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Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at (Formula presented.) TeV with the ATLAS detector

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Journal of High Energy Physics 2024年第4期2024卷 26页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramont Department of Physics University of Adelaide Department of Physics University of Alberta Department of Physics Ankara University Division of Physics TOBB University of Economics and Technology LAPP Université Savoie Mont Blanc CNRS/IN2P3 APC Université Paris Cité CNRS/IN2P3 High Energy Physics Division Argonne National Laboratory Department of Physics University of Arizona Department of Physics University of Texas at Arlington Physics Department National and Kapodistrian University of Athens Physics Department National Technical University of Athens Department of Physics University of Texas at Austin Institute of Physics Azerbaijan Academy of Sciences Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Institute of High Energy Physics Chinese Academy of Sciences Physics Department Tsinghua University Department of Physics Nanjing University School of Science Shenzhen Campus of Sun Yat-sen University University of Chinese Academy of Science (UCAS) Institute of Physics University of Belgrade Department for Physics and Technology University of Bergen Physics Division Lawrence Berkeley National Laboratory University of California Institut für Physik Humboldt Universität zu Berlin Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern School of Physics and Astronomy University of Birmingham Department of Physics Bogazici University Department of Physics Engineering Gaziantep University Department of Physics Istanbul University Facultad de Ciencias y Centro de Investigaciónes Universidad Antonio Nariño Departamento de Física Universidad Nacional de Colombia Dipartimento di Fisica e Astronomia A. Righi Università di Bologna INFN Sezione di Bologna Physikalisches Institut Universität Bonn Department of Physics Boston University Department of Physics Brandeis University Transilvania University of Brasov Horia Hulubei National Institute of Physics and Nuclear Engineering Department of Physics Alexandru

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W^±W^±jj) using 139 fb⁻¹ of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W^±W^±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H^±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H^±± mass near 450 GeV, with a global significance of 2.5 standard deviations. © The Author(s) 2024.

关键词： Hadron-Hadron Scattering Vector Boson Production

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Prototype Design of Playback and Search system for Lecture Video Content using Google Cloud API

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Procedia computer science 2019年 159卷 1517-1526页

作者： Yoshimasa Ohnishi Shin’nosuke Yamaguchi Yoshiki Shimoikura Kazunori Nishino Hideki Kondo Akihiro Hayashi Kyushu Institute of Technology Learning and Teaching Center 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan Kyushu Institute of Technology Institute of Liberal Arts 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan

Recently, it has become possible to easily use video teaching materials in lectures and exercises using high-performance information terminals. In this study, we design and develop playback functions for lecture videos as learning support using a learning management system. The main feature of the proposed system generates keywords from handwritten characters and lecture speech so that learners can search for playback positions related to keywords. Additionally, it becomes possible to create a highly maintainable system in a short development period using speech recognition and still-image recognition functions available on the internet. In this paper, we describe our prototype implementation and present the results of our initial evaluation. The results demonstrate that, regarding the playback of a lecture video, it is possible to use the keyword search function 20–40 min after the lecture video is released. Moreover, we implemented a playback system using a block function on Moodle so that other teaching material in the course could be viewed simultaneously.

关键词： keyword search handwritten characters lecture video internet service Moodle

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Numerical Analysis of Dielectric Post-Wall Waveguides

Numerical Analysis of Dielectric Post-Wall Waveguides

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International Workshop on Antenna technology: Small Antennas and Novel Metamaterials, iWAT

作者： Elguja Archemashvili Kiyotoshi Yasumoto Vakhtang Jandieri Jaromir Pistora Hiroshi Maeda Daniel Erni School of Mathematics and Computer Sciences Free University of Tbilisi Tbilisi Georgia Faculty of Information Science and Electrical Engineering Professor Emeritus Kyushu University Fukuoka Japan General and Theoretical Electrical Engineering (ATE) Faculty of Engineering University of Duisburg-Essen Duisburg Germany Nanotechnology Centre VSB Technical University of Ostrava Ostrava – Poruba Czech Republic Department of Information and Communication Engineering Fukuoka Institute of Technology Fukuoka Japan

ISBN: (数字)9781728126401

ISBN: (纸本)9781728126418

Functional post-wall waveguides that are formed by periodically distributed dielectric posts are numerically analyzed. In this preliminary study, the propagation constant and attenuation constant of the dielectric post-wall waveguide is rigorously calculated using our originally developed numerical method. The developed formulation is accurate and numerically very fast. Structural parameters of the dielectric post-wall waveguide are properly chosen in order to achieve the confinement of the field in the guiding region as strong as possible even in case of one-layered dielectric structure. The final goal of our investigations is to realize the functional dielectric post-wall waveguide-based filters, which are expected to have a practical application in THz region, where the metallic (PEC) rods are losing their properties.

