Food, Water, Waste Research Group

PhD Students 

Nasser Alkhulaifi

Nasser Alkhulaifi

PhD title:  Energy Monitoring and Modelling: Investigating the Use of Machine Learning Techniques to Improve Energy Efficiency in Food Manufacturing Environments. 

Supervisor:  Nicholas Watson and Isaac Tirguero

Research Summary
In the context of ‘environmental sustainability’, the industrial sector confronts environmental difficulties due to the growing energy demand. In 2016, about three-quarters of the world's CO2 emissions were driven by the use of energy. The FAO predicts that food production would need to rise by 70% by 2050 but energy output will only increase by 33%. Consequently, increasing energy efficiency has emerged as a critical concern for the food industry. Due to its excellent problem-solving and dimensionality capabilities, data-driven methods such as machine learning are often hailed as a superior analytical approach. To support and drive industry 4.0 technologies adoption and enhance the implementation of sustainable industrial development practices, this research will investigate the use of ML techniques to improve energy efficiency in commercial food manufacturing environments.

Maira Anam

PhD title: Advanced three-dimensional electrode structure in microbial fuel cell for resource recovery from wastewater

Supervisors: Prof. Rachel GomesDr.Helena Gomes and Dr. Ricky Wildman

Research Summary
In the last century, global economic development and industrial growth were supported by fossil fuels, but these natural resources cannot support industrialization and economic growth forever. Bio electrochemical systems provide an attractive method to add wastewater to the list of environmentally friendly and renewable energy sources. This study will focus on the conversion of solar energy into electrical power using cyanobacterial biofilms on chemically stable three-dimensional (3D) macroporous electrodes developed via additive manufacturing techniques. This could significantly improve the economic viability of anodes in existing microbial fuel cell configurations. Furthermore, this research will demonstrate the visualization and characterization of the photosynthetic biofilm-electrode interface during charge transfer processes, exploring the use of chemical biology and electrochemical methods, such as in situ confocal fluorescence and Raman microscopy, and using chemical and biophysical characterizations of synthetic electrode materials.
Khivishta Boodhoo

Khivishta Boodhoo

Supervisors: Dr Nicholas Watson and Dr Isaac Triguero 

Industrial supervisor: Josh Plumbly

Research Summary
This Resilient Decarbonised Fuel Energy Systems PhD project will investigate the use of sensor measurements and machine learning to predict and optimise either the energy production or energy utilisation for a range of industrial relevant case studies. The PhD project will be sponsored by the industrial partner Intelligent Plant, who focus on the analysis and visualisation of industrial data. Although the project will focus on different case studies the aim is to determine suitable data collection and analysis strategies that can be applied to a variety of different industrial systems. The first and second case studies will focus on energy production systems and the third and fourth on the energy efficiency of industrial processes. An objective of this project is to develop appropriate data analysis and visualisation methods, which contribute to the UK’s, net zero ambition. 
CS1: Wind turbines
This case study will use data from offshore wind turbines provided by the Offshore Renewable Energy Catapult. Predictive models will be developed to determine the energy produced for a variety of turbine conditions (e.g.) in addition to determining the optimal conditions to maximise energy production.
CS2 : Minimizing errors of wind turbines
Alarms, minimising false positive identification and replacement to reduce them which will contribute to more uptime / reduce downtime.
CS3: Industry baking 
This case study will use data (e.g. temperature, residence time) from industrial bakeries and develop models to determine the optimal parameters of different unit operations (e.g. baking and cooling) to minimise the energy utilised whilst ensuring the product remain within specification.
CS4: Brewing 
This case study will use data collected from local breweries to monitor the energy usage through key unit operations (e.g. fermentation and wort boiling and cleaning) and develop models to monitor processes and reduce energy utilisation.
Alex Bowler

Alex Bowler

PhD title: Machine Learning and Ultrasonic Sensors for the Optimisation of Mixing Processes

Supervisor:  Dr Nicholas Watson and Prof Serafim Bakalis

Research Summary
End-point determination of mixing processes using multiple ultrasonic transducers. Ultrasonic sensors are low cost and non-invasive. Machine Learning is utilised to infer the level of mixing from sensor measurements. 
Henry Forbes

Henry Forbes

PhD title: Sustainable porous materials for water treatment applications.

