Faculty of Science, Engineering and Technology (FSET)

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ASSESSMENT OF QUALITY OF SHALLOW WELLS WATER IN CHUKA SUB-COUNTY, KENYA
(Chuka University, 2020-12) Rugendo, Edith Mwende
Groundwater from shallow wells is an important source of water for domestic and agricultural uses in Chuka Sub-County. However, most shallow wells in Chuka Sub-County are undocumented because approval is not required to sink a shallow well. Groundwater from these shallow wells is therefore susceptible to contamination by both geogenic and anthropogenic sources. This study was conducted to determine the quality of shallow wells water in Chuka Sub-County. Samples were collected from twenty shallow wells in Chuka Sub-County during the dry and wet seasons. The temperature, pH and conductivity were determined in situ using a conductivity meter. The concentration of cations in the water samples was determined using an Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) system. The concentration of chloride and nitrate ions in the water samples were determined using the argentometric and the spectrophotometric method, respectively. The concentration of sulphate ions was determined using a turbidimetric method while the concentration of phosphate ions was determined using a colorimetric method. The data obtained were subjected to ANOVA to test the significance differences using R-3.5.2. Mean comparison was achieved through LSD. The temperatures of the waters were significantly higher during the dry season. The pH of water in most shallow wells during the wet season was within the limits set by KEBS and WHO. However, shallow well water at Karandini (T15) was highly acidic (pH of 3.95) during the wet season. During the dry season, the shallow well waters were slightly acidic (4.42 - 6.44) except for the shallow wells at Ndagani market (T11), whose water was alkaline (pH = 8.75). The shallow wells water at site T11 had remarkably higher conductivities than the other shallow wells in the study area during both the wet (1150 μs/cm) and the dry (1208 μs/cm) seasons. The concentrations of macro-cations (Ca2+ and Mg2+) were higher during the dry season. The concentrations of the trace and toxic cations differed significantly across sites and seasons but were within the limits set by KEBS and WHO. The concentrations of anions (NO3-, SO42-, Cl- and PO43-) were within the limits set by KEBS and WHO for portable water. Groundwater from most shallow wells in Chuka Sub-County is generally safe for domestic uses but regular monitoring for quality is recommended because, the concentration of nitrate in several wells during the dry season was within the range that causes chronic health effects including colorectal, ovarian, thyroid, kidney and bladder cancers.
A CONVOLUTIONAL NEURAL NETWORKS AND SUPPORT VECTOR MACHINES HYBRID MODEL FOR NUMBER PLATE RECOGNITION
(Chuka University, 2022-03) Kibaara, Peter
ABSTRACT Automatic Number Plate Recognition (ANPR) systems are applied in many fields such as automatic electronic toll collection, car park management and access control, logistics and vehicle tracking, traffic law enforcement and crime resolution amongst others. Motion blur, plate orientation, lighting changes and image noise severely lower the detection speed and recognition accuracy of these systems. The incorporation of machine learning algorithms in ANPRs has seen Convolutional Neural Network (CNN) being used to develop ANPR models with improved performance in license plate detection. CNNs are best suited for image data where the number of features is large such as license plate detection. This is attributed to their design architecture which enables them to perform feature extraction automatically. However, their speed of execution is slow as the model has to learn a lot of features. Support Vector Machine (SVM) is a supervised machine learning algorithm suitable for classification and regression problems with datasets that have a small number of features. It doesn’t scale up well for large datasets with many features. It has demonstrated high speed and accuracy when used for classification in small datasets such as character recognition. The final stage in ANPR is a character recognition phase and involves few features. These two algorithms have been deployed independently, however the concept of combining the two algorithms for ANPR models remains highly unexplored. The research therefore combines the two models (CNN and SVM) to come up with an efficient hybrid ANPR system with improved number plate recognition accuracy. The two models were developed using a deep cascade framework; a CNN with a SoftMax classifier and a hybrid CNN with a SVM classifier. The Universidade Federal do Paraná (UFPR-ALPR) dataset was used to train validate and test the models. Recognition accuracy, precision, recall and F1 score metrics were used to evaluate the model. The hybrid CNN-SVM model had a recognition accuracy of 91.25% against 89.07 % from the pure CNN model. The weighted average precision, recall, and F1-score of the hybrid CNN-SVM was 92%, 91% and 91% respectively, which was better compared to that of pure CNN. The hybrid model was tested for external validity using the Smart Sense Laboratory (SSIG) dataset. The hybrid CNN-SVM model had a recognition accuracy of 91% against 89 % from the pure CNN model. The weighted average precision, recall, and F1 score of the hybrid CNN-SVM was 91%, 91% and 91% respectively which was better compared to that of pure CNN, which had 90%, 89% and 89% respectively.
