Design of Wiring Harness and Performance Analysis of Powertrain Using Matlab and E-Cad for Electric Vehicle

A.T. Ashmi Christus; M.  Vinothkumar; M.  Hemnath; S. Mohamed  Vapik; M. Mohamed Sameer  Ali; B.  Vaidianathan

doi:10.51699/cajotas.v6i3.1565

A.T. Ashmi Christus Dhaanish Ahmed College of Engineering, Padappai, Chennai, Tamil Nadu, India
M. Vinothkumar Dhaanish Ahmed College of Engineering, Padappai, Chennai, Tamil Nadu, India
M. Hemnath Dhaanish Ahmed College of Engineering, Padappai, Chennai, Tamil Nadu, India
S. Mohamed Vapik Dhaanish Ahmed College of Engineering, Padappai, Chennai, Tamil Nadu, India
M. Mohamed Sameer Ali Dhaanish Ahmed College of Engineering, Padappai, Chennai, Tamil Nadu, India
B. Vaidianathan Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India

DOI: https://doi.org/10.51699/cajotas.v6i3.1565

Keywords: zero-emission vehicles; automotive electrification; vehicle electrical harnesses; computer-aided design (cad); electromagnetic compatibility; current type and manufacturability; wire harness design

Abstract

In this work, we aim to design the electrical harness of an electric vehicle, which serves as the crucial network that connects all components within the vehicle. The primary objective is to ensure that the harness is designed to optimize cost, serviceability, and safety during vehicle operation. To achieve this, we use AutoCAD Electrical software, which allows for precise and systematic layout of the wiring harness. Designing a vehicle involves several complex calculations, including those related to fuel economy, vehicle dynamics, transmission configurations, motor sizing and its control strategies, motor performance mapping, and battery capacity sizing. These calculations are essential for ensuring optimal performance and efficiency. For accurate evaluation, we employ Excel spreadsheets to carry out powertrain sizing calculations. This process helps in identifying the required capacity of both the battery pack and the motor suitable for the vehicle. Additionally, we utilize MATLAB Simulink software to simulate and analyze the electric vehicle's overall performance. By integrating these tools, we can evaluate the system's efficiency and functionality during the design and testing stages. This method allows us to make necessary adjustments and optimize the vehicle's performance before moving to large-scale production, reducing the risks and costs associated with design errors.

Downloads

Download data is not yet available.

References

E. Y. Fedorov, V. S. Tereshchuk, and A. V. Ferenetz, “Wiring of complicated electrical circuits of interblock assembling in automated design of aircraft,” Russ. Aeronaut., vol. 58, no. 1, pp. 96–99, 2015.

A. Ferenets and E. Fedorov, “Computer-aided design of power supply systems of vehicles,” Machines, Technologies, Materials, vol. 2, no. 2, pp. 59-60, 2016.

E. Fedorov and A. Gorodnov, “Software Instruments for Computer-Aided Design Onboard Cable Network of the Aircraft,” International Journal of Applied Engineering Research, vol. 11, no. 16, pp. 9047–9051, 2016.

C. Y. Lee, “An algorithm for path connections and its applications,” IEEE Trans. Electron. Comput., vol. EC-10, no. 3, pp. 346–365, 1961.

P. Hart, N. Nilsson, and B. Raphael, “A formal basis for the heuristic determination of minimum cost paths,” IEEE Trans. Syst. Sci. Cybern., vol. 4, no. 2, pp. 100–107, 1968.

V. Rajavel, "Integrating power-saving techniques into design for testability of semiconductors for power-efficient testing," The American Journal of Engineering and Technology, vol. 7, no. 3, pp. 243–251, 2025.

V. Rajavel, "Novel machine learning approach for defect detection in DFT processes," ASRJETS-Journal, vol. 101, no. 1, pp. 325–334, Apr. 2025. [Online].