Supervisors:  Dr Rebecca Ferrari and Dr Ifty Ahmed

Research Summary
The aim of this project is to address the issue of micro-pollutants which are present in waste water sources. Activated carbon (AC) is a well-known commercial material used for removal of organic and inorganic pollutants in water, which is prepared using carbonaceous precursors, including coal, peat and coconut shells. However, the use of AC is not sustainable. This project will focus on developing alternate, sustainable advanced porous materials for water treatment applications. A previously developed manufacturing technology for the production of highly porous glass microspheres will be applied to natural materials to manufacture highly porous microspheres from alternative, sustainable, non-resorbable glass alternatives and natural materials.
Max Gillingham 2020

Max Gillingham

PhD title: Magnetic biochar for remediation of polluted soils: developing a novel approach to reduce losses of nitrogenous pollutants derived from agriculture.

Supervisors: Dr Rebecca FerrariProf Rachel Gomes and Helen West

Research summary

This PhD will investigate the use of magnetic biochar as a tool to extract pollutants from soil, considering practicality, sustainability, cost-effectiveness and environmental safety. Biochar is a carbon-based material, made from pyrolysed organic matter, that shows high capacity for sorption of pollutants in various environments. Biochar can be ‘tailor-made’ to improve sorption capacity of specific pollutants, via manipulation of surface functional groups and physical properties. Recently, magnetisation of biochar has been explored as a way to improve biochar removal from media. Nitrogen pollution is of great concern in the UK, with nitrogen losses from agricultural soils causing environmental damage in the form of eutrophication, as well as raising public health concerns through contamination of groundwater. Low Nitrogen Use Efficiency (NUE) also acts as a financial burden for farmers. This PhD will therefore:

  • Design, synthesise and analyse biochar to be used for nitrogen sorption in soil.
  • Investigate magnetisation of biochar by optimising methods of biochar surface modification and testing subsequent removal from soil by magnetic separation.
  • Study the effects of magnetic biochar application/removal on soil chemistry and biology.
  • Explore the reusability of magnetic biochar, to promote sustainability and cost-effectiveness.
Erhan Gulsen

Erhan Gulsen

PhD title: Ultrasonic Sensors and Machine Learning for Digital Food and Drink Manufacturing

Supervisors:  Dr Nicholas WatsonProf Ed MorrisDr Stephen Grebby and Dr Abubakr Ibrahim

Research summary

The world is experiencing the 4th industrial revolution which involves the use of digital technologies such as artificial intelligence, cloud computing, sensors and the industrial internet of things. These digital manufacturing technologies have the potential to improve manufacturing productivity and efficiency whilst reducing the environmental impact it has. One barrier preventing the widespread adoption of digital technologies within food and drink manufacturing is the lack of suitable online technologies capable of measuring the properties and therefore quality of the food.

Ultrasonic techniques use mechanical waves to probe and therefore characterise the properties of multicomponent materials (e.g. food) and are an attractive sensing technology due to their low cost and size. However, for them to be a suitable online sensor, new signal and data processing algorithms are required to relate sensor measurements to the food’s physical properties. Machine learning uses vast amounts of data to develop predictive algorithms. A key advantage of machine learning techniques is the variety of data they can process and their ability to improve as more or better data becomes available.

I will focus on developing ultrasonic techniques, which utilise machine-learning algorithms to classify the structure and quality of food during my PhD.

Andy Henshaw

Andrew Henshaw

PhD title: Designing Aquaponic Systems for Off-grid Communities

Supervisors:  Dr Mike Clifford and  Dr Helen West

Reseearch Summary

One of the largest challenges for the global food production system is achieving global food security; meeting the ever-growing demand with an ever-shrinking supply of resources.  Aquaponics is a technique which combines hydroponics (soilless plant culture) and aquaculture (fish farming), utilising fish waste to provide the nutrients essential to plant growth. This in turn improves the water quality for fish and has a high nutrient and water use efficiency compared to conventional agriculture.

This project aims to assess the ability of aquaponics to provide food security in rural off-grid communities and consider methods of making aquaponics more economically feasible. I aim to combine models of water quality in aquaculture ponds and nutrient uptake rates of plants to predict aquaponic system behaviour and use this as a basis for improving aquaponic system design. Based on findings of this research, improvements will be applied to an existing system and its social, technical and economic success evaluated.