FACTORS AFFECTING ADOPTION OF MANURE ON BANANA YIELDS IN SMALLHOLDER FARMS IN MAARA SUB COUNTY, THARAKA NITHI COUNTY, KENYA
(Chuka University, 2022-09) Kimetto, Jerono
ABSTRACT Banana (Musa ssp) is a widely distributed fruit and which is contributing greatly towards food security in the developing countries. In Kenya, banana is among the major food and cash crop produced by smallholder farmers as a source of income and food security. However, it has been associated with low productivity and income. Currently, banana production in Kenya is 14 t/ha-1yr-1, which is below the global average of 20.5 t/ha-1 yr1. The low production has been attributed to various factors such as poor agronomic practices, low soil fertility, poor markets, lack of farming capital and sociodemographic factors. Despite studies on most of these factors, information on dynamics of socio-economic factors on banana farming by smallholder farmers is ever changing due to change in climate and lifestyles. Therefore, there is need to continuously monitor and study the effect of these factors on productivity and income of banana farming. The study, therefore determined the effect of manure adoption on banana production in smallholder farms in Maara Sub County, Tharaka-Nithi County. Descriptive research design was used in the study. The study targeted 34,779 smallholder banana farmers. A structured questionnaire, open and closed ended, were used to collect the data. Data was collected on demographic socio economic, institutional factors and banana production. Data obtained was analysed using the SPSS version 26. Descriptive statistics were employed in the presentation of the results. The study revealed that majority of the banana farmers are above 53 years and majority (54.8%) of the farmers derived their seedlings from their own suckers. About 83.8% of the farmers have adopted manure while 16.2% of the respondents have not. The common variety planted by the farmers is Kampala represented by 30.73%. About 29.7% banana farmers own land sizes between 0.5-1.0 ha of land. The majority (97.3%) of the farmers privately owned their lands while 2.7 3% of the respondents leased the lands for growing bananas. It was established that majority (88.0%) of the adopters received extension services while adopters who had not received any extension services were being represented by 8.0 %. Majority of the farmers who belonged to a farmer group and were adopters of manure being represented by 82.0% respondents while farmers who and were adopters and did not belong to any farmer group were represented by 14.0%. The study sought to determine the socioeconomic factors that affect adoption of manure in smallholder farms in Maara Sub County. Logistic regression model was used to find out whether gender, age, highest level of education of decision maker, access to extension service, participation in a farmer group, labour and land size were significant in the adoption of manure. Education level of decision maker p = 0.007, Gender p = 0.000, land size p = 0.000 and participation in farmer group p = 0.003 and extension services p = 0. 027 were the factors that were found to significantly affect adoption of manure. Multiple regression model was carried out to determine the impact of adoption of manure on banana yield. The result showed that adoption of manure had an association with banana yield and was statically significant at p = 0.000. Most of the respondents were found to be literate. Therefore, illiterate farmers should be enlightened as education boost a farmer’s ability to decode information. Awareness should be created to encourage any member who has not registered to any group as is through such groups the information is disseminated. Extension services should also be well strengthened. The study recommends farmers to adopt manure as a way of increasing banana yields.