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Digital Reference: a quasi-standard for digitalization in the domain of semiconductor supply chains

Digital Reference: a quasi-standard for digitalization in th...

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Industrial Cyber-Physical systems (ICPS)

作者： Hans Ehm Erwin Schoitsch Jan Wytze van der Weit Nour Ramzy Lanyingzhu Luo Daniel Louis Gruetzner Infineon Technologies AG Munich Germany Austrian Institute of Technology Vienna Austria Philips Consumer Lifestyle Philips Drachten Netherlands Faculty of Electrical Engineering and Computer Science Leibniz University Hannover Germany Faculty of Information System The Technical University of Munich Munich Germany EPF École d'ingénieur-e-s Sceaux France

ISBN: (数字)9781728163895

ISBN: (纸本)9781728163901

This paper is about the installation of trust in the Semantic Web content of the Digital Reference (DR). The DR was developed in H2020/ECSEL/Productive4.0, which contains ontologies to model production and Cyber Physical systems addressing the whole industrial automation and control area. It should serve as a quasi-standard for digitalization in the domain of semiconductors and corresponding supply chains to overcome the partial incompatibility problem of existing *** Web is a success story in the B2C (Business to consumer) environment as it is understandable for both humans and machines alike. To transfer this success of easy data exchange into the complex industrial B2B (Business to business) environment, a much higher quality is required - a standardization of the classes and properties. The confidence in standards usually comes from human verification, validation and confirmation, which has the disadvantage of being slow. Machine validation could be faster but often lacks confidence. Thus, how can trust be installed to ensure the "correctness" of the used classes and properties in a speedy process?We propose a human and machine blended approach based on peer review and Blockchain technology built on decentralized peer-to-peer networks to solve this problem. The consensus process combines transparency, traceability, immutability and speed of Blockchain with the fidelity of human experts.

关键词： Standards IEC Standards Semantic Web Safety Industries Ontologies Supply chains

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Epileptic seizures detection using deep learning techniques: A review

arXiv

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arXiv 2020年

作者： Shoeibi, Afshin Khodatars, Marjane Ghassemi, Navid Jafari, Mahboobeh Moridian, Parisa Alizadehsani, Roohallah Panahiazar, Maryam Khozeimeh, Fahime Zare, Assef Hosseini-Nejad, Hossein Khosravi, Abbas Atiya, Amir F. Aminshahidi, Diba Hussain, Sadiq Rouhani, Modjtaba Nahavandi, Saeid Acharya, Udyavara Rajendra K. N. Toosi University of Technology Tehran*** Iran The Computer Engineering Department Ferdowsi University of Mashhad Mashhad*** Iran The Mashhad Branch Islamic Azad University Mashhad91735413 Iran Electrical and Computer Engineering Faculty Semnan University Semnan*** Iran The Faculty of Engineering Science and Research Branch Islamic Azad University Tehran*** Iran Deakin University Waurn PondsVIC3217 Australia The Institute for Computational Health Sciences School of Medicine University of California San FranciscoCA94143 United States Faculty of Electrical Engineering Gonabad Branch Islamic Azad University Gonabad*** Iran The Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran*** Iran The Department of Computer Engineering Faculty of Engineering Cairo University Cairo12613 Egypt System Administrator at Dibrugarh University Assam 786004 India The Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore599494 Singapore The Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore599489 Singapore The Department of Bioinformatics and Medical Engineering Taichung City41354 Taiwan