V. Rajavel, "Optimizing semiconductor testing: Leveraging stuck-at fault models for efficient fault coverage," Int. J. Latest Eng. Manag. Res. (IJLEMR), vol. 10, no. 2, pp. 69–76, Feb. 2025.

Md S. Miah and Md S. Islam, "Big Data Analytics Architectural Data Cut off Tactics for Cyber Security and Its Implication in Digital forensic," in Proc. 2022 Int. Conf. Futuristic Technol. (INCOFT), Belgaum, India, 2022, pp. 1–6.

M. A. Obaida, Md S. Miah, and Md. A. Horaira, “Random Early Discard (RED-AQM) Performance Analysis in Terms of TCP Variants and Network Parameters: Instability in High-Bandwidth-Delay Network,” Int. J. Comput. Appl., vol. 27, no. 8, pp. 40–44, Aug. 2011.

A. Srivastava, “Use of AI/ML in Data Security,” J. Artif. Intell. Mach. Learn. Data Sci., vol. 2, no. 2, pp. 1–3, 2024.

A. Srivastava, “WFH Impact on Work Culture and Future of Work Place,” Int. J. Innov. Res. Creat. Technol., vol. 8, no. 6, pp. 1–8, Nov. 2020.

G. Kashyap, "Neural Architecture Search (NAS): Exploring the Trade-Offs In Automated Model Design and Its Impact on Deep Learning Performance," Int. J. Innov. Res. Eng. Multidiscip. Phys. Sci., vol. 13, no. 2, pp. 1–12, Mar.–Apr. 2025.

G. Kashyap, "Large Language Models and Their Ethical Implications: The role of models like GPT and BERT in shaping future AI applications and their risks," Int. J. Innov. Res. Creat. Technol., vol. 6, no. 6, pp. 1–5, Dec. 2020.

G. Kashyap, "AI for Epidemiology: Using AI to Predict and Track the Spread of Diseases like COVID-19," Int. J. Innov. Res. Multidiscip. Field, vol. 3, no. 6, pp. 1–10, Nov. 2021.

G. Kashyap, "AI for Threat Detection and Mitigation: Using AI to Identify and Respond to Cybersecurity Threats in Real-Time," Int. J. Sci. Res. Eng. Manag. Sci., vol. 6, no. 6, pp. 1–5, Nov. 2024.

G. Kashyap, "AI for Information Retrieval: Advancements in Search Engines and Chatbots through Deep Learning-Based Query Understanding," Int. J. Innov. Res. Creat. Technol., vol. 7, no. 1, pp. 1–7, Jan. 2021.

G. Kashyap, "Multilingual NLP: Techniques for Creating Models that Understand and Generate Multiple Languages with Minimal Resources," Int. J. Sci. Res. Eng. Manag. Sci., vol. 6, no. 12, pp. 1–5, Dec. 2024.

B. Chandrashekar, S. Boggavarapu, S. Pundir, C. Yosepu, S. Chepyala and G. Manikandan, "Machine Learning Prediction Approach For Financial Forecast System In Stock Exchange Marketing Management," 2023 6th International Conference on Contemporary Computing and Informatics (IC3I), Gautam Buddha Nagar, India, 2023, pp. 1433–1438.

S. Boggavarapu, G. Ramkumar, P. R. Gedamkar, A. Kaneria, S. Pundir and R. Selvameena, "Research on Unmanned Artificial Intelligence Based Financial Volatility Prediction in International Stock Market," 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST), Jamshedpur, India, 2024, pp. 16–20.

S. Gokulakrishnan, P. Chakrabarti, B. T. Hung, et al., "An optimized facial recognition model for identifying criminal activities using deep learning strategy," International Journal of Information Technology, vol. 15, pp. 3907–3921, 2023.

S. N. V. J. D. Kosuru, R. Praveen Kumar, R. Kumar, S. Gokulakrishnan, A. Sethy, and V. Sreenivas, “A comparative assessment for examining the performance of reconfigurable multiband MIMO antennas for communication systems,” J. Inf. Syst. Eng. Manag., vol. 10, no. 10s, 2025.