Formulation of Schrödinger Equation Using The Hilbert Space Operators Approach
(Chuka University, 2019-09) Mbatha, Elizabeth
Operators in Hilbert space have properties which are useful in the study of mathematical abstract areas such as approximation theory, Banach Fixed point theory, the spectral theory as well as Quantum Mechanics. Schrödinger equation is a fundamental entity with many applications in Quantum Mechanics. This equation was initially derived by applying the knowledge of electromagnetic wave function and Einstein theory of relativity. Later, it was derived by applying the knowledge of Newtonian mechanics. It was also derived by extending the wave equation for classical fields to photons and simplified using approximations consistent with generalized non-zero rest mass. However, from the existing literature no study has been done on deriving Schrödinger equation using properties of Hilbert space operators. In this study, Hilbert space operators that include unitary operators, self adjoint operators and compact operators, norms of linear operators, Hilbert Schmidt operator, normal operators together with Lebesque Integral, Neumann Integral and spectrum are used in place of the existing concepts of electromagnetic wave function, Einstein theory of relativity and approximation consistent with generalized non zero mass to derive the Schrödinger equation. Furthermore, this study has established the correlation between the electromagnetic wave function and Einstein theory of relativity in relation with Hilbert space operators. Application of Hilbert space operators on Quantum observables such as position, momentum and energy of a particle has been done in these study. The derivation of Schrödinger enhances equation and its application using Hilbert space operators have enhanced a better understanding of the concept of Schrödinger equation. The results of this work will be useful in quantum mechanics as well as in mathematical operator theory.
INCIDENCE AND PREVALENCE OF FUSARIUM WILT AND PHYTOCHEMICAL ANALYSIS OF CRUDE EXTRACTS OF Tithonia diversifolia (Hemsl.) A.Gray AND Kigelia africana (Lam.) Benth AND THEIR ANTIMICROBIAL ACTIVITIES AGAINST Fusarium oxysporum IN TOMATOES
(Chuka University, 2020-12) Awere, Collince Omondi
Kenya is one of the leading countries in Africa in tomato production. Production of tomato is 14% of the total vegetable and 6.72% of the horticultural crops produced in the country. It is a source of food, foreign exchange earnings and source of employment and income. The major factor that reduces the growth and yield of tomato production in Kenya are pathogenic microorganisms. For instance, Fusarium oxysporum is among the fungal pathogens that destroy the xylem of the plant hence causing Fusarium wilt due to poor transportation of water to various parts of the plant. Besides, it persists in the soil environment for a long period thus continuously infecting healthy plants grown in the site. The management practices that are mostly used to control the pathogen are ineffective and environmentally unfriendly. Therefore, plant products with antimicrobial properties present an affordable alternative solution to control such persistent pathogens. The objective of this study was to determine the incidence and prevalence of Fusarium wilt and the phytochemical composition of Tithonia diversifolia and Kigelia africana and their antimicrobial activity against fungal pathogen F. oxysporum in tomatoes. Tithonia diversifolia and Kigelia africana plants were selected because of their wide medicinal use, distribution and availability. A preliminary survey was carried out in Mwea, Kirinyaga County which is among the most common areas where tomatoes are grown. Questionnaires were used to evaluate the farmers` knowledge, perception and management practices of Fusarium wilt disease. A total of 80 respondents were interviewed. K. africana and T. diversifolia plant samples were collected for phytochemical analysis. The samples were ground into a fine powder and extracted using water. Phytochemical screening of the crude extract was done. Soil was used for F. oxysporum pathogen isolation. Antimicrobial test disc soaked with plant extract was placed on to the media cultured with F. oxysporum and incubated at 28 oC for a week to allow growth. Analysis of the collected data was done using