A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its branches is deep learning (DL). Before the rise of DL, conventional machine learning algorithms involving feature extraction were performed. This limited their performance to the ability of those handcrafting the features. However, in DL, the extraction of features and classification are entirely automated. The advent of these techniques in many areas of medicine, such as in the diagnosis of epileptic seizures, has made significant advances. In this study, a comprehensive overview of works focused on automated epileptic seizure detection using DL techniques and neuroimaging modalities is presented. Various methods proposed to diagnose epileptic seizures automatically using EEG and MRI modalities are described. In addition, rehabilitation systems developed for epileptic seizures using DL have been analyzed, and a summary is provided. The rehabilitation tools include cloud computing techniques and hardware required for implementation of DL algorithms. The important challenges in accurate detection of automated epileptic seizures using DL with EEG and MRI modalities are discussed. The advantages and limitations in employing DL-based techniques for epileptic seizures diagnosis are presented. Finally, the most promising DL models proposed and possible future works on automated epileptic seizure detection are delineated. © 2020, CC BY-NC-ND.

关键词： Feature extraction

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HARNESSING DIGITAL PATHOLOGY AND CAUSAL LEARNING TO IMPROVE EOSINOPHILIC ESOPHAGITIS DIETARY TREATMENT ASSIGNMENT

arXiv

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arXiv 2023年

作者： Aknin, Eliel Larey, Ariel Caldwell, Julie M. Collins, Margaret H. Rothenberg, Marc E. Savir, Yonatan Abonia, Juan P. Aceves, Seema S. Arva, Nicoleta C. Chehade, Mirna Dellon, Evan S. Gonsalves, Nirmala Gupta, Sandeep K. Leung, John Peterson, Kathryn A. Shoda, Tetsuo Spergel, Jonathan M. Department of Physiology Biophysics and System Biology Faculty of Medicine Technion Israel Institute of Technology Haifa Israel Faculty of Industrial Engineering Technion Israel Institute of Technology Haifa Israel Faculty of Computer Science Technion Israel Institute of Technology Haifa Israel Division of Allergy and Immunology Cincinnati Children's Hospital Medical Center CincinnatiOH United States Dept. of Pediatrics University of Cincinnati College of Medicine CincinnatiOH United States Division of Pathology and Laboratory Medicine Cincinnati Children's Hospital Medical Center CincinnatiOH United States Division of Allergy and Immunology University of California at San Diego Rady Children's Hospital San DiegoCA United States Dept. of Pathology and Laboratory Ann and Robert H Lurie Children's Hospital Northwestern University Feinberg School of Medicine ChicagoIL United States Mount Sinai Center for Eosinophilic Disorders Icahn School of Medicine at Mount Sinai New YorkNY United States Division of Gastroenterology and Hepatology University of North Carolina School of Medicine Chapel HillNC United States Division of Gastroenterology and Hepatology Northwestern University Feinberg School of Medicine ChicagoIL United States Division of Pediatric Gastroenterology Hepatology and Nutrition Children's of Alabama University of Alabama at Birmingham BirminghamAL United States Boston Specialists BostonMA United States Division of Gastroenterology University of Utah Salt Lake CityUT United States Division of Allergy and Immunology Children's Hospital of Philadelphia Dept. of Pediatrics Perelman School of Medicine The University of Pennsylvania PhiladelphiaPA United States

Eosinophilic esophagitis (EoE) is a chronic, food antigen-driven, allergic inflammatory condition of the esophagus associated with elevated esophageal eosinophils. EoE is a top cause of chronic dysphagia after GERD. Diagnosis of EoE relies on counting eosinophils in histological slides, a manual and time-consuming task that limits the ability to extract complex patient-dependent features. The treatment of EoE includes medication and food elimination. A personalized food elimination plan is crucial for engagement and efficiency, but previous attempts failed to produce significant results. In this work, on the one hand, we utilize AI for inferring histological features from the entire biopsy slide, features that cannot be extracted manually. On the other hand, we develop causal learning models that can process this wealth of data. We applied our approach to the 'Six-Food vs. One-Food Eosinophilic Esophagitis Diet Study', where 112 symptomatic adults aged 18-60 years with active EoE were assigned to either a six-food elimination diet (6FED) or a one-food elimination diet (1FED) for six weeks. Our results show that the average treatment effect (ATE) of the 6FED treatment compared with the 1FED treatment is not significant, that is, neither diet was superior to the other. We examined several causal models and show that the best treatment strategy was obtained using T-learner with two XGBoost modules. While 1FED only and 6FED only provide improvement for 35%-38% of the patients, which is not significantly different from a random treatment assignment, our causal model yields a significantly better improvement rate of 58.4%. This study illustrates the significance of AI in enhancing treatment planning by analyzing molecular features' distribution in histological slides through causal learning. Our approach can be harnessed for other conditions that rely on histology for diagnosis and treatment. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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Noise bias compensation for reconstructed HDR images in two layer coding

