Siddharth obtained his PhD in Chemical Engineering from the Indian Institute of Technology Bombay and Monash University Australia (Joint collaboration project under IITB-Monash Research Academy) in 2013, where he worked on several projects to understand the relationships between the flow behaviors of slender electrified viscoelastic jets and key physical properties & operating parameters using mathematical models. Siddharth then worked in COMSOL Multiphysics until 2014. In 2015 he moved to Cranfield University where he worked on modeling microwave-assisted pyrolysis, refining and decomposition of biomass.
In 2016 he joined Surrey as a Research Fellow and worked on an EPSRC project (EP/M013162/1) on the development of mathematical models for plasma-catalysis for a novel gas cleaning process based on low temperature plasma/catalytic technology to produce a clean, high quality syngas from the gasification of waste biomass .
In 2018, Siddharth was awarded the UKRI-NERC Industrial Innovation Fellowship to pursue his research on development of comprehensive mathematical models for bioelectrochemical systems.
Through his academic research and industry experience, Siddharth has developed a unique set of skills that lie at the interface between computational modeling and experimentation in the domain of waste valorisation and circular economy.
Areas of specialism
University roles and responsibilities
- Department Wellbeing Champion
- Department representative of Early Career Researchers' Forum
Affiliations and memberships
Postdoctoral opportunities are currently available to work on experimentation and modeling (dynamic/LCA/TEA) of bioelectrochemical systems or other sustainable energy technologies.
Those interested in postdoctoral research are encouraged to inquire about possible opportunities, national or international postdoctoral fellowships (Newton, Commonwealth Royal Commission, etc.). If your research interests match with the current work in our Lab, we can host you at Surrey for any fellowship applications.
Newton International Fellowships: https://royalsociety.org/grants-schemes-awards/grants/newton-international/
Royal Commission for the Exhibition of 1851: https://www.royalcommission1851.org/awards/?award=research
NERC Independent Research Fellowships: https://nerc.ukri.org/funding/available/fellowships/irf/
EPSRC Fellowships: https://epsrc.ukri.org/skills/fellows/
My work is focused on using experimental and numerical approaches to develop sustainable technologies for an effective transition to circular economy.
Some specific areas on which am current working on include:
- Bioelectrochemical systems: Microbial Fuel cell, Microbial Electrolysis cell, Microbial Electrosynthesis
- Resource recovery from wastewater using bioelectrochemical and physico-chemical approaches.
- Li-CO2 battery
- Thermo-chemical and bio-chemical technological routes for converting biomass/wastewater to energy and fuels.
- Life cycle and techno-economic analysis (LCA-TEA) of different processes focusing on waste-to-energy/chemicals production.
To achieve a sustainable circular economy, recovery and recycling of useful resources needs to be prioritized. Metal contaminated industrial waste streams post great health and ecological concerns, but they are also a valuable source for recovery of useful resources like metals. Traditional metal recovery technologies involve high energy consumption and are chemically intensive. Bioelectrochemical systems such as microbial fuel cells (MFCs) have emerged as a new sustainable technology platform for removal and recovery of metal ions from industrial wastewaters. MFCs combine treatment of organic wastewater by microbial biofilms at the anode with the reduction of metal ions from metal-laden waste streams at cathode. So far, recovery of several metal ions like Cobalt, Chromium, Copper, Gold, Silver, Selenium, Vanadium, Zinc, etc., has been demonstrated. Though promising, metal recovery using MFCs is a complex process and depends on large number of operational and design parameters such as, pH, redox potential of the metal ion, type of electrode materials, initial concentration of metal ions in the wastewater, etc. To optimize the process and maximize metal recovery using MFCs, more research is needed to understand the role of different determinant factors influencing the process. In this international collaborative project, we combine the strengths of two world leading research groups based in UK and India, to develop a robust predictive optimisation tool that can be used to determine the design and operating conditions to maximize the recovery of metals from wastewaters.
