Published on 11/10/202511/10/2025 by Environmental Scientists 62 / 100 Powered by Rank Math SEO SEO Score Ms. Asma Rehman | Catalysis | Best Review Paper Award Researcher | University of Agriculture Faisalabad | Pakistan Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI. Asma Rehman | Catalysis | Best Review Paper Award
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Ms. Asma Rehman is a dedicated researcher in chemistry whose work bridges green chemistry, organocatalysis, polymer degradation, and artificial intelligence–driven process optimization. With a strong academic foundation from the University of Agriculture, Faisalabad, and Government College University, Faisalabad, she focuses on sustainable catalytic methods for polymer waste valorization and environmental remediation. Her research integrates benign organocatalysts with data-driven modeling to enhance the controlled degradation and upcycling of polystyrene, aligning with global sustainability initiatives. Through the application of machine learning and response surface methodology, she develops predictive models for optimizing reaction parameters and designing eco-efficient processes. Beyond her academic pursuits, Ms. Asma Rehman has contributed to several high-impact publications in reputed journals, addressing themes such as photocatalysis, wastewater treatment, and circular economy approaches to plastic waste management. She has participated in multiple international seminars, conferences, and e-courses on artificial intelligence, biostatistics, and academic writing, demonstrating her commitment to interdisciplinary learning. Alongside her research, she has served as a chemistry teacher and discipline in-charge, fostering scientific curiosity among students. Her technical proficiency spans Python, R Studio, ChemDraw, and machine learning tools, reflecting her analytical and computational expertise. Passionate about sustainability and innovation, Ms. Asma Rehman actively engages in community welfare initiatives and scientific collaborations, striving to contribute to environmentally conscious technological advancements that promote cleaner, smarter, and greener chemical processes for the future. Profile: Orcid
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Featured Publications Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.
Rehman, A., Ahad, A., Majeed, A., Zafar, A., Iqbal, M. A., Ali, S., Batool, M., & Manzoor, F. (2025). A green marriage: The union of theophylline’s catalytic activity and healing potential. RSC Advances. Manzoor, F., Majeed, A., Ibrahim, A. H., Iqbal, M. A., Rehman, A., Aziz, S., Shahzadi, A., Fatima, S., Ejaz, S., & Zafar, M. S. (2025). Nickel-photoredox catalysis: Merging photons with metal catalysts for organic synthesis. RSC Advances. Rehman, A., Iqbal, M. A., Haider, M. T., & Majeed, A. (2025). Artificial intelligence-guided supervised learning models for photocatalysis in wastewater treatment. AI.