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2019年第12期139卷 1442-1451页

作者： Minewaki, Sayaka Hamzah, Fairoza Amira Binti Yoshida, Taichi Iwahashi, Masahiro Kiya, Hitoshi Department of Computer Science and Engineering National Institute of Technology Yuge College 1000 Kamijima-cho Ochi-gun Ehime794-2593 Japan Kyoto College of Graduate Studies for Informatics 7 Tanakamonzen-cho Sakyo-ku Kyoto606-8225 Japan Department of Computer and Network Engineering University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Department of Electrical Electronics and Information Engineering Nagaoka University of Technology 1603-1 Kamitomioka Nagaoka Niigata940-2188 Japan Department of Information and Communication Systems Faculty of System Design Tokyo Metropolitan University 6-6 Asahigaoka Hino Tokyo191-0065 Japan

We propose a two-layer coding method for HDR images with noise bias compensation (NBC). Although the mean of image noise is assumed to be zero originally, it becomes nonzero (that is, noise bias is present) after tone mapping, because of the nonlinearity of tone mapping. In the conventional two-layer coding, the reconstructed LDR image is decoded using a lossy encoder of a base layer that includes noise;the noise is included in an HDR image that is inverse tone mapped from a reconstructed LDR image with noise bias. We aim to improve the quality of reconstructed HDR images by compensating for noise bias. NBC classifies pixels in a noisy image into several subsets according to the pixel value after tone mapping, and compensates for the pixel value in each subset with a compensation value determined in advance. The compensation values are determined by using all pixel values in the LDR image that is input to the base layer, in addition to those in the HDR image that is inversely tone mapped from the reconstructed LDR image. We perform NBC following inverse tone mapping for the reconstructed LDR image. Experimental results show the effectiveness of the proposed method. © 2019 The institute of Electrical Engineers of Japan.

关键词： Image denoising

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Correction to: How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning

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Journal of religion and health 2021年第4期60卷 2322-2323页

作者： Roghieh Nooripour Simin Hosseinian Abir Jaafar Hussain Mohsen Annabestani Ameer Maadal Laurel Radwin Peyman Hassani-Abharian Nikzad Ghanbari Abolghasem Khoshkonesh Department of Counseling Faculty of Education and Psychology Alzahra University Tehran Iran. r.noori@alzahra.ac.ir. Department of Counseling Faculty of Education and Psychology Alzahra University Tehran Iran. Computer Science Department Liverpool John Moores University Liverpool L33AF UK. Faculty of Electrical Engineering Sharif University of Technology Azadi Ave PO Box 11365-11155 Tehran Iran. Department of Psychology Faculty of Humanities Islamic Azad University Shahr-E Rey Branch Tehran Iran. Center for Health Care Organizational and Implementation Research (CHOIR) VA Boston Healthcare System Boston MA USA. Institute for Cognitive Science Studies Brain and Cognition Clinic Tehran Iran. Clinical Psychology (Prevention and Treatment of Addiction) Faculty of Education and Psychology Shahid Beheshti University (SBU) Tehran Iran. Department of Counseling Faculty of Education and Psychology Shahid Beheshti University (SBU) Tehran Iran.

The original version of the article was inadvertently published with the ethical code in Ethical Considerations section.

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CRNN Based Jersey-Bib Number/Text Recognition in Sports and Marathon Images

CRNN Based Jersey-Bib Number/Text Recognition in Sports and ...

