Cited by 154Thermodynamic and Exergetic Analyses of Power and Cooling SystemsHybrid Renewable Energy SystemsIntegrated Energy Systems Optimization

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

Machine learning optimization of a novel geothermal driven system with LNG heat sink for hydrogen production and liquefaction

Mehrenjani, J. Rezazadeh, Gharehghani, A., Sangesaraki, A. Gholizadeh·2022·Energy Conversion and Management

DOI 10.1016/j.enconman.2022.115266

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1016/j.enconman.2022.115266

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Animal Communication: When I'm Calling You, Will You Answer Too?
Vickers, N. J. (2017) · Current Biology · doi:10.1016/j.cub.2017.05.064 · Cited by 1,793
Energy and exergy analysis of hydrogen production by a proton exchange membrane (PEM) electrolyzer plant
Ni, M., Leung, M. K. H., & Leung, D. Y. C. (2008) · Energy Conversion and Management · doi:10.1016/j.enconman.2008.03.018 · Cited by 720
Performance comparison and parametric optimization of subcritical Organic Rankine Cycle (ORC) and transcritical power cycle system for low-temperature geothermal power generation
Shengjun, Z., Huaixin, W., & Tao, G. (2011) · Applied Energy · doi:10.1016/j.apenergy.2011.02.034 · Cited by 719
Thin film electrocatalyst layer for unitized regenerative polymer electrolyte fuel cells
Ioroi, T., Yasuda, K., Siroma, Z., Fujiwara, N., & Miyazaki, Y. (2002) · Journal of Power Sources · doi:10.1016/s0378-7753(02)00466-4 · Cited by 534
Thermal design and optimization
Seshadri, K. (1996) · Energy · doi:10.1016/s0360-5442(96)90000-6 · Cited by 507
Exergetic analysis of various types of geothermal power plants
Yari, M. (2009) · Renewable Energy · doi:10.1016/j.renene.2009.07.023 · Cited by 472
A recent review of waste heat recovery by Organic Rankine Cycle
Mahmoudi, A., Fazli, M., & Morad, M. R. (2018) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2018.07.136 · Cited by 458
Working-fluid selection and thermoeconomic optimisation of a combined cycle cogeneration dual-loop organic Rankine cycle (ORC) system for solid oxide fuel cell (SOFC) waste-heat recovery
Emadi, M. A., Chitgar, N., Oyewunmi, O. A., & Markides, C. N. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.114384 · Cited by 349
Multi-objective design optimization of a multi-generation energy system based on geothermal and solar energy
Alirahmi, S. M., Dabbagh, S. R., Ahmadi, P., & Wongwises, S. (2020) · Energy Conversion and Management · doi:10.1016/j.enconman.2019.112426 · Cited by 303
Exergoeconomic and environmental analyses of CO2/NH3 cascade refrigeration systems equipped with different types of flash tank intercoolers
Mosaffa, A. H., Farshi, L. G., Ferreira, C. A. I., & Rosen, M. A. (2016) · Energy Conversion and Management · doi:10.1016/j.enconman.2016.03.053 · Cited by 275

Show all 51 references

Research works printed but not linked: 1

“Turton R, Bailie RC, Whiting WB, Shaeiwitz JA. Analysis,... - Google Scholar.” https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=+Turton+R%2C+Bailie+RC%2C+Whiting+WB%2C+Shaeiwitz+JA.+Analysis%2C+synthesis+and+design+of+chemical+processes.+Pearson+Education%3B+2009.&btnG= (accessed Oct. 09, 2021).

