This paper presents an improved density-functional theory (DFT) approach for calculating adsorption energetics on transition-metal surfaces. The authors propose a revised Perdew-Burke-Ernzerhof (revPBE) functional, which systematically improves the accuracy of chemisorption energies for various adsorbates on Ni(100), Ni(111), Rh(100), Pd(100), and Pd(111) surfaces. The revPBE functional is derived by modifying a parameter in the original PBE functional, leading to better agreement with experimental data. However, the revPBE functional may locally violate the Lieb-Oxford criterion, which is a fundamental constraint in DFT. To address this, an alternative functional, RPBE, is introduced. The RPBE functional achieves the same improvement in chemisorption energies as revPBE while satisfying the Lieb-Oxford criterion locally. The study compares the performance of several DFT functionals, including the Perdew-Wang-91 (PW91), PBE, revPBE, and RPBE, in predicting chemisorption energies for oxygen, CO, and NO on various transition-metal surfaces. The results show that the revPBE and RPBE functionals provide significantly more accurate predictions of chemisorption energies compared to the PW91 and PBE functionals. The root-mean-square deviations for the calculated chemisorption energies are reduced, indicating improved accuracy. The authors also analyze the spatial and gradient-resolved contributions of exchange-correlation energy to the chemisorption energies. They find that the revPBE and RPBE functionals yield similar results, with the RPBE functional being a more physically consistent choice due to its adherence to the Lieb-Oxford criterion. The study highlights the importance of choosing appropriate exchange-correlation functionals in DFT calculations for accurately predicting adsorption energetics on surfaces. The results demonstrate that the revPBE and RPBE functionals provide a more accurate description of chemisorption energies than the PW91 and PBE functionals, making them valuable tools for surface science applications.This paper presents an improved density-functional theory (DFT) approach for calculating adsorption energetics on transition-metal surfaces. The authors propose a revised Perdew-Burke-Ernzerhof (revPBE) functional, which systematically improves the accuracy of chemisorption energies for various adsorbates on Ni(100), Ni(111), Rh(100), Pd(100), and Pd(111) surfaces. The revPBE functional is derived by modifying a parameter in the original PBE functional, leading to better agreement with experimental data. However, the revPBE functional may locally violate the Lieb-Oxford criterion, which is a fundamental constraint in DFT. To address this, an alternative functional, RPBE, is introduced. The RPBE functional achieves the same improvement in chemisorption energies as revPBE while satisfying the Lieb-Oxford criterion locally. The study compares the performance of several DFT functionals, including the Perdew-Wang-91 (PW91), PBE, revPBE, and RPBE, in predicting chemisorption energies for oxygen, CO, and NO on various transition-metal surfaces. The results show that the revPBE and RPBE functionals provide significantly more accurate predictions of chemisorption energies compared to the PW91 and PBE functionals. The root-mean-square deviations for the calculated chemisorption energies are reduced, indicating improved accuracy. The authors also analyze the spatial and gradient-resolved contributions of exchange-correlation energy to the chemisorption energies. They find that the revPBE and RPBE functionals yield similar results, with the RPBE functional being a more physically consistent choice due to its adherence to the Lieb-Oxford criterion. The study highlights the importance of choosing appropriate exchange-correlation functionals in DFT calculations for accurately predicting adsorption energetics on surfaces. The results demonstrate that the revPBE and RPBE functionals provide a more accurate description of chemisorption energies than the PW91 and PBE functionals, making them valuable tools for surface science applications.