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International Conference on Document Analysis and Recognition

作者： Sauradip Nag Raghavendra Ramachandra Palaiahnakote Shivakumara Umapada Pal Tong Lu Mohan Kankanhalli Department of Computer Science & Engineering Kalyani Government Engineering College Kalyani India Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Norway Faculty of Computer System and Information Technology University of Malaya Malaysia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University China Department of computer science National University of Singapore Singapore

The primary challenge in tracing the participants in sports and marathon video or images is to detect and localize the jersey/Bib number that may present in different regions of their outfit captured in cluttered environment conditions. In this work, we proposed a new framework based on detecting the human body parts such that both Jersey Bib number and text is localized reliably. To achieve this, the proposed method first detects and localize the human in a given image using Single Shot Multibox Detector (SSD). In the next step, different human body parts namely, Torso, Left Thigh, Right Thigh, that generally contain a Bib number or text region is automatically extracted. These detected individual parts are processed individually to detect the Jersey Bib number/text using a deep CNN network based on the 2-channel architecture based on the novel adaptive weighting loss function. Finally, the detected text is cropped out and fed to a CNN-RNN based deep model abbreviated as CRNN for recognizing jersey/Bib/text. Extensive experiments are carried out on the four different datasets including both bench-marking dataset and a new dataset. The performance of the proposed method is compared with the state-of-the-art methods on all four datasets that indicates the improved performance of the proposed method on all four datasets.

关键词： Text recognition Sports Image recognition Hip Thigh Torso Biological system modeling

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Environmentally safe layered crystal produced from hazardous chemical elements: TlPb2BrI4, a new promising detector material

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Journal of Alloys and Compounds 2022年 924卷 1页

作者： Khyzhun, O.Y. Vu, Tuan V. Parasyuk, O.V. Fedorchuk, A.O. Fochuk, P.M. Lavrentyev, A.A. Gabrelian, B.V. Levchuk, Ievgen Matt, Gebhard J. Tedde, Sandro F. Schmidt, Oliver Shrestha, Shreetu Brabec, Christoph J. Kityk, I.V. Piasecki, M. Frantsevych Institute for Problems of Materials Science National Academy of Sciences of Ukraine 3 Krzhyzhanovsky Street KyivUA-03142 Ukraine Faculty of Mechanical - Electrical and Computer Engineering School of Engineering and Technology Van Lang University Ho Chi Minh City Viet Nam Department of Inorganic and Physical Chemistry Lesya Ukrainka Volyn National University 13 Voli Avenue LutskUA-43025 Ukraine Department of Inorganic and Organic Chemistry Lviv National University of Veterinary Medicine and Biotechnologies 50 Pekarska Street Lviv79010 Ukraine Yuriy Fed'kovych Chernivtsi National University 2 Kotziubynskoho Street Chernivtsi58012 Ukraine Department of Electrical Engineering and Electronics Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Department of Computational Technique and Automated System Software Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Martensstrasse 7 Erlangen91058 Germany Siemens Healthineers Technology Center Guenther-Scharowsky-Str. 1 Erlangen91058 Germany Electrical Engineering Department Czestochowa University Technology Armii Krajowej 17 Częstochowa42217 Poland Departmentof Experimental Physics and Information-measuring Technology Lesya Ukrainka Volyn National University Voli Avenue 13 Lutsk43025 Ukraine J.Dlugosz University Częstochowa Armii Krajowej 13/15 Częstochowa42200 Poland

Exploring better Gamma, X-Ray and IR-Mid-R detectors, adequately sensitive to ambient temperatures and environmental conditions, is highly desirable. Therefore, following this path, we present detecting opportunities, based on data of experimental and theoretical investigation of the electronic and optical properties, photocurrent behavior at different bias voltages as well as the reflection for the He-Cd cw laser after irradiation by three different IR laser wavelengths, for recently grown TlPb2BrI4 single crystal with strong anisotropic, two-dimensional (2D) layered structure. The X-ray photoelectron spectroscopy brings data on binding energy values of core levels of TlPb2BrI4 for both as-grown and Ar+-ion-treated crystal surfaces as well as for elucidation of the energy distribution of the valence electronic states. In opposite to well-known IR-detector materials, TlPb2BrI4 crystal surface shows high chemical stability concerning Ar+-ion bombardment. Further, we carry out ab initio band-structure calculations to gain curves of total and partial densities of states and to elucidate the principal optical constants of TlPb2BrI4. The present studies indicate that, in spite of the fact that the TlPb2BrI4 crystal contains two very hazardous/toxic chemical elements, thallium and lead;however, it is chemically stable and reveals very low hygroscopic behavior when being exposed to environmental conditions. © 2022 Elsevier B.V.

关键词： X ray photoelectron spectroscopy

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