Sorted by citations

Items 101–154 of 154

Thermal/econmic/environmental considerations in a multi-geneation layout with a heat recovery process; A multi-attitude optimization based on ANN approach
Du, G., Wei, H., Singh, P. K., Dutta, A. K., Abdullaeva, B. S., Fouad, Y., Alkhalaf, S., Alkhayyat, A. H., & Deifalla, A. F. (2024) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2024.104170 · Cited by 7
Development of a geothermal-driven multi-output scheme for electricity, cooling, and hydrogen production: Techno-economic assessment and genetic algorithm-based optimization
Guo, X., Abed, A. M., Alghassab, M. A., Alhomayani, F. M., Mahariq, I., Elmasry, Y., Safi, M. S., Alturise, F., Alkhalaf, S., & Alrawashdeh, A. I. (2024) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2024.105228 · Cited by 7
A machine learning-optimized multi-generation system for sustainable electricity, water, hydrogen, and CO2 utilization
Mehrenjani, J. R., & Gharehghani, A. (2025) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2025.151264 · Cited by 7
Self-citation
Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach
Osman, H., Amari, A., Samad, S., Sadeq, A. M., Mahariq, I., Atamurotov, F., & Safarova, L. (2025) · Thermal Science and Engineering Progress · doi:10.1016/j.tsep.2025.104071 · Cited by 6
Intelligent optimization of eco-friendly H2/freshwater production and CO2 reduction layout integrating GT/rankine cycle/absorption chiller/TEG unit/PEM electrolyzer/RO section
Li, S., Leng, Y., Nutakki, T. U. K., Abdullaev, S. S., Fouad, Y., & Alhadrawi, M. (2024) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2024.06.062 · Cited by 6
Assessment and optimization of an integrated hydrogen liquefaction system utilizing solar energy and LNG cold energy
Yang, F., Wang, C., Jiang, W., Qiao, Y., Lv, Y., & Song, W. (2026) · Renewable Energy · doi:10.1016/j.renene.2025.125173 · Cited by 5
Multi-objective optimisation of a geothermal-liquefied natural gas combined organic Rankine cycle system under different distribution pressures
Zhang, H., Cavazzini, G., Zanetti, G., & Benato, A. (2025) · Energy Conversion and Management · doi:10.1016/j.enconman.2025.119554 · Cited by 5
An intelligent data-driven investigation and optimization integrated with an eco-friendly thermal design approach for a marine diesel engine to study its waste-to-liquefied hydrogen generation potential
Yan, C., Mohammed, K. J., Farouk, N., Alghassab, M. A., Zhou, X., Abdullaev, S. S., Dutta, A. K., Mahariq, I., Alharbi, F. S., & Knani, S. (2024) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2024.06.100 · Cited by 4
Thermo-environmental multi- investigation and ANN-based optimization of a novel heat integration criteria system integrated with a marine engine generating liquefied hydrogen
Nutakki, T. U. K., Alghassab, M. A., Dutta, A. K., Abdullaeva, B. S., Alkhalaf, S., Alharbi, F. S., Ghandour, R., Barakeh, Z. A., & Knani, S. (2024) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2024.104240 · Cited by 4
Comprehensive evaluation of energy consumption in LNG liquefaction plants and investigation of energy saving optimization
Shen, K., Wang, J., & Chen, L. (2025) · Fuel · doi:10.1016/j.fuel.2025.135301 · Cited by 3
Investigation of the cascade utilization of LNG cold energy using total site heat integration method
Ji, M., Zhao, Y., Li, Z., Han, D., Wang, B., Pan, T., Chen, Y., & Yang, X. (2025) · Thermal Science and Engineering Progress · doi:10.1016/j.tsep.2025.104209 · Cited by 3
A Review of Hydrogen Strategies in South, Southeast, and Southwest Asia: National Outlooks and Collaboration Opportunities for Canada
Ghorbani, B., Zendehboudi, S., Bagheri, M., Saady, N. M. C., Albayati, T. M., & Venkatachalam, P. (2026) · Energy & Fuels · doi:10.1021/acs.energyfuels.5c04988 · Cited by 3
Biogas–geothermal heat integration with post-combustion CO2 capture for power generation, multi-level cooling, and desalination: Exergoeconomic–environmental assessment and optimization
Chaudhry, I. A., Basem, A., Soliman, N. F., Singh, P., Khaliq, A., Dahari, M., Samandarov, B., Ibragimova, S., Makharov, K., Mahariq, I., et al. (2026) · Thermal Science and Engineering Progress · doi:10.1016/j.tsep.2026.104757 · Cited by 3
Multi-objective optimisation of ORC–LNG systems using the novel One-shot Optimisation method
Zhang, H., Cavazzini, G., & Benato, A. (2024) · Energy · doi:10.1016/j.energy.2024.133629 · Cited by 3
A multi-criteria data-driven study/optimization of an innovative eco-friendly fuel cell-heat recovery process, generating electricity, cooling and liquefied hydrogen
Hai, T., Sharma, K., Mahariq, I., El-Shafai, W., Fouad, H., & Sillanpää, M. E. T. (2024) · Energy · doi:10.1016/j.energy.2024.134079 · Cited by 3
Applying artificial intelligence for forecasting behavior in a liquefied hydrogen unit
Jing, D., Abed, A. M., Patel, P., Arunkumar, D. T., Aulakh, D., Salah, B., & Mahariq, I. (2025) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2025.02.349 · Cited by 3
Innovative energy-saving and simplified hydrogen liquefaction system using LNG cold energy