R. Kumar, S. Gokulakrishnan, S. N. V. J. D. Kosuru, R. Praveen Kumar, and R. T. Radha, “An efficient fuzzy logic and artificial intelligence based optimization strategy for big data healthcare system,” Edelweiss Appl. Sci. Technol., vol. 9, no. 3, 2025.

S. Gokulakrishnan and J. M. Gnanasekar, “Efficient and privacy for data integrity and data replication in cloud computing,” Int. J. Innov. Technol. Explor. Eng., 2019.

A. Chahal et al., “Systematic analysis based on Conflux of machine learning and internet of things using bibliometric analysis,” Journal of Intelligent Systems and Internet of Things, vol. 13, no. 1, pp. 196–224, 2024.

A. K. Tyagi and S. R. Addula, “Artificial Intelligence for malware analysis,” Artificial Intelligence‐Enabled Digital Twin for Smart Manufacturing, pp. 359–390, Sep. 2024.

A. Pati et al., “Artificial Intelligence in improving disease diagnosis,” Artificial Intelligence in Medicine and Healthcare, pp. 24–49, Jan. 2025.

G. S. Nadella et al., “Generative AI-Enhanced Cybersecurity Framework for Enterprise Data Privacy Management,” Computers, vol. 14, no. 2, p. 55, Feb. 2025.

G. S. Sajja and S. R. Addula, “Automation using robots, machine learning, and artificial intelligence to enhance production and quality,” 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES), pp. 1–4, Nov. 2024.

N. K. Misra, S. Das, S. Satpathy, S. R. Addula, and M. C. Trivedi, “Covid-19 pandemic: A worldwide critical review with the machine learning model-based prediction,” Journal of The Institution of Engineers (India): Series B, vol. 106, no. 1, pp. 339–349, Sep. 2024.

S. Almotairi et al., “Personal data protection model in IOMT-blockchain on secured bit-count transmutation data encryption approach,” Fusion: Practice and Applications, vol. 16, no. 1, pp. 152–170, 2024.

S. Dontu, S. R. Addula, P. Kumar Pareek, R. Vallabhaneni and M. H. Fallah, "A Feature Selection based Decisive Red Fox Algorithm with Deep Learning for Protecting Cybersecurity Network," 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2024, pp. 1-7.

S. Dontu, S. R. Addula, P. Kumar Pareek, R. Vallabhaneni and M. M. Adnan, "Attack Detection from Internet of Things using TPE based Self-Attention based Bidirectional Long-Short Term Memory," 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2024, pp. 1-6.

S. Menon et al., “Streamlining task planning systems for improved enactment in contemporary computing surroundings,” SN Computer Science, vol. 5, no. 8, Oct. 2024.

S. R. Addula and A. K. Tyagi, “Future of computer vision and industrial robotics in smart manufacturing,” Artificial Intelligence‐Enabled Digital Twin for Smart Manufacturing, pp. 505–539, Sep. 2024.

S. R. Addula and G. S. Sajja, “Automated machine learning to streamline data-driven industrial application development,” 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES), pp. 1–4, Nov. 2024.

S. R. Addula, A. K. Tyagi, K. Naithani, and S. Kumari, “Blockchain‐empowered internet of things (IoTs) platforms for automation in various sectors,” Artificial Intelligence‐Enabled Digital Twin for Smart Manufacturing, pp. 443–477, Sep. 2024.

S. R. Addula, K. Meduri, G. S. Nadella, and H. Gonaygunta, “AI and Blockchain in Finance: Opportunities and Challenges for the Banking Sector,” IJARCCE, vol. 13, no. 2, Feb. 2024.

S. R. Addula, U. Mamodiya, W. Jiang, and M. A. Almaiah, “Generative AI-Enhanced Intrusion Detection Framework for secure healthcare networks in Manets,” SHIFRA, vol. 2025, pp. 62–68, Feb. 2025.