Harbin Institute of Technology, China
University of Liverpool
Council Of Scientific And Industrial Research–Indian Institute Of Chemical Technology (CSIR-IICT)
Postgraduate research supervision
PhD - Anna Salvian (Working on development of biosensors (based on Microbial Fuel Cells))
PhD - Mahsa Masoudi (Working on Li-CO2 batteries)
PhD - Maano Tshimange (Working on membrane separation processes to recover Phosphorus from wastewater)
PhD - Ning Mao (Understanding the behaviour of Lithium-ion batteries under overcharge)
PhD - Tengfei He (Thermal runaway behaviour of lithium-ion battery during charge/discharge processes)
This review presents the developments in the mathematical models for various bioelectrochemical systems. A number of modeling approaches starting with the simple description of biological and electrochemical processes in terms of ordinary differential equations to very detailed 2D and 3D models that study the spatial distribution of substrates and biomass, have been developed to study BES performance. Additionally, mathematical models focused on studying a particular process such as ion diffusion through membrane and new modeling approaches such as artifcial intelligence methods, cellular network models, etc., have also been described. While most mathematical models are still focused on performance studies and optimization of microbial fuel cells, new models to study other BESs such as microbial electrolysis cell, microbial electrosynthesis and microbial desalination cell have also been reported and discussed in this review.
This paper discusses a novel digital output using mathematical computation of life cycle sustainability assessment for design decisions on systemic holistic sustainability of technical systems. The computational social life cycle assessment (SLCA) combining the supply chain import data and social hotspot database for interacting countries in entire supply chain indicates that self-generation in electricity sector gives savings in community infrastructure (68%), governance (53%), human rights (50%), labour rights & decent work (24%), and health & safety (8%), SLCA categories compared to electricity import scenarios in the UK. The life cycle assessment shows the carbon-efficient energy systems for net zero greenhouse gas emissions (GHG) in increasing order of environmental impacts: hydroelectric, wind, biomass, geothermal and solar (4-76 gCO2eq./kWh). The technical and life cycle costing models show that within bioenergy, biomass combined heat and power systems give greater feasibility than microbial fuel cells with a levelized cost of electricity of 0.026 and 0.07 Euro/kWh. TESARREC™ (Trademark: UK00003321198), a novel web-based open-source digital output integrates intrinsic physicochemical, design, operating and systemic characteristics to model and analyse technical systems for sustainability and benchmark/standardise GHG of renewable, biomass and carbon dioxide capture and sequestration strategies for policy directives.
A two-dimensional numerical fluid model is developed for studying the influence of packing configurations on dielectric barrier discharge (DBD) characteristics. Dis- charge current profiles, and time averaged electric field strength, electron number density and electron temperature distributions are compared for the three DBD configurations, plain DBD with no packing, partially packed DBD and fully packed DBD. The results show a strong change in discharge behaviour occurs when a DBD is fully packed as compared to partial packing or no packing. While the average electric field strength and electron temperature of a fully packed DBD are higher relative to the other DBD configurations, the average electron density is substantially lower and may impede the DBD reactor performance under certain operating conditions. Possible scenarios of the synergistic effect of the combination of plasma with catalysis are also discussed.
A comprehensive three-dimensional mathematical model is developed for studying the microwave-assisted pyrolysis of biomass. Kraft Lignin is considered as biomass feedstock in the model, and a mixture of lignin and char, is used as the sample for pyrolysis. A lumped kinetic model which considers three lumped pyrolysis products (gas, liquid and remaining solid fractions) is coupled with the governing equations for the microwave field, heat transfer, mass transfer, Darcy fluid flow and a transient numerical analysis is performed. The distribution of electric field in the microwave cavity, and the distribution of electric field, temperature, and pyrolysis products within the lignin sample are presented. The lignin sample is predicted to undergo volumetric heating when subjected to microwave heating. Accordingly the reaction zone extends from the center of the biomass sample bed towards the outer surface. Preliminary evaluation of the applicability of the model for assessing the effect of different parameters on the microwave pyrolysis of lignin is also carried out.
In this work, a dynamic computational model is developed for a single chamber microbial fuel cell (MFC), consisting of a bio-catalyzed anode and an air-cathode. Electron transfer from the biomass to the anode is assumed to take place via intracellular mediators as they undergo transformation between reduced and oxidized forms. A two-population model is used to describe the biofilm at the anode and the MFC current is calculated based on charge transfer and Ohm's law, while assuming a non-limiting cathode reaction rate. The open circuit voltage and the internal resistance of the cell are expressed as a function of substrate concentration. The effect of operating parameters such as the initial substrate (COD) concentration and external resistance, on the Coulombic efficiency, COD removal rate and power density of the MFC system is studied. Even with the simple formulation, model predictions were found to be in agreement with observed trends in experimental studies. This model can be used as a convenient tool for performing detailed parametric analysis of a range of parameters and assist in process optimization.
