Gas-solid contactors and catalytic reactors with direct microwave heating: current status and perspectives

Microwave heating (MWH) transforms energy from an electromagnetic wave to heat. In contrast to conventional heating (CH) mechanisms that use slower heat transfer processes via conduction, convection or radiation, microwaves (MW) directly interact with MW susceptor materials and induce a rapid conversion of the electromagnetic energy into heat. This rapid heating provides MWH with distinct features that can be leveraged to increase conversion, selectivity and/or energy efficiency of chemical processes. Here we discuss recent significant advances reported in MWH processes involving gas-solid interactions. Special attention is devoted to key aspects such as the methodologies to accurately determine local temperatures under the influence of electromagnetic (EM). Other relevant aspects such as the consideration of the solid catalyst dielectric properties or the design of novel gas-solid contactor configurations will be discussed. Emerging aspects such as the potential of MWH to minimize secondary by-products in high temperature reactions or to efficiently perform in transient processes, e.g. adsorption-desorption cycles, are highlighted. Finally, current challenges and perspectives towards a wide application of MWH in gas solid contactors will be critically discussed

Engineered nanostructured photocatalysts for cancer therapy

The present review aims at highlighting recent advances in the development of photocatalysts devoted to cancer therapy applications. We pay especial attention to the engineering aspects of different nanomaterials including inorganic semiconductors, organic-based nanostructures, noble metal-based systems or synergistic hybrid heterostructures. Furthermore, we also explore and correlate structural and optical properties with their photocatalytic capability to successfully performing in cancer-related therapies. We have made an especial emphasis to introduce current alternatives to organic photosensitizers (PSs) in photodynamic therapy (PDT), where the effective generation of reactive oxidative species (ROS) is pivotal to boost the efficacy of the treatment. We also overview current efforts in other photocatalytic strategies to tackle cancer based on photothermal treatment, starvation therapy, oxidative stress unbalance via glutathione (GSH) depletion, biorthogonal catalysis or local relief of hypoxic conditions in tumor microenvironments (TME)

Serial and Parallel Iterative Splitting Methods: Algorithms and Applications to Fractional Convection-Diffusion Equations