S. S. Nair, G. Lakshmikanthan, N. Belagalla, S. Belagalla, S. K. Ahmad and S. A. Farooqi, "Leveraging AI and Machine Learning for Enhanced Fraud Detection in Digital Banking System: A Comparative Study," 2025 First International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), Bhimtal, Nainital, India, 2025, pp. 1278-1282.

S. S. Nair, G. Lakshmikanthan, J.ParthaSarathy, D. P. S, K. Shanmugakani and B.Jegajothi, "Enhancing Cloud Security with Machine Learning: Tackling Data Breaches and Insider Threats," 2025 International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India, 2025, pp. 912-917.

R. Aravindhan, R. Shanmugalakshmi, K. Ramya and Selvan C., "Certain investigation on web application security: Phishing detection and phishing target discovery," 2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2016, pp. 1-10.

R. Aravindhan and R. Shanmugalakshmi, "Comparative analysis of Web 3.0 search engines: A survey report," 2013 International Conference on Advanced Computing and Communication Systems, Coimbatore, India, 2013, pp. 1-6.

R. Aravindhan, R. Shanmugalakshmi, and K. Ramya, "Circumvention of nascent and potential Wi-Fi phishing threat using association rule mining," Wireless Personal Communications, vol. 94, no. 3, pp. 2331–2361, 2017.

R. Aravindhan and R. Shanmugalakshmi, "Visual analytics for semantic based image retrieval (SBIR): semantic tool," International Journal of Latest Trends in Engineering and Technology, vol. 7, no. 2, pp. 300–312, 2016.

R. Aravindhan and R. Shanmugalakshmi, "Multistage fuzzy classifier based phishing detection using LDA and CRF features followed by impersonated entity discovery," International Journal of Control Theory and Applications, vol. 10, no. 29, pp. 33–42, 2017.

C. Selvan, A. Ragunathan, and U. M. Ashwinkumar, "Mitigating phishing threats in unmanned aircraft systems (UAS) through multi-stage defense strategies," in Analyzing and Mitigating Security Risks in Cloud Computing, IGI Global, 2024, pp. 125–162.

G. Lakshmikanthan, S. S. Nair, J. Partha Sarathy, S. Singh, S. Santiago and B. Jegajothi, "Mitigating IoT Botnet Attacks: Machine Learning Techniques for Securing Connected Devices," 2024 International Conference on Emerging Research in Computational Science (ICERCS), Coimbatore, India, 2024, pp. 1-6.

G. Lakshmikanthan and S. S. Nair, "Zero trust architecture: Redefining security parameters for remote-first organizations," International Research Journal of Modernization in Engineering Technology and Science, vol. 2, no. 3, pp. 1003–1013, 2020.

S. Sreekandan Nair and G. Lakshmikanthan, “Open Source Security: Managing Risk in the Wake of Log4j Vulnerability”, International Journal of Emerging Trends in Computer Science and Information Technology, vol. 2, no. 4, pp. 33–45, Nov. 2021.

T. S. Chu, S. S. Nair, and G. Lakshmikanthan, "Network intrusion detection using advanced AI models: A comparative study of machine learning and deep learning approaches," Int. J. Commun. Netw. Inf. Secur., vol. 14, no. 2, pp. 359–365, Aug. 2022.

S. Gokulakrishnan and J. M. Gnanasekar, “Data integrity and recovery management in cloud systems,” in Proc. 4th Int. Conf. Inventive Syst. Control (ICISC), Coimbatore, India, 2020, pp. 645–648.

Z. H. Jaber, M. Ihsan, S. Gokulakrishnan, H. A. Alshaibani, F. H. Alsalamy, and H. Al-Aboudy, “Distributed self-localization with improved optimization with machine learning in IoT applications,” in Proc. Asian Conf. Commun. Netw. (ASIANComNet), 2024.