According to the US Department of Energy, succinic acid (SA) is a top platform chemical that can be produced from biomass. Bread waste, which has high starch content, is the second most wasted food in the UK and can serve as a potential low cost feedstock for the production of SA. This work evaluates the environmental performance of a proposed biorefinery concept for SA production by fermentation of waste bread using a cradle-to-factory gate life cycle assessment approach. The performance was assessed in terms of greenhouse gas (GHG) emissions and non-renewable energy use (NREU). Waste bread fermentation demonstrated a better environmental profile compared to the fossil-based system, however, GHG emissions were about 50 higher as compared to processes using other biomass feedstocks such as corn wet mill or sorghum grains. NREU for fermentative SA production using waste bread was significantly lower ( 46) than fossil-based system and about the same as that of established biomass-based processes, thus proving the great potential of waste bread as a valuable feedstock for bioproduction of useful chemicals. The results show that steam and heating oil used in the process were the biggest contributors to the NREU and GHG emissions. Sensitivity analyses highlighted the importance of the solid biomass waste generated in the process which can potentially be used as fish feed. The LCA analysis can be used for targeted optimization of SA production from bread waste, thereby enabling the utilization of an otherwise waste stream and leading to the establishment of a circular economy.
In this work, a two-dimensional numerical fluid model is developed for a partially packed dielectric barrier discharge (DBD) in pure helium. In fluence of packing on the discharge characteristics is studied by comparing the results of DBD with partial packing with those obtained for DBD with no packing. In the axial partial packing configuration studied in this work, the electric field strength was shown to be en hanced at the top surface of the spherical packing material and at the contact points between the packing and the dielectric layer. For each value of applied potential, DBD with partial packing showed an increase in the number of pulses in the current profile in the positive half cycle of the applied voltage, as compared to DBD with no packing. Addition of partial packing to the plasma-alone DBD also led to an increase in the electron and ion number densities at the moment of breakdown. The time averaged electron energy profiles showed that a much higher range of electron energy can be achieved with the use of partial packing as compared to no packing in a DBD, at the same applied power. The spatially and time averaged values over one voltage cycle also showed an increase in power density and electron energy on inclusion of partial packing in the DBD. For the applied voltage parameters studied in this work, the discharge was found to be consistently homogeneous and showed the characteristics of atmospheric pressure glow discharge.
This study presents a steady state, two dimensional mathematical model of microbial fuel cells (MFCs) developed by coupling mass, charge and energy balance with the bioelectrochemical reactions. The model parameters are estimated and validated using experimental results obtained from ve aircathode MFCs operated at different temperatures. Model analysis correctly predicts the nonlinear performance trend of MFCs with temperatures ranging between 20 oC - 40 oC. The two dimensional distribution allows the computation of local current density and reaction rates in the biolm, helping to correctly capture the interdependence of system variables and predict the drop in power density at higher temperatures. Model applicability for parametric analysis and process optimization is further highlighted by studying the effect of electrode spacing and ionic strength on MFC performance.
A novel framework integrating dynamic simulation (DS), life cycle assessment (LCA) and techno-economic assessment (TEA) of bioelectrochemical system (BES) has been developed to study for the first time wastewater treatment by removal of chemical oxygen demand (COD) by oxidation in anode and thereby harvesting electron and proton for carbon dioxide reduction reaction or reuse to produce products in cathode. Increases in initial COD and applied potential increase COD removal and production (in this case formic acid) rates. DS correlations are used in LCA and TEA for holistic performance analyses. The cost of production of HCOOH is €0.015–0.005g–1 for its production rate of 0.094–0.26kgyr–1 and a COD removal rate of 0.038–0.106kgyr–1. The life cycle (LC) benefits by avoiding fossil-based formic acid production (93%) and electricity for wastewater treatment (12%) outweigh LC costs of operation and assemblage of BES (–5%), giving a net 61MJkg-1HCOOH saving.
