Tag Archives: Ageo Meier de Andrade

Phonon-Assisted Hot Carrier Generation in Plasmonic Semiconductor Systems

Authors: Yocefu Hattori, Jie Meng, Kaibo Zheng, Ageo Meier de Andrade, Jolla Kullgren, Peter Broqvist, Peter Nordlander, and Jacinto Sá

Plasmonic materials have optical cross sections that exceed by 10-fold their geometric sizes, making them uniquely suitable to convert light into electrical charges. Harvesting plasmon-generated hot carriers is of interest for the broad fields of photovoltaics and photocatalysis; however, their direct utilization is limited by their ultrafast thermalization in metals. To prolong the lifetime of hot carriers, one can place acceptor materials, such as semiconductors, in direct contact with the plasmonic system. Herein, we report the effect of operating temperature on hot electron generation and transfer to a suitable semiconductor. We found that an increase in the operation temperature improves hot electron harvesting in a plasmonic semiconductor hybrid system, contrasting what is observed on photodriven processes in nonplasmonic systems. The effect appears to be related to an enhancement in hot carrier generation due to phonon coupling. This discovery provides a new strategy for optimization of photodriven energy production and chemical synthesis.

Nano Lett. 2021, 21, 2, 1083–1089

Lignin Intermediates on Palladium: Insights into Keto‐Enol Tautomerization from Theoretical Modelling

Authors: Ageo Meier de Andrade, Pemikar Srifa, Peter Broqvist, and Kersti Hermansson

It has been suggested in the literature that keto‐to‐enol tautomerization plays a vital role for lignin fragmentation under mild conditions. On the other hand, previous modelling has shown that the adsorbed keto form is more stable than enol on the Pd(111) catalyst. The current density functional theory study of lignin model molecules shows that, in the gas‐phase, keto is more stable than enol, but on the Pd surface, we find enol conformers that are at least as stable as keto. This supports the experimental result that the favourable reaction pathway for lignin depolymerization involves keto‐enol tautomerization. An energy decomposition analysis gives insights concerning the origin of the fine energy balance between the keto and enol forms, where the molecule–surface interaction (−7 eV) and the molecular strain energy (+3 eV) are the main contributors to the adsorption energy.

ChemSusChem, 2020, 13, 6574-6581


Quantitative and qualitative performance of density functional theory rationalized by reduced density gradient distributions

Authors: Ageo Meier de Andrade, Jolla Kullgren and Peter Broqvist 

We evaluate the qualitative and quantitative accuracy of various flavors of density functionals with and without accounting for dispersion corrections. Our test system is nickel in the form of bulk, surfaces, and nanoparticles for which we compute structural properties, bulk cohesive energies, surface energies, and work functions and compare to experimental data. We find that the inclusion of any dispersion, either by an a posteriori correction or by a self-consistent treatment by explicitly computing the nonlocal correlation contribution to the total energy, has a significant effect on the calculated properties and improves the quantitative comparison to experiments. Besides the quantitative agreement, we also investigate qualitative features by comparing Wulff shapes of metal nanoparticles as obtained using the different density functionals. We find that all tested functionals predict similar Wulff shapes for nickel nanoparticles but still have some small differences. These results show that the relative energies calculated using the semilocal GGA and meta-GGA functionals, with and without dispersion, are quite similar. Our findings can also be generalized to other systems when rationalized in terms of the computed reduced density gradients. We find that the distribution of reduced density gradients in a material is correlated to the steepness of the exchange enhancement factor and propose that this information can be used as a quantitative guide when it comes to picking the most appropriate density functional for specific target systems as well as when it comes to extrapolating DFT data to predict experiments.

Phys. Rev. B 102, 2020, 075115