Fu, L., Yue, J., Chen, X., & Shen, B. (2026) · Energy · doi:10.1016/j.energy.2026.140094 · Cited by 2
Methane-fueled gas turbine with hydrogen blending and integrated steam Rankine cycle, absorption refrigeration cycle, PEM electrolyzer, and a CO2 separation unit
Abouzied, A., Balla, H. H. A., Alkhatib, O. J., Abokhalil, A. G., Dahari, M., Ahmed, M. A., Bayhan, Z., Alrasheed, D. S., Fouad, Y., & Mahariq, I. (2026) · Fuel · doi:10.1016/j.fuel.2026.139882 · Cited by 2
Hydrogen-to-Ammonia Green Fuel Production via Haber–Bosch Process in a Solar–Wind Poly-Generation System: Design, Intelligent Optimization, and 4E Analysis
Alkhatib, O. J., Basem, A., Balla, H. H. A., Alanazi, M., Albaijan, I., Albalawi, H., Ali, H. E., Jastaneyah, Z., Fouad, Y., & Mahariq, I. (2026) · Fuel · doi:10.1016/j.fuel.2026.140153 · Cited by 2
Integrated biomass–geothermal system for decarbonized ammonia production enhanced by a supercritical CO2 cycle: a data-driven approach
Slimene, M. B., Basem, A., Farouk, N., Hasan, M. A., Khlifi, M. A., Islam, S., Atamuratova, Z. A., Mukhitdinov, O., Khudoynazarov, E., & Mahariq, I. (2026) · Fuel · doi:10.1016/j.fuel.2026.140022 · Cited by 2
Comparative Analysis of a Novel System Integrating ORC, Hydrogen Production, and Seawater Desalination with LNG Cold Energy: Energy, Economic, and Environmental Analyses
Chen, C., Mu, H., Li, N. J., Zhao, X., Song, Y., & Wang, H. (2023) · Energy & Fuels · doi:10.1021/acs.energyfuels.3c02647 · Cited by 2
Waste to hydrogen: Investigation of different loads of diesel engine exhaust gas
Ata, S., Kahraman, A., ŞAHİN, R., & Aksoy, M. (2024) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2024.09.443 · Cited by 2
Effective and Realistic Strategies for Large-Scale Liquid Hydrogen Production
Yang, J. G., & Li, Y. (2025) · Cryo · doi:10.3390/cryo1020008 · Cited by 3
Employing cooling/power cycle in a sustainable geothermal scheme integrated desalinated water-based H2 production/liquefaction; AI-aided multi-facet optimization and economic examination
Yin, T., Chang, L., Salih, S. Q., Almadhor, A. S., Shaban, M., El-Zahar, E. R., Dutta, A. K., Abdullaeva, B. S., Ali, H. E., & Albalawi, H. M. (2025) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2025.06.016 · Cited by 1
Investigation of an integrated clean energy system using heat recovery from fuel cell and LNG expansion waste heat combined with solar energy
Khanmohammadi, S., Khanjani, S., & Chaghakaboodi, H. A. (2025) · Environmental Progress & Sustainable Energy · doi:10.1002/ep.70029 · Cited by 1
Optimization of Cold, Heat, Power and Carbon Quadruple Synergistic System with Green Ammonia in LNG
Yu, R., Pan, Z., Liu, Z., Qiu, Y., Deng, W., & Yu, J. (2026) · Energy & Fuels · doi:10.1021/acs.energyfuels.6c00788 · Cited by 1
Dynamic simulation and multi-objective optimization of a novel PCM-integrated solar-biomass hybrid system with water harvesting
Balvardi, A. A., Alikhani, M. S., Gharehghani, A., & Mehrenjani, J. R. (2026) · Energy Conversion and Management · doi:10.1016/j.enconman.2026.121380 · Cited by 1
Self-citation
Prior Knowledge-Informed Adaptive Federated Dual Scenario Graph Neural Network for Boil-Off Gas Generation Prediction
Wang, Y., Liu, G., Chen, L., Zhang, C., Yu, M., & Gui, Y. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.114663 · Cited by 1
An optimum liquified hydrogen production by hybrid wind–geothermal green energies by using MPSO algorithm
Akbari, S., Esfahani, J. A., & Miri, S. M. (2026) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2026.155118 · Cited by 1
ANN evaluation of thermodynamic efficiency, economic and environmental analysis of the geothermal-based electricity and hydrogen production system: A case study
Karabuğa, A., Barutçu, E. İ., Morozova, S., & Utlu, Z. (2026) · Energy · doi:10.1016/j.energy.2026.141505 · Cited by 1
Global advances in biohydrogen production: A systematic review synergizing nanotechnology, genetic engineering, and AI for sustainable energy
Niyazi, S. (2026) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2026.156073 · Cited by 1
Global Trends in PEM Electrolyzer Research Based on Published Articles
Bai, Z., Li, J., Deng, Z., Tan, H., Li, L., Xu, G., Kang, W., & Liu, M. (2024) · Springer proceedings in physics · doi:10.1007/978-981-99-8631-6_5
Innovations and advances of hydrogen liquefaction processes
Sleiti, A. K., & Al‐Ammari, W. A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-21438-7.00008-x
Techno-Economic Performance Evaluation of a Novel Hydrogen Liquefaction System Coupled with Liquefied Natural Gas Gasification as ByproductPreprint
Li, T., Zhang, Y., Qiao, Y., Yu, H., & Yuan, Y. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4816321
Research on Rural Integrated Energy Systems with Economic-Energy Efficiency Synergistic OptimizationPreprint
Liu, Q., Wu, L., Zhou, N., Peng, X. L., Zhao, J. H., Huo, Q., & Wei, T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5266809
Determination of hydrogen production in power plant using predictive machine learning methods
Ma, L., & Yuan, K. (2025) · Chemical Product and Process Modeling · doi:10.1515/cppm-2025-0010