Microbial electrosynthesis (MES) is an innovative technology for electricity driven microbial reduction of carbon dioxide (CO2) to useful multi-carbon compounds. This study assesses the cradle-to-gate environmental burdens associated with acetic acid (AA) production via MES using graphene functionalized carbon felt cathode. The analysis shows that, though the environmental impact for the production of the functionalized cathode is substantially higher when compared to carbon felt with no modification, the improved productivity of the process helps in reducing the overall impact. It is also shown that, while energy used for extraction of AA is the key environmental hotspot, ion-exchange membrane and reactor medium (catholyte & anolyte) are other important contributors. A sensitivity analysis, describing four different scenarios, considering either continuous or fed-batch operation, is also described. Results show that even if MES productivity can be theoretically increased to match the highest space time yield reported for acetogenic bacteria in a continuous gas fermenter (148 g L−1 d−1), the environmental impact of AA produced using MES systems would still be significantly higher than that produced using a fossil-based process. Use of fed-batch operation and renewable (solar) energy sources do help in reducing the impact, however, the low production rates and overall high energy requirement makes large-scale implementation of such systems impractical. The analysis suggests a minimum threshold production rate of 4100 g m−2 d−1, that needs to be achieved, before MES could be seen as a sustainable alternative to fossil-based AA production.
This study describes and evaluates a dynamic computational model for two chamber microbial electrosynthesis (MES) system. The analysis is based on redox mediators and a two population model, describing bioelectrochemical kinetics at both anode and cathode. Mass transfer rates of substrate and bacteria in the two chambers are combined with the kinetics and Ohm’s law to derive an expression for the cell current density. Effect of operational parameters such as initial substrate concentration at anode & cathode and the operation cycle time, on MES performance are evaluated in terms of product formation rate, substrate consumption and Coulombic efficiency (CE). For fixed operation cycle time of 3 or 4 days, the anode and cathode initial substrate concentrations show linear relationship with product formation rate; however MES operation with 2 day cycle time shows a more complex behaviour, with acetic acid production rates reaching a plateau and even a slight decrease at higher concentrations of the two substrates. It is also shown that there is a trade-off between product formation rate and substrate consumption & CE. MES performance for operation with cycle time being controlled by substrate consumption is also described. Results from the analysis demonstrate the interdependence of the system parameters and highlight the importance of multi-objective system optimization based on targeted end-use.
In this study, plasma-catalytic steam reforming of toluene as a biomass tar model compound was carried out in a coaxial dielectric barrier discharge (DBD) plasma reactor. The effect of Ni/Al2O3 catalysts with different nickel loadings (5–20 wt%) on the plasma-catalytic gas cleaning process was evaluated in terms of toluene conversion, gas yield, by-products formation and energy efficiency of the plasma-catalytic process. Compared to the plasma reaction without a catalyst, the combination of DBD with the Ni/Al2O3 catalysts significantly enhanced the toluene conversion, hydrogen yield and energy efficiency of the hybrid plasma process, while significantly reduced the production of organic by-products. Increasing Ni loading of the catalyst improved the performance of the plasma-catalytic processing of toluene, with the highest toluene conversion of 52% and energy efficiency of 2.6 g/kWh when placing the 20 wt% Ni/Al2O3 catalyst in the plasma. The possible reaction pathways in the hybrid plasma-catalytic process were proposed through the combined analysis of both gas and liquid products.
Bioelectrochemical systems (BESs) have been catalogued as a technological solution to three pressing global challenges: environmental pollution, resource scarcity, and freshwater scarcity. This study explores the social risks along the supply chain of requisite components of BESs for two functionalities: (i) copper recovery from spent lees and (ii) formic acid production via CO2 reduction, based on the UK’s trade policy. The methodology employed in this study is based on the UNEP/SETAC guidelines for social life-cycle assessment (S-LCA) of products. Relevant trade data from UN COMTRADE database and generic social data from New Earth’s social hotspot database were compiled for the S-LCA. The results revealed that about 75% of the components are imported from the European Union. However, the social risks were found to vary regardless of the magnitude or country of imports. “Labour and Decent Work” was identified as the most critical impact category across all countries of imports, while the import of copper showed relatively higher risk than other components. The study concludes that BESs are a promising sustainable technology for resource recovery from wastewater. Nevertheless, it is recommended that further research efforts should concentrate on stakeholder engagement in order to fully grasp the potential social risks.