[EN] The benefits and properties of iterative splitting methods, which are based on serial versions, have been studied in recent years, this work, we extend the iterative splitting methods to novel classes of parallel versions to solve nonlinear fractional convection-diffusion equations. For such interesting partial differential examples with higher dimensional, fractional, and nonlinear terms, we could apply the parallel iterative splitting methods, which allow for accelerating the solver methods and reduce the computational time. Here, we could apply the benefits of the higher accuracy of the iterative splitting methods. We present a novel parallel iterative splitting method, which is based on the multi-splitting methods, The flexibilisation with multisplitting methods allows for decomposing large scale operator equations. In combination with iterative splitting methods, which use characteristics of waveform-relaxation (WR) methods, we could embed the relaxation behavior and deal better with the nonlinearities of the operators. We consider the convergence results of the parallel iterative splitting methods, reformulating the underlying methods with a summation of the individual convergence results of the WR methods. We discuss the numerical convergence of the serial and parallel iterative splitting methods with respect to the synchronous and asynchronous treatments. Furthermore, we present different numerical applications of fluid and phase field problems in order to validate the benefit of the parallel versions.This research was partially supported by Ministerio de Economia y Competitividad, Spain, under grant PGC2018-095896-B-C21-C22 and German Academic Exchange Service grant number 91588469.Geiser, J.; Martínez Molada, E.; Hueso, JL. (2020). Serial and Parallel Iterative Splitting Methods: Algorithms and Applications to Fractional Convection-Diffusion Equations. Mathematics. 8(11):1-42. https://doi.org/10.3390/math8111950S142811Farago, I., & Geiser, J. (2007). Iterative operator-splitting methods for linear problems. International Journal of Computational Science and Engineering, 3(4), 255. doi:10.1504/ijcse.2007.018264Frommer, A., & Szyld, D. B. (2000). On asynchronous iterations. Journal of Computational and Applied Mathematics, 123(1-2), 201-216. doi:10.1016/s0377-0427(00)00409-xO’Leary, D. P., & White, R. E. (1985). Multi-Splittings of Matrices and Parallel Solution of Linear Systems. SIAM Journal on Algebraic Discrete Methods, 6(4), 630-640. doi:10.1137/0606062White, R. E. (1986). Parallel Algorithms for Nonlinear Problems. SIAM Journal on Algebraic Discrete Methods, 7(1), 137-149. doi:10.1137/0607017Geiser, J. (2016). Picard’s iterative method for nonlinear multicomponent transport equations. Cogent Mathematics, 3(1), 1158510. doi:10.1080/23311835.2016.1158510Miekkala, U., & Nevanlinna, O. (1987). Convergence of Dynamic Iteration Methods for Initial Value Problems. SIAM Journal on Scientific and Statistical Computing, 8(4), 459-482. doi:10.1137/0908046Miekkala, U., & Nevanlinna, O. (1996). Iterative solution of systems of linear differential equations. Acta Numerica, 5, 259-307. doi:10.1017/s096249290000266xGeiser, J. (2010). Iterative operator-splitting methods for nonlinear differential equations and applications. Numerical Methods for Partial Differential Equations, 27(5), 1026-1054. doi:10.1002/num.20568He, D., Pan, K., & Hu, H. (2020). A spatial fourth-order maximum principle preserving operator splitting scheme for the multi-dimensional fractional Allen-Cahn equation. Applied Numerical Mathematics, 151, 44-63. doi:10.1016/j.apnum.2019.12.018Giona, M., Cerbelli, S., & Roman, H. E. (1992). Fractional diffusion equation and relaxation in complex viscoelastic materials. Physica A: Statistical Mechanics and its Applications, 191(1-4), 449-453. doi:10.1016/0378-4371(92)90566-9Nigmatullin, R. R. (1986). The realization of the generalized transfer equation in a medium with fractal geometry. physica status solidi (b), 133(1), 425-430. doi:10.1002/pssb.2221330150Allen, S. M., & Cahn, J. W. (1979). A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Acta Metallurgica, 27(6), 1085-1095. doi:10.1016/0001-6160(79)90196-2Yue, P., Feng, J. J., Liu, C., & Shen, J. (2005). Diffuse-interface simulations of drop coalescence and retraction in viscoelastic fluids. Journal of Non-Newtonian Fluid Mechanics, 129(3), 163-176. doi:10.1016/j.jnnfm.2005.07.002Sommacal, L., Melchior, P., Oustaloup, A., Cabelguen, J.