Comparative analysis of single-objective and multi-objective optimization methods for geothermal-LNG integrated Rankine cycles
Zhang, H., Li, Y., & Zheng, J. (2025) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2025.101195
Implementing machine learning solutions in hydrogen projects
Poudel, S., Baniya, S., Zafirakou, A., Angove, M. J., & Paudel, S. R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34090-1.00018-x
Catalytic methane decomposition via nickel–mesoporous silica nanoparticle KIT6 catalyst for hydrogen production: A machine learning perspective
Fauzi, A. S. A., Khajavian, M., Noh, T. U., Ismail, S. B., Bakar, M. Z. A., & Hamid, N. A. (2025) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2025.151975
Enhancing energy efficiency with a photovoltaic-based multi-product system with integration of electrolysis and desalination
Huang, Q. (2025) · Chemical Product and Process Modeling · doi:10.1515/cppm-2025-0149
Dynamic modeling, predictive control, and optimization of a multi-scenario CCHP-PV-hydrogen energy system with integrated carbon capture using machine learning algorithms
Nasrabadi, A. M., & Mehrenjani, J. R. (2025) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2025.108235
Self-citation
Multi-objective optimisation and comparison of solar-liquefied natural gas expansion cycle combined organic Rankine cycles under three distribution pressures
Zhang, H., & Mao, H. (2025) · Energy · doi:10.1016/j.energy.2025.139788
Comparative optimization and exergy analysis of solar–LNG integrated Rankine cycles among different hot tank outlet temperatures
Zhang, H., & 毛慧明 (2026) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2026.101609
Intelligent Decision-Making for Energy Dispatch in Lng Receiving Stations: High-Precision Prediction Models and Adaptive Energy Efficiency OptimizationPreprint
dong, C., Ji, Z., Zhu, M. Q., Chen, R., Ma, L., Chang, C., & Wu, X. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5391509
Ensemble empirical mode decomposition and sample entropy-based adaptive boosting model for solar radiation forecasting for enhanced hydrogen production and carbon dioxide mitigation
Liu, X., Liu, E., Wang, X., Wang, S., Feng, Z., Gu, H., 丁攀, & Shao, L. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.114655
A carbon-managed oxy-fuel multigeneration system using municipal solid waste for electricity, hydrogen, and ammonia production: ANN-assisted multi-objective optimization
Slimene, M. B., Basem, A., Soliman, N. F., Singh, P. K., Khlifi, M. A., Ruzmetov, A., Uljayev, U., Ibragimova, S., Mahariq, I., & Fouad, Y. (2026) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2026.156111
Bibliometric Analysis of Studies on "Machine Learning in Geothermal Energy"
Teke, O. (2025) · Kastamonu University Journal of Engineering and Sciences · doi:10.55385/kastamonujes.1783433
Artificial intelligence in thermal-fluid systems: Data-driven modeling, optimization, and intelligent control — A comprehensive review
Zhang, W., Liu, J., Sun, H., Zhang, T., Kreschel, M., & Liu, L. (2026) · AI Thermal Fluids · doi:10.1016/j.aitf.2026.100045
Research on Rural Integrated Energy Systems With Economic–Energy Efficiency Synergistic Optimisation
Liu, Q., Wu, L., Liang, Y., Zhou, N., Peng, X., Zhao, J., Huo, Q., & Wei, T. (2026) · IET Energy Systems Integration · doi:10.1049/esi2.70054
A decarbonization pathway based on a biogas-fueled multigeneration system with ammonia as an energy carrier: Techno-economic analysis and machine learning optimization
Khaliq, A., Farouk, N., Khan, M. N., Singh, P. K., Soliman, N. F., Seytnazarov, M., Saydullaev, B., Siddikov, R., Mahariq, I., & Fouad, Y. (2026) · Fuel · doi:10.1016/j.fuel.2026.140893
Cryogenic upgrading of coke oven gas for LNG, power, and liquid hydrogen production: Thermodynamic, economic, and environmental assessment
Yan, Z., Jasim, D. J., Khan, M., Singh, P. K., Ullah, R. H., Liu, J., Alshehery, S., & Alqahtani, M. (2026) · International Communications in Heat and Mass Transfer · doi:10.1016/j.icheatmasstransfer.2026.112322
A novel municipal solid waste–driven energy conversion system with a molten carbonate fuel cell for power, cooling, and freshwater: Thermo-economic and environmental optimization
Chaudhry, I. A., Ali, A. B. M., Soliman, N. F., Singh, P. K., Khaliq, A., Madaminov, S., Sotvoldiav, D., Abdumalikovich, B. E., Mahariq, I., & Fouad, Y. (2026) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2026.132832
Renewable-driven green hydrogen-to-ammonia cogeneration via the Haber–Bosch loop with LNG cold-energy recovery: Techno-economic optimization using ANN-assisted MOGWO
Alotaibi, T. S. (2026) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2026.157823
Environmental and economic viability of a solar-driven multigeneration system with thermal energy storage for sustainable coastal development: A hybrid data-driven approach with a comparative case study
Ahmad, A., Khan, M. N., Abdullah, K. A., Alshahrani, S., Alshehery, S., Ullah, R. H., Soliman, N. F., & Sarvarbek, Y. (2026) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2026.109682