Azimmatul Ihwah 

PhD title: Machine Learning for Milk Quality Control

Supervisors:  Dr Nicholas Watson,
Research Summary

 Milk is the one of agricultural products that the quality can be measured both chemically and visually. Some research has been conducted for analyzing milk quality partially or simultaneously from chemical aspects or visual perspectives. The prominent composition of milk comprises fat, protein, lactose, and total solid content. Meanwhile, the quality of milk is depicted by sensory quality as well. Sensory quality can be defined as two parts, flavor; taste, mouthfeel, and off-flavor; texture, aroma, visual aspect, color, and odor. A sensor-based data-driven approach will be used for milk quality assessment (both sensory and objective measurements). Machine learning will take part in model analysis and development.

my- Louise Johnston

Amy-Louise Johnston

PhD title: Layered Double Hydroxides for sorption of antibiotics from wastewater

Supervisors: Prof. Rachel L. Gomes, Prof. Edward Lester, and Dr. Orla Williams

Research Summary
The aim of this project is to explore the use of layered double hydroxide for the removal of antibiotics from wastewater. The presence of antibiotics in wastewater, especially from pharmaceutical manufacturing facilities, is a known driver of the spread of antimicrobial resistance (AMR). AMR is considered to be one of the next healthcare catastrophes if nothing done to stop the spread, with millions of lives at risk. Therefore, solutions to remove antibiotics from wastewater are required and sorption is one option. Layered double hydroxides have been shown to be successful sorbent materials for a range of differed organic pollutants – but more work is required to understand how they can be applied for the removal of antibiotics. This project focuses on removal of antibiotics at environmentally relevant concentrations and from various aqueous matrices. Layered double hydroxides will be synthesised through a continuous hydrothermal flow reactor. 
Chris Lanyon

Christopher Lanyon

PhD title: Evaluating antimicrobial resistance in dairy farming

Supervisors:  Prof. Rachel Gomes

Research Summary
Dairy slurry tanks store farm wastewater which includes bovine faeces and urine, parlour washings and foot-bath contents. After storage, the slurry is spread on to both human and animal food crops. As both antibiotic resistance genes (ARGs) and antibiotics are excreted by cows, the slurry tank is potentially a breeding ground for antimicrobial resistant (AMR) bacteria and a source of AMR and ARGs into the environment. In my project I am attempting to use mathematical modelling to better understand the prevalence and spread of AMR in the Sutton Bonington Dairy Farm slurry tank.

Qingsu Liu

PhD title: Manipulating protein-starch matrix for health benefits using in vitro digestion models

Supervisors: Dr Nicholas Watson

Research Summary

My research spans a range of engineering aspects of in vitro digestion systems and the microstructural effect of the protein matrix on starch digestibility.

I joined the team after completing the degree in human nutrition at the University of Glasgow. I previously worked as a research director of in vivo digestion models (Non-Human Primate) at Wincon Thera Cells Biotechnologies Co, Ltd for obesity related research projects and medical assessment. 



Melissa Maher

PhD title: Understanding plastic pollution to mitigate impact to freshwaters and services. 

Supervisors: Prof. Rachel GomesProfessor Steve Howdle, and Professor Matthew Johnson. 

Research Summary
Macro and micro plastic are unregulated water pollutants with significant implications to service provision (e.g. water treatment), as well as generating considerable public and political concern. To deliver solutions to the plastic pollution pandemic, we need first to understand the extent of plastic pollution and how environmental conditions influence plastic fate and impact on water quality. Environmental conditions are complex and variable that lead to fragmentation and a changing condition of the plastic due to abiotic and biotic degradation. The condition of waste plastic (versus as manufactured) will influence the pollution severity and impact to freshwater function and services. Characterising plastic under dynamic conditions require analytics able to elucidate the plastic presence and fate processes involved. This project will aim to understand the extent and impact of plastic pollution on water quality and services using established (e.g. SEM, Raman, and FTIR) and emerging (e.g. 3D ToF-SIMS) analytics. Outcomes will serve to understand how plastic interacts with its surrounding complex environment and implications to water quality and use by society.

 Lucija Strkalj

PhD Title: From Plant to Plate: Biotransformation of Functional Polysaccharides

SupervisorsDr Gleb Yakubov, Dr David Cook and Dr Nicholas Watson 

Research Summary

Lucija Strkalj is doing her PhD in Biosciences as a part of Nottingham-Adelaide programme. She holds Bachelor's and Master's Degree in Nutrition Science from University of Zagreb, Croatia.

Lucija's project focuses on dietary fibre from plant Plantago ovata L., commonly known as Psyllium. Said dietary fibres have an unusual structure and water interaction and her aim is to use different modification techniques to change the structure, and also to examine the relationship between dietary fibre and enzyme L-amylase to lower glycaemic response.