-M., & Ijspeert, A. J. (2008). Fractional Multi-models of the Frog Gastrocnemius Muscle. Journal of Vibration and Control, 14(9-10), 1415-1430. doi:10.1177/1077546307087440Moshrefi-Torbati, M., & Hammond, J. K. (1998). Physical and geometrical interpretation of fractional operators. Journal of the Franklin Institute, 335(6), 1077-1086. doi:10.1016/s0016-0032(97)00048-3El-Nabulsi, R. A. (2009). Fractional Dirac operators and deformed field theory on Clifford algebra. Chaos, Solitons & Fractals, 42(5), 2614-2622. doi:10.1016/j.chaos.2009.04.002Kanney, J. F., Miller, C. T., & Kelley, C. T. (2003). Convergence of iterative split-operator approaches for approximating nonlinear reactive transport problems. Advances in Water Resources, 26(3), 247-261. doi:10.1016/s0309-1708(02)00162-8Geiser, J., Hueso, J. L., & Martínez, E. (2020). Adaptive Iterative Splitting Methods for Convection-Diffusion-Reaction Equations. Mathematics, 8(3), 302. doi:10.3390/math8030302Meerschaert, M. M., Scheffler, H.-P., & Tadjeran, C. (2006). Finite difference methods for two-dimensional fractional dispersion equation. Journal of Computational Physics, 211(1), 249-261. doi:10.1016/j.jcp.2005.05.017Irreversibility, Least Action Principle and Causality. Preprint, HAL, 2008 https://hal.archives-ouvertes.fr/hal-00348123v1Cresson, J. (2007). Fractional embedding of differential operators and Lagrangian systems. Journal of Mathematical Physics, 48(3), 033504. doi:10.1063/1.2483292Meerschaert, M. M., & Tadjeran, C. (2004). Finite difference approximations for fractional advection–dispersion flow equations. Journal of Computational and Applied Mathematics, 172(1), 65-77. doi:10.1016/j.cam.2004.01.033Geiser, J. (2011). Computing Exponential for Iterative Splitting Methods: Algorithms and Applications. Journal of Applied Mathematics, 2011, 1-27. doi:10.1155/2011/193781Geiser, J. (2008). Iterative operator-splitting methods with higher-order time integration methods and applications for parabolic partial differential equations. Journal of Computational and Applied Mathematics, 217(1), 227-242. doi:10.1016/j.cam.2007.06.028Ladics, T. (2015). Error analysis of waveform relaxation method for semi-linear partial differential equations. Journal of Computational and Applied Mathematics, 285, 15-31. doi:10.1016/j.cam.2015.02.003Yuan, D., & Burrage, K. (2003). Convergence of the parallel chaotic waveform relaxation method for stiff systems. Journal of Computational and Applied Mathematics, 151(1), 201-213. doi:10.1016/s0377-0427(02)00749-5Ladics, T., & Faragó, I. (2013). Generalizations and error analysis of the iterative operator splitting method. Open Mathematics, 11(8). doi:10.2478/s11533-013-0246-4Moler, C., & Van Loan, C. (2003). Nineteen Dubious Ways to Compute the Exponential of a Matrix, Twenty-Five Years Later. SIAM Review, 45(1), 3-49. doi:10.1137/s00361445024180Najfeld, I., & Havel, T. F. (1995). Derivatives of the Matrix Exponential and Their Computation. Advances in Applied Mathematics, 16(3), 321-375. doi:10.1006/aama.1995.1017Hochbruck, M., & Ostermann, A. (2010). Exponential integrators. Acta Numerica, 19, 209-286. doi:10.1017/s0962492910000048Casas, F., & Iserles, A. (2006). Explicit Magnus expansions for nonlinear equations. Journal of Physics A: Mathematical and General, 39(19), 5445-5461. doi:10.1088/0305-4470/39/19/s07Magnus, W. (1954). On the exponential solution of differential equations for a linear operator. Communications on Pure and Applied Mathematics, 7(4), 649-673. doi:10.1002/cpa.3160070404Jeltsch, R., & Pohl, B. (1995). Waveform Relaxation with Overlapping Splittings. SIAM Journal on Scientific Computing, 16(1), 40-49. doi:10.1137/0916004Faragó, I. (2008). A modified iterated operator splitting method. Applied Mathematical Modelling, 32(8), 1542-1551. doi:10.1016/j.apm.2007.04.018Li, J., Jiang, Y., & Miao, Z. (2019). A parareal approach of semi‐linear parabolic equations based on general waveform relaxation. Numerical Methods for Partial Differential Equations, 35(6), 2017-2043. doi:10.1002/num.22390Trotter, H. F. (1959). On the product of semi-groups of operators. Proceedings of the American Mathematical Society, 10(4), 545-545. doi:10.1090/s0002-9939-1959-0108732-6Strang, G. (1968). On the Construction and Comparison of Difference Schemes. SIAM Journal on Numerical Analysis, 5(3), 506-517. doi:10.1137/0705041Geiser, J. (2009). Operator-splitting methods in respect of eigenvalue problems for nonlinear equations and applications for Burgers equations. Journal of Computational and Applied Mathematics, 231(2), 815-827. doi:10.1016/j.cam.2009.05.00

An alternative analysis for the local convergence of iterative methods for multiple roots including when the multiplicity is unknown

[EN] In this paper we propose an alternative for the study of local convergence radius and the uniqueness radius for some third-order methods for multiple roots whose multiplicity is known. The main goal is to provide an alternative that avoids the use of sophisticated properties of divided differences that are used in already published papers about local convergence for multiple roots. We defined the local study by using a technique taking into consideration a bounding condition for the derivative of the function with i=1,2. In the case that the method uses first and second derivative in its iterative expression and i=1 in case the method only uses first derivative. Furthermore we implement a numerical analysis in the following sense. Since the radius of local convergence for high-order methods decreases with the order, we must take into account the analysis of ITS behaviour when we introduce a new iterative method. Finally, we have used these iterative methods for multiple roots for the case where the multiplicity m is unknown, so we estimate this factor by different strategies comparing the behaviour of the corresponding estimations and how this fact affect to the original method.This work was supported by Secretaria de Educacion Superior, Ciencia, Tecnologia e Innovacion (Convocatoria Abierta 2015 fase II).Alarcon, D.; Hueso, JL.; Martínez Molada, E. (2020). An alternative analysis for the local convergence of iterative methods for multiple roots including when the multiplicity is unknown. International Journal of Computer Mathematics. 97(1-2):312-329. https://doi.org/10.1080/00207160.2019.1589460S312329971-2Argyros, I. (2003). On The Convergence And Application Of Newton’s Method Under Weak HÖlder Continuity Assumptions. International Journal of Computer Mathematics, 80(6), 767-780. doi:10.1080/0020716021000059160Hueso, J. L., Martínez, E., & Teruel, C. (2014). Determination of multiple roots of nonlinear equations and applications. Journal of Mathematical Chemistry, 53(3), 880-892. doi:10.1007/s10910-014-0460-8McNamee, J. M. (1998). A comparison of methods for accelerating convergence of Newton’s method for multiple polynomial roots. ACM SIGNUM Newsletter, 33(2), 17-22. doi:10.1145/290590.290592Ortega, J. M. (1974). Solution of Equations in Euclidean and Banach Spaces (A. M. Ostrowski). SIAM Review, 16(4), 564-564. doi:10.1137/1016102Osada, N. (1994). An optimal multiple root-finding method of order three. Journal of Computational and Applied Mathematics, 51(1), 131-133. doi:10.1016/0377-0427(94)00044-1Schr�der, E. (1870). Ueber unendlich viele Algorithmen zur Aufl�sung der Gleichungen. Mathematische Annalen, 2(2), 317-365. doi:10.1007/bf01444024Vander Stracten, M., & Van de Vel, H. (1992). Multiple root-finding methods. Journal of Computational and Applied Mathematics, 40(1), 105-114. doi:10.1016/0377-0427(92)90045-yZhou, X., Chen, X., & Song, Y. (2013). On the convergence radius of the modified Newton method for multiple roots under the center–Hölder condition. Numerical Algorithms, 65(2), 221-232. doi:10.1007/s11075-013-9702-

Adaptive Iterative Splitting Methods for Convection-Diffusion-Reaction Equations

[EN] This article proposes adaptive iterative splitting methods to solve Multiphysics problems, which are related to convection-diffusion-reaction equations. The splitting techniques are based on iterative splitting approaches with adaptive ideas. Based on shifting the time-steps with additional adaptive time-ranges, we could embedded the adaptive techniques into the splitting approach. The numerical analysis of the adapted iterative splitting schemes is considered and we develop the underlying error estimates for the application of the adaptive schemes. The performance of the method with respect to the accuracy and the acceleration is evaluated in different numerical experiments. We test the benefits of the adaptive splitting approach on highly nonlinear Burgers' and Maxwell-Stefan diffusion equations.This research was funded by German Academic Exchange Service grant number 91588469. We acknowledge support by the DFG Open Access Publication Funds of the Ruhr-Universität of Bochum, Germany and by Ministerio de Economía y Competitividad, Spain, under grant PGC2018-095896-B-C21-C22.Geiser, J.; Hueso, JL.; Martínez Molada, E. (2020). Adaptive Iterative Splitting Methods for Convection-Diffusion-Reaction Equations. Mathematics. 8(3):1-22. https://doi.org/10.3390/math8030302S12283Auzinger, W., & Herfort, W. (2014). Local error structures and order conditions in terms of Lie elements for exponential splitting schemes. Opuscula Mathematica, 34(2), 243. doi:10.7494/opmath.2014.34.2.243Auzinger, W., Koch, O., & Quell, M. (2016). Adaptive high-order splitting methods for systems of nonlinear evolution equations with periodic boundary conditions. Numerical Algorithms, 75(1), 261-283. doi:10.1007/s11075-016-0206-8Descombes, S., & Massot, M. (2004). Operator splitting for nonlinear reaction-diffusion systems with an entropic structure : singular perturbation and order reduction. Numerische Mathematik, 97(4), 667-698. doi:10.1007/s00211-003-0496-3Descombes, S., Dumont, T., Louvet, V., & Massot, M. (2007). On the local and global errors of splitting approximations of reaction–diffusion equations with high spatial gradients. International Journal of Computer Mathematics, 84(6), 749-765. doi:10.1080/00207160701458716McLachlan, R. I., & Quispel, G. R. W. (2002). Splitting methods. Acta Numerica, 11, 341-434. doi:10.1017/s0962492902000053Trotter, H. F. (1959). On the product of semi-groups of operators. Proceedings of the American Mathematical Society, 10(4), 545-545. doi:10.1090/s0002-9939-1959-0108732-6Strang, G. (1968). On the Construction and Comparison of Difference Schemes. SIAM Journal on Numerical Analysis, 5(3), 506-517. doi:10.1137/0705041Jahnke, T., & Lubich, C. (2000). Bit Numerical Mathematics, 40(4), 735-744. doi:10.1023/a:1022396519656Nevanlinna, O. (1989). Remarks on Picard-Lindelöf iteration. BIT, 29(2), 328-346. doi:10.1007/bf01952687Farago, I., & Geiser, J. (2007). Iterative operator-splitting methods for linear problems. International Journal of Computational Science and Engineering, 3(4), 255. doi:10.1504/ijcse.2007.018264DESCOMBES, S., DUARTE, M., DUMONT, T., LOUVET, V., & MASSOT, M. (2011). ADAPTIVE TIME SPLITTING METHOD FOR MULTI-SCALE EVOLUTIONARY PARTIAL DIFFERENTIAL EQUATIONS. Confluentes Mathematici, 03(03), 413-443. doi:10.1142/s1793744211000412Geiser, J. (2008). Iterative operator-splitting methods with higher-order time integration methods and applications for parabolic partial differential equations. Journal of Computational and Applied Mathematics, 217(1), 227-242. doi:10.1016/j.cam.2007.06.028Dimov, I., Farago, I., Havasi, A., & Zlatev, Z. (2008). Different splitting techniques with application to air pollution models. International Journal of Environment and Pollution, 32(2), 174. doi:10.1504/ijep.2008.017102Karlsen, K. H., Lie, K.-A., Natvig, J. ., Nordhaug, H. ., & Dahle, H. . (2001). Operator Splitting Methods for Systems of Convection–Diffusion Equations: Nonlinear Error Mechanisms and Correction Strategies. Journal of Computational Physics, 173(2), 636-663. doi:10.1006/jcph.2001.6901Geiser, J. (2010). Iterative operator-splitting methods for nonlinear differential equations and applications. Numerical Methods for Partial Differential Equations, 27(5), 1026-1054. doi:10.1002/num.20568Geiser, J., & Wu, Y. H. (2015). Iterative solvers for the Maxwell–Stefan diffusion equations: Methods and applications in plasma and particle transport. Cogent Mathematics, 2(1), 1092913. doi:10.1080/23311835.2015.1092913Geiser, J., Hueso, J. L., & Martínez, E. (2017). New versions of iterative splitting methods for the momentum equation. Journal of Computational and Applied Mathematics, 309, 359-370. doi:10.1016/j.cam.2016.06.002Boudin, L., Grec, B., & Salvarani, F. (2012). A mathematical and numerical analysis of the Maxwell-Stefan diffusion equations. Discrete & Continuous Dynamical Systems - B, 17(5), 1427-1440. doi:10.3934/dcdsb.2012.17.1427Duncan, J. B., & Toor, H. L. (1962). An experimental study of three component gas diffusion. AIChE Journal, 8(1), 38-41. doi:10.1002/aic.69008011

Gold-Platinum Nanoparticles with Core-Shell Configuration as Efficient Oxidase-like Nanosensors for Glutathione Detection

Nanozymes, defined as nanomaterials that can mimic the catalytic activity of natural enzymes, have been widely used to develop analytical tools for biosensing. In this regard, the monitoring of glutathione (GSH), a key antioxidant biomolecule intervening in the regulation of the oxidative stress level of cells or related with Parkinson’s or mitochondrial diseases can be of great interest from the biomedical point of view. In this work, we have synthetized a gold-platinum Au@Pt nanoparticle with core-shell configuration exhibiting a remarkable oxidase-like mimicking activity towards the substrates 3,3′,5,5′-tetramethylbenzidine (TMB) and o-phenylenediamine (OPD). The presence of a thiol group (-SH) in the chemical structure of GSH can bind to the Au@Pt nanozyme surface to hamper the activation of O2 and reducing its oxidase-like activity as a function of the concentration of GSH. Herein, we exploit the loss of activity to develop an analytical methodology able to detect and quantify GSH up to µM levels. The system composed by Au@Pt and TMB demonstrates a good linear range between 0.1–1.0 µM to detect GSH levels with a limit of detection (LoD) of 34 nM

Plasmonics Devoted to Photocatalytic Applications in Liquid, Gas, and Biological Environments