Authors: Mehrenjani, J. R., Gharehghani, A., & Sangesaraki, A. G.
Affiliations: Iran University of Science and Technology (IR)
Corresponding author: Gharehghani, A.
ORCID: Mehrenjani, J. Rezazadeh
Gharehghani, A.
Venue: Energy Conversion and Management
Publisher: Elsevier BV
Published: 2022-02
Volume: 254
Pages: 115266
ISSN: 0196-8904 (ISSN-L)
DOI: 10.1016/j.enconman.2022.115266
OpenAlex: W4224288113
Cited by: 154
References: 51
Citations by year: 2026: 24 · 2025: 40 · 2024: 37 · 2023: 37 · 2022: 16
FWCI: 12.26
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Energy Conversion and Management (publishedVersion)
Topics: Physical Sciences › Engineering › Mechanical Engineering › Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Physical Sciences › Energy › Energy Engineering and Power Technology › Hybrid Renewable Energy Systems
Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
Keywords: geothermal energy, liquefied natural gas, hydrogen production, hydrogen liquefaction, Claude cycle, proton exchange membrane electrolyzer, LNG vaporizer, exergy analysis, multi-objective optimization, artificial neural networks, genetic algorithm, levelized cost of hydrogen

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Machine learning optimization of a novel geothermal driven system with LNG heat sink for hydrogen production and liquefaction

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks