0, 0.3 and 0.7 wt.%) were investigated as input parameters using a specially designed dagger tool for the first time in the literature. Additionally, Taguchi's L18 design was employed to determine the optimal combination of input variables.FindingsThe results indicate that lower feed rates, smaller tool diameters and higher nanoparticle concentrations result in the lowest cutting forces. As for the delamination factor, lower feed rates, larger tool diameters and higher nanoparticle concentrations were identified as the best combination to maintain the structural integrity of the machined surfaces. Only localized minor chips were seen at the best combination. Detected outcomes can be used for future projects that aim to explore the joining strength of mechanical assembly for aircraft laminate structures.Originality/valueAchieving high-performance composite assemblies in aerospace applications (particularly in wing, fuselage and interior components), with sufficient mechanical properties, requires precise optimization of drilling operations to ensure strong joints and high-quality surfaces without delamination defects. This study, specifically focusing on nanoparticle-modified basalt fiber-reinforced laminates for aerospace implementations, is the first to elucidate the combined effects of FR, tool diameter and nanoparticle ratio on thrust force and delamination factor
Synthesis of Glutaraldehyde Cross-Linked Magnetic Alginate/Banana Peel Biocomposite for the Removal of Methylene Blue: Kinetic, Thermodynamic and Equilibrium Studies
No full textOne of the specific pollutants worldwide is dyes. These must be removed from wastewater before being discharged into receiving environments. In this study, the adsorption of methylene blue (MB), used in many industries, from its aqueous solution onto glutaraldehyde cross-linked nano Fe3O4/banana peel/alginate beads (g-BP/ALG@Fe3O4) was examined. Biocomposite beads were prepared by incorporating nano Fe3O4 powder and banana peel powder into a calcium alginate gel using a simple 'mix and drop' synthesis. Characterization of the synthesized g-BP/ALG@Fe3O4 was carried out by FTIR, SEM, EDX-mapping and XRD. In the study, for MB adsorption in the batch system with g-BP/ALG@Fe3O4, adsorbent amount (1-8g/L), pH (3-9), contact time (5-360min), temperature (25-55 degrees C), initial dye concentration (10-300mg/L) optimum removal conditions were examined. The optimum conditions obtained were determined as pH6 (original solution pH), temperature 25 degrees C, amount of adsorbent 4 g/L, and contact time 180 min. To calculate isotherm parameters and examine adsorption kinetics, Langmuir, Freundlich, Tempkin, Scarthard, D-R adsorption isotherm models and pseudo-I-order kinetic, pseudo-II-order kinetic, elovich, intraparticle diffusion kinetic models equations were applied. It was determined that the adsorption process conformed more to Langmuir isotherm model and adsorption capacity was determined as 75.76 mg/g. The adsorption process followed the pseudo-II-order kinetic model, thermodynamic studies revealed that it was an exothermic and spontaneous process. This new adsorbent, synthesized for reasons such as the high removal capacity of waste banana peels, cheap, environmentally friendly, recyclable, and the fact that alginate as a biopolymer does not harm the environment, has been found to be an effective and alternative material when compared to different adsorbents in the removal of MB dye from aqueous media