In this work, a one-dimensional numerical uid model is developed for co-axial dielec- tric barrier discharge (DBD) in pure helium and a parametric study is performed to systematically study the in uence of relative permittivity of the dielectric barrier and the applied voltage amplitude and frequency on the discharge performance. Discharge current, gap voltage and spatially averaged electron density pro les are presented as a function of relative permittivity and voltage parameters. For the geometry un- der consideration, both the applied voltage parameters are shown to increase the maximum amplitude of the discharge current peak up to a certain threshold value, above which it stabilized or decreased slowly. The spatially averaged electron density pro les follow a similar trend as the discharge current. Relative permittivity of the dielectric barrier is predicted to have a positive in uence on the discharge current. At lower frequency it is also shown to lead a transition from Townsend to glow dis- charge mode. Spatially and time averaged power density is also calculated and is shown to increase with increasing relative permittivity, applied voltage amplitude and frequency.
A comprehensive 3D coupled mathematical model is developed to study the microwave assisted thermocatalytic decomposition of methane with activated carbon as the catalyst. A simple reaction kinetic model for methane conversion (accounting for catalyst deactivation) is developed from previously published experimental data and coupled with the governing equations for the microwaves, heat transfer, mass transfer and fluid flow physics. Temperature distribution and concentration profiles of CH4 & H2 in the catalyst bed are presented. The temperature profiles at di erent input power values predict a non-uniform temperature distribution with hot-spots near the top and bottom of the catalyst. The concentration profiles predict a linear variation of CH4 and H2 concentration along the length of the reactor and show a good agreement with experimental conversion values. The influence of volumetric hourly space velocity on methane conversion is also investigated.
Highly efficient macroalgae based chemical factories and environmental protection have been comprehensively studied for the first time to displace fossil resources to mitigate climate change impact. Wild macroalgae by (bio)phytoremediation and residual macroalgae by biosorption can be used to treat wastewaters, marine environment, soil and sludge. Cultured macroalgae can be processed through drying, milling, grinding, suspension in deionised water and filtration extracting sap of heavy metals; centrifugation of solids recovering nutrients; ion exchange resins of supernatants separating protein and polysaccharides; dialysis purifying protein from salts and pretreatment of polysaccharides producing a sugar platform. Protein profiling shows the presence of the essential amino acids as well as others as food additive, flavour enhancer and pharmaceutical ingredient. Sugars can be converted into a chemical: levulinic acid by controlled acid hydrolysis; 2,5-furandicarboxylic acid by heterogeneous catalytic reaction; succinic acid by tricarboxylic acid cycle; lactic acid by fermentation, with 3-5 times market value than bioethanol. Protein, sugar based chemical and inorganics give the highest to the lowest climate change impact savings of 12, 3 and 1 kg CO2 equivalent kg-1 product. Their cost of production is estimated at $2010 t-1, significantly lower than their market prices, making the integrated marine biorefinery system economically more attractive than lignocellulosic terrestrial biorefinery systems. Social life cycle assessment indicates that the highest to the lowest avoided social impacts will be from the displacements of animal based protein, sugars and minerals, in Indonesia, China and Philippines (producing 27 million tonnes per annum, 93% of global production), respectively.
A two-dimensional mathematical model has been developed for characterizing and predicting the dynamic performance of an air-cathode MFC with graphite fiber brush used as anode. The charge transfer kinetics are coupled to the mass balance at both electrodes considering the brush anode as a porous matrix. The model has been used to study the effect of design (electrode spacing and anode size) as well as operational (substrate concentration) parameters on the MFC performance. Two-dimensional dynamic simulation allows visual representation of the local overpotential, current density and reaction rates in the brush anode and helps in understanding how these factors impact the overall MFC performance. The numerical results show that while decreasing electrode spacing and increasing initial substrate concentration both have a positive influence on power density of the MFC, reducing anode size does not affect MFC performance till almost 60 brush material has been removed. The proposed mathematical model can help guide experimental/pilot/industrial scale protocols for optimal performance.
We present a correlation for determining the power density of microbial fuel cells based on dimensional analysis. Important operational, design and biological parameters are non-dimensionalized using a selection of scaling variables. Experimental data from various microbial fuel cell studies operating over a wide range of system parameters are analyzed to attest accuracy of the model in predicting power output. The correlation predicts nonlinear dependencies between power density, substrate concentration, solution conductivity, external resistance, and electrode spacing. The straightforward applicability without the need for any significant computational resources, while preserving good level of accuracy; makes this correlation useful in focusing the experimental effort for the design and optimization of microbial fuel cells.
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