Plasmonic nanomaterials have emerged in the last years as a very interesting option for many photocatalytic processes. Their localized surface plasmon resonance (LSPR) brings in some unique properties that overcome some of the drawbacks associated with traditional photocatalysis based on semiconductors. Even when in its infancy, many advances have been made in the field, mainly related to the synthesis of new structures with the capabilities of light absorption in the whole solar spectrum. A great number of reactions have been attempted using nanoplasmonic materials. In this chapter, we present the most recent advances made in the field of plasmonic photocatalysis comprising an introductory section to define the main types of plasmonic nanomaterials available, including the most recently labeled alternatives. Following with the major areas of catalytic application, a second section of the chapter has been devoted to liquid-phase reactions for the treatment of pollutants and a selection of organic reactions to render added-value to chemicals under mild conditions. The third part of the chapter addresses two specific applications of nanoplasmonic photocatalysts in gas-phase reactions involving the remediation of volatile organic compounds and the transformation of carbon dioxide into valuable energy-related chemicals. Finally, a fourth section of the chapter introduces the most recent applications of plasmonics in biochemical processes involving the regulation of cofactor molecules and their mimetic behavior as potential enzyme-like surrogates

Silver-Copper Oxide Heteronanostructures for the Plasmonic-Enhanced Photocatalytic Oxidation of n-Hexane in the Visible-NIR Range

Volatile organic compounds (VOCs) are recognized as hazardous contributors to air pollution, precursors of multiple secondary byproducts, troposphere aerosols, and recognized contributors to respiratory and cancer-related issues in highly populated areas. Moreover, VOCs present in indoor environments represent a challenging issue that need to be addressed due to its increasing presence in nowadays society. Catalytic oxidation by noble metals represents the most effective but costly solution. The use of photocatalytic oxidation has become one of the most explored alternatives given the green and sustainable advantages of using solar light or low-consumption light emitting devices. Herein, we have tried to address the shortcomings of the most studied photocatalytic systems based on titania (TiO2) with limited response in the UV-range or alternatively the high recombination rates detected in other transition metal-based oxide systems. We have developed a silver-copper oxide heteronanostructure able to combine the plasmonic-enhanced properties of Ag nanostructures with the visible-light driven photoresponse of CuO nanoarchitectures. The entangled Ag-CuO heteronanostructure exhibits a broad absorption towards the visible-near infrared (NIR) range and achieves total photo-oxidation of n-hexane under irradiation with different light-emitting diodes (LEDs) specific wavelengths at temperatures below 180 °C and outperforming its thermal catalytic response or its silver-free CuO illuminated counterpart

Non-oxidative methane conversion in microwave-assisted structured reactors

The main problem to be addressed in the valorization of methane under non-oxidative conditions (MNOC) is to reduce or even avoid coke formation. In this work we report the use of microwave-assisted heating for MNOC. We have developed a system able to heat-up a Mo-ZSM5 catalyst coated on silicon carbide monolith that could operate stable for at least 19¿h at reaction conditions, 700°C. We demonstrate that under MW-heating the selectivity shifts to C2s and benzene. In contrast, the operation under conventional heating (CH) produces more coke and polyaromatics. The selective microwave heating has two effects in this reaction: i) during the activation of the catalyst the formation of the active catalytic species of Mo2C inside the microporous support is different affecting the selectivity and product distribution; ii) a gas-solid temperature gradient is established that prevents the formation of coke from PAHs in the gas phase. The MNOC process under controlled MW heating at high space velocity (3000¿mL/gcat·h) gives a hydrocarbon yield of around 6% with a very low deactivation rate. These results open up new possibilities for process intensification using alternative sources of energy, as is the case of microwaves, for heating structured catalytic reactors

Platinum-based nanodendrites as glucose oxidase-mimicking surrogates

Catalytic conversion of glucose represents an interesting field of research with multiple applications. From the biotechnology point of view, glucose conversion leads to the fabrication of different added-value by-products. In the field of nanocatalytic medicine, the reduction of glucose levels within the tumor microenvironment (TME) represents an appealing approach based on the starvation of cancer cells. Glucose typically achieves high conversion rates with the aid of glucose oxidase (GOx) enzymes or by fermentation. GOx is subjected to degradation, possesses poor recyclability and operates under very specific reaction conditions. Gold-based materials have been typically explored as inorganic catalytic alternatives to GOx in order to convert glucose into building block chemicals of interest. Still, the lack of sufficient selectivity towards certain products such as gluconolactone, the requirement of high fluxes of oxygen or the critical size dependency hinder their full potential, especially in liquid phase reactions. The present work describes the synthesis of platinum-based nanodendrites as novel enzyme-mimicking inorganic surrogates able to convert glucose into gluconolactone with outstanding selectivity values above 85%. We have also studied the enzymatic behavior of these Pt-based nanozymes using the Michaelis–Menten and Lineweaver–Burk models and used the main calculation approaches available in the literature to determine highly competitive glucose turnover rates for Pt or Pt–Au nanodendrites