G. Parasa, D. K. Nayak, A. Gangopadhyay, M. Stanlywit, S. Gokulakrishnan, and P. Sharma, “Exploring the role of artificial intelligence in enhancing chatbot functionality,” in Proc. Int. Conf. Adv. Comput., Commun. Netw. (ICAC2N), 2024.

M. A. Mookambal and S. Gokulakrishnan, “Potential subscriber detection using machine learning,” in Proc. ICIPCN 2020, J. I. Z. Chen, J. M. R. S. Tavares, S. Shakya, and A. M. Iliyasu, Eds., Adv. Intell. Syst. Comput., vol. 1200, Springer, Cham, 2021, pp. 425–435.

S. Boggavarapu, G. S. Navale, G. Manikandan, N. Senthamilarasi, K. Lakshminarayana and H. R. Goyal, "A Novel Intelligent AI with Automated Defense Attack Data Privacy System Design," 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST), Jamshedpur, India, 2024, pp. 99–104.

S. Boggavarapu, S. S. Ali, G. Manikandan, R. Mohanraj, D. P. Singh and R. R, "Flying Neural Network-Based Optimistic Financial Early Alert System in AI Model," 2023 6th International Conference on Contemporary Computing and Informatics (IC3I), Gautam Buddha Nagar, India, 2023, pp. 1367–1373.

F. Ahamed, S. Biswal, S. Sekhar Nanda, S. Pundir, T. Soubhari and S. Boggavarapu, "Intelligent Unmanned AI Detection Model for Financial Volatility in Stock Exchange," 2023 6th International Conference on Contemporary Computing and Informatics (IC3I), Gautam Buddha Nagar, India, 2023, pp. 1422–1426.

K. Sridhar, A. R. Yeruva, P. N. Renjith, A. Dixit, A. Jamshed, and R. Rastogi, "Enhanced Machine learning algorithms Lightweight Ensemble Classification of Normal versus Leukemic Cel," Journal of Pharmaceutical Negative Results, vol. 13, no. s9, pp. 496–505, 2022.

N. S. Patil, S. M. Patil, C. M. Raut, A. P. Pande, A. R. Yeruva, and H. Morwani, "An Efficient Approach for Object Detection using Deep Learning," Journal of Pharmaceutical Negative Results, vol. 13, no. s9, pp. 563–572, 2022.

A. Srivastava, “Impact of AI on Social Media and its Implication Mental Health,” Int. J. Sci. Res. Eng. Manag., vol. 7, no. 7, 2023.

A. Srivastava, “WFH Impact on Work Culture and Future of Work Place,” Int. J. Innov. Res. Creat. Technol., vol. 8, no. 6, pp. 1–8, 2022.

R. Vadisetty and A. Polamarasetti, “Quantum Computing For Cryptographic Security With Artificial Intelligence,” in 2024 12th International Conference on Control, Mechatronics and Automation (ICCMA), 2024, pp. 252–260.

R. Vadisetty and A. Polamarasetti, “AI-Augmented Skill Development Roadmaps: Tailoring 12-Month Learning Paths for Future-Ready Careers in Education 4.0 and Industry 4.0,” in 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART), 2024, pp. 655–661.

U. K. Lilhore, V. Dutt, T. A. Kumar, M. Margala, and K. Raahemifar, Math Optimization for Artificial Intelligence: Heuristic and Metaheuristic Methods for Robotics and Machine Learning. De Gruyter, 2025.

M. S. Dr. Dilipkumar A. Ode, J. D. K. Dr. Krishnendu Roy, M. M. C. Dr. Birajlakshmi Ghosh, and R. S. Dr. Amar Baliram Abhrange, AI & Chatgpt Tools For Teaching Learning Process. Redshine Publication, 2024.

R. Vadishetty, “Efficient Deep Fake Detection Technique on Video and Audio Dataset Using Deep Learning BT - Proceedings of 5th International Ethical Hacking Conference,” 2025, pp. 137–155.