Zhongli Wang

Zhongli Wang

PhD Title: Bio-recovery of Selenium (Se(0)) from contaminated water

SupervisorsProf. Rachel GomesHelena Gomes and Yanming Wang

Research summary

Water is one of the most important resources in nature, and it is an essential resource for human survival and societal development. However, human activity has contributed to water contamination. Pollutants that cause harm to the environment can be recovered and recycled by implementing novel technologies, in line with the developing circular economy. This will not only reduce environmental pollution but also improve the efficiency of resource utilization and reduce the waste of resources. The selenium (Se) content in the Earth's crust is about 0.05 ppm, and it is considered a critical raw material in more than 40 countries. On the other side, its widespread use in the mining, semiconductor, and electronics industries has increased the probability of selenium leakage and contamination. Dissimilatory reduction of Se to elemental selenium (Se(0)) by microorganisms is known to be an important process for removing toxic soluble Se and recovery of elemental Se nanoparticles.

My PhD is focused on using activated sludge to perform Se recovery from contaminated water. This work aims to boost bio-recovery efficiency, assess microbial communities involved, and optimize the bio-recovery process.

Publications:  BAOGANG Z, ZHONGLI W, JIAXIN S, HAILIANG D, 2019, Sulfur-based mixotrophic bio-reduction for efficient removal of chromium (VI) in groundwater, Geochimica et Cosmochimica Acta, 268, 296-309.ZHONGLI W, BAOGANG Z, YUFENG J, YUNLONG LI, CHAO H, 2018, Spontaneous thallium (I) oxidation with electricity generation in single-chamber microbial fuel cells: Applied Energy, 209, 33-42.BAOGANG Z, CAIXING T, YING L, LITING H, YE L, CHUANPING, F, YUQIAN L, ZHONGLI W, 2015, Simultaneous microbial and electrochemical reductions of vanadium (V) with bioelectricity generation in microbial fuel cells, Bioresource Technology, 179, 91-97.

franziska wohlgemuth

Franziska Wohlgemuth

PhD Title: Water resilience and food security: Electrolysed water to prevent microbial food spoilage

Supervisors: Prof. Simon Avery,  Prof. Rachel Gomes and Dr Frankie Rawson

Research summary
Microbial food spoilage can occur at different stages of the food supply chain (pre- or post-harvest, during storage or transport) and represents an important economic and environmental problem. Additionally, food borne pathogens and related illnesses are a major global health threat. Electrolysed Water is a novel disinfectant that offers a cost-friendly, environmentally beneficial alternative to conventional disinfection techniques. In cooperation with UK industry, this project aims to elucidate the mode of action of electrolysed water in food spoilage fungi. This will be addressed with microbiological, genetic and biochemical methods. A second focus will be on the efficacy and water resilience of the system. This includes the safety of both the treated produce and the effluent water.

John Woodliffe

PhD Title: Magnetic metal-organic framework composites for pollutant gas capture

Supervisors: Dr Andrea LaybournDr Rebecca Ferrari and Dr Ifty Ahmed

Research Summary

The largest contributor to global anthropogenic CO2 emissions is coal-fired power plants. However, the current amine absorption technologies for carbon capture are not widely used due to their high energy requirements for separation and purification, increasing a power plant’s energy demand by 25-40%.

In addition to CO2, other pollutant gases such as SOx and NOx are detrimental to both the environment and human health. Our research aims to develop novel and sustainable magnetic framework composite materials with leading adsorption profiles and processing capabilities for capturing CO2 and other pollutant gases. 

Mohammed Zari

Mohammed Zari

PhD title: Health and environmental Impact assessment of landfill mining activities 

Supervisors: Dr Rebecca Ferrari

Research Summary
Landfill mining (LFM) is a process whereby solid wastes which have previously been landfilled are excavated and processed. It has been progressing for at least two decades for resource recovery in EU and the UK. Previous research has focused on aspects of materials and energy recovery. Implementation has been limited due to concerns about health and environmental impacts. Therefore, this proposed research will determine the potential health impacts of landfill mining activities. Results will inform the development of risk assessment and health impact assessment studies to allow fuller implementation of landfill mining activities.

Food, Water, Waste Research Group

Faculty of Engineering
The University of Nottingham
Nottingham, NG7 2RD

telephone: +44 (0)115 82 32502