S. M. Abdulrahman, R. R. Asaad, H. B. Ahmad, A. A. Hani, S. R. Zeebaree, and A. B. Sallow, “Machine learning in nonlinear material physics,” J. Soft Comput. Data Min., vol. 5, no. 1, pp. 122–131, 2024.

S. M. Abdulrahman, A. A. Hani, S. R. Zeebaree, R. R. Asaad, D. A. Majeed, A. B. Sallow, and H. B. Ahmad, “Intelligent home IoT devices: An exploration of machine learning-based networked traffic investigation,” J. Ilm. Ilmu Terapan Univ. Jambi, vol. 8, no. 1, pp. 1–10, 2024.

H. B. Ahmad, R. R. Asaad, S. M. Almufti, A. A. Hani, A. B. Sallow, and S. R. Zeebaree, “Smart home energy saving with big data and machine learning,” J. Ilm. Ilmu Terapan Univ. Jambi, vol. 8, no. 1, pp. 11–20, 2024.

S. M. Almufti, H. B. Ahmad, R. B. Marqas, and R. R. Asaad, “Grey wolf optimizer: Overview, modifications and applications,” Int. Res. J. Sci. Technol. Educ. Manag., vol. 1, no. 1, p. 1, 2021.

S. Almufti, R. Asaad, and B. Salim, “Review on elephant herding optimization algorithm performance in solving optimization problems,” Int. J. Eng. Technol., vol. 7, no. 1, pp. 6109–6114, 2018.

S. Almufti, R. Marqas, and R. Asaad, “Comparative study between elephant herding optimization (EHO) and U-turning ant colony optimization (U-TACO) in solving symmetric traveling salesman problem (STSP),” J. Adv. Comput. Sci. Technol., vol. 8, no. 2, p. 32, 2019.

D. Kodi and S. Chundru, “Unlocking new possibilities: How advanced API integration enhances green innovation and equity,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 437–460.

D. Kodi and B. C. C. Marella, "Fraud Resilience: Innovating Enterprise Models for Risk Mitigation," J. Inf. Syst. Eng. Manag., vol. 10, no. 12S, pp. 683–695, Jan. 2025.

B. C. C. Marella and D. Kodi, “Generative AI for fraud prevention: A new frontier in productivity and green innovation,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 185–200.

A. Palakurti and D. Kodi, “Building intelligent systems with Python: An AI and ML journey for social good,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 77–92.

D. Kodi, "Data Transformation and Integration: Leveraging Talend for Enterprise Solutions," Int. J. Innov. Res. Sci. Eng. Technol., vol. 13, no. 9, p. 13, Sep. 2024.

D. Kodi, "Performance and Cost Efficiency of Snowflake on AWS Cloud for Big Data Workloads," Int. J. Innov. Res. Comput. Commun. Eng., vol. 12, no. 6, p. 14, Jun. 2024.

B. Sallow, R. R. Asaad, H. B. Ahmad, S. M. Abdulrahman, A. A. Hani, and S. R. M. Zeebaree, “Machine learning skills to K–12,” J. Soft Comput. Data Min., vol. 5, no. 1, pp. 132–141, 2024.

B. C. C. Marella and A. Palakurti, “Harnessing Python for AI and machine learning: Techniques, tools, and green solutions,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 237–250.

B. C. C. Marella and D. Kodi, “Generative AI for fraud prevention: A new frontier in productivity and green innovation,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 185–200.

B. C. C. Marella, "Driving Business Success: Harnessing Data Normalization and Aggregation for Strategic Decision-Making," Int. J. Intell. Syst. Appl. Eng., vol. 10, no. 2s, pp. 308–317, Nov. 2022.

B. C. C. Marella, “Data Synergy: Architecting Solutions for Growth and Innovation,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 11, no. 9, pp. 10551–10560, Sep. 2023.

B. C. C. Marella, “From Silos to Synergy: Delivering Unified Data Insights across Disparate Business Units,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 11993–12003, Nov. 2024.

B. C. C. Marella, “Scalable Generative AI Solutions for Boosting Organizational Productivity and Fraud Management,” International Journal of Intelligent Systems and Applications in Engineering, vol. 11, no. 10s, pp. 1013–1023, Aug. 2023.

D. Kodi and M. B. C. Chowdari, “Fraud resilience: Innovating enterprise models for risk mitigation,” Journal of Information Systems Engineering and Management, vol. 10, no. 12s, pp. 683–695, 2024.

V. R. Anumolu and B. C. C. Marella, “Maximizing ROI: The intersection of productivity, generative AI, and social equity,” in Advances in Environmental Engineering and Green Technologies, IGI Global, 2025, pp. 373–386.

I. Aryal, M. Stricklin, D. Behzadirad, W. Branch, A. Siddiqui, and T. Busani, "High-quality dry etching of LiNbO₃ assisted by proton substitution through H₂-plasma surface treatment," Nanomaterials (Basel, Switzerland), vol. 12, no. 16, p. 2836, 2022.

R. L. Paldi, A. Aryal, M. Behzadirad, T. Busani, A. Siddiqui, and H. Wang, "Nanocomposite-seeded single-domain growth of lithium niobate thin films for photonic applications," in Conf. Lasers Electro-Optics, Washington, D.C.: Optica Publishing Group, 2021.

S. M. Z. Shifat, I. Stricklin, R. K. Chityala, A. Aryal, G. Esteves, A. Siddiqui, and T. Busani, "Vertical etching of scandium aluminum nitride thin films using TMAH solution," Nanomaterials (Basel, Switzerland), vol. 13, no. 2, 2023.

R. R. Asaad, S. M. Abdulrahman, and A. A. Hani, “Advanced encryption standard enhancement with output feedback block mode operation,” Acad. J. Nawroz Univ., vol. 6, no. 3, pp. 1–10, 2017.

R. R. Asaad, S. M. Abdurahman, and A. A. Hani, “Partial image encryption using RC4 stream cipher approach and embedded in an image,” Acad. J. Nawroz Univ., vol. 6, no. 3, pp. 40–45, 2017.

A. Hani, A. B. Sallow, H. B. Ahmad, S. M. Abdulrahman, R. R. Asaad, S. R. M. Zeebaree, and D. A. Majeed, “Comparative analysis of state-of-the-art classifiers for Parkinson’s disease diagnosis,” J. Ilm. Ilmu Terapan Univ. Jambi, vol. 8, no. 2, pp. 409–423, 2024.

R. R. Ihsan, S. M. Almufti, B. M. Ormani, R. R. Asaad, and R. B. Marqas, “A survey on cat swarm optimization algorithm,” Asian J. Res. Comput. Sci., vol. 10, no. 2, pp. 22–32, 2021.

S. G. A. Hasan, K. W. Gaines, S. Azharuddin, M. A. N. Khan, and S. S. Fatima, "Study of magnetic nanoparticles (Fe₂O₃ and Fe₃O₄) synthesized by electric ARC-discharge technique," TBEAH, vol. 5, no. 2, pp. 18–24, Oct. 2024.

S. G. A. Hasan, G. A. V. S. S. K. S., B. V. Reddi, and G. S. Reddy, "A critical review on preparation of Fe3O4 magnetic nanoparticles and their potential application," International Journal of Current Engineering and Technology, vol. 8, no.6, pp. 1613-1618, 2018.

S.G.A. Hasan and M.D.A. Rasool, "Preparation and Study of Magnetic Nanoparticles (Fe2O3 and Fe3O4) by Arc-Discharge Technique" ," IJSRSET, vol. 3, no. 2, pp. 730-732, 2017.

S.G.A. Hasan, A. Gupta, and B.V. Reddi, "Effect of Voltage on the Size of Magnetic Nanoparticles Synthesized Using Arc-Discharge Method," Innovations in Mechanical Engineering: Select Proceedings of ICIME 2021, pp. 339-346, 2022.