SAS version 9.4 for analysis of variance and further subjected to a post adhoc test with 𝛼 = 0.05 being considered significant. The results showed that the Rio Grande was the tomato variety widely grown; the preference for this variety was attributed due to its high marketability, high production, high quality, and early maturity. From the response, 92.5 % of the farmers had seen the symptoms of the pathogen while the rest had not seen the symptoms of the pathogen in tomatoes. The application of chemicals was widely used to control the pathogen, which contributes to environmental pollution. Screening of the plant extract revealed the presence of tannins, alkaloids, flavonoids, saponins, terpenoids, and glycosides. Each of the plant extract used had antimicrobial activity against F. oxysporum; this was due to the presence of phytochemicals that had an effect on the growth of the pathogen. K. africana exhibited the highest zone of inhibition while T. diversifolia had the lowest zones of inhibition. When each crude extract was used singly and in combination against the F. oxysporum, the zone of inhibition was found to be statistically significant at P< 0.05. The combined crude extract showed an increased antimicrobial activity against F. oxysporum. The results provide a potential application of the crude extract as an antifungal agent against F. oxysporum. It also provides scientific evidence that K. africana and T. diversifolia extract possess antifungal activity that can be used as a broad-spectrum in managing microbial diseases.
LEVELS OF SELECTED PHTHALATES FROM WASTEWATER TREATMENT PLANTS IN LAKE VICTORIA CATCHMENT AREA AND THEIR ADSORPTION ONTO WATER HYACINTH BIOCHAR
(Chuka University, 2020-12) OGORA, ELKANAH NYAKWAMA
Endocrine disrupting chemicals (EDCs) disturb the endocrine system’s functionality causing negative effects on health in an organism and its progeny. They can interfere with natural hormone cycles in humans or animals, potentially affecting metabolism, development, reproduction and growth. Phthalates are among the many examples of EDCs, which have been used as plasticizers for longtime around the world. Due to their extensive usage, they are found in many surface waters, sludge and waste waters. The occurrence of phthalates in water, and their exposure to non-target organisms cause adverse effects such as congenital anomalies, endocrine disruption and chronic toxicity. This study determined residual levels of three phthalates namely; dimethyl phthalate (DMP), benzyl butyl phthalate, (BBP) and bis(2-ethylhexyl) phthalate (BEHP) in wastewater sampled from wastewater treatment plants (WWTPs) of Nyalenda, Homabay and Kisii during wet and dry seasons. The wastewater samples were extracted and cleaned by solid phase extraction cartridges (SPE) ready for high performance liquid chromatography (HPLC) for quantitative analysis. Most of the sites sampled had detectable levels of DMP, BBP and BEHP in wastewater. High concentrations were detected during wet season compared to dry season in all sampled sites. Nyalenda WWTP recorded the highest concentrations of phthalates than Homabay and Kisii WWTPs. The concentrations of all selected phthalates were recorded highest at the inlet sampling points from all WWTPs, in both seasons sampled. Almost all the selected phthalates were below the limit of quantification (LOQ) at the outlet sampling points of Homabay and Kisii WWTPs in both seasons. The residue levels obtained showed significant differences at 5% confidence limits with zcal for all phthalates in all WWTPs less than the critical value (Zcritical = 1.96). Therefore, the null hypothesis was rejected. Consequently, a cost-effective technique of removing DMP, BBP and BEHP from their solutions using water hyacinth biochar (WHB) as an adsorbent was investigated. A mass of 0.1 g of WHB both before and after adsorption was used for characterization process. Elemental analysis of WHB was determined using XRF (EDXRF), the XRD patterns were obtained using bruker operating with Cu Kά(λ = 1.541nm) and samples scanned in coupled TwoTheta/Theta. The FTIR spectra were obtained between 4000cm-1 and 400cm-1 using Shimadzu type. The adsorption process was done using an orbital shaker agitated at 125 rpm and residual levels determined using the HPLC. The optimum conditions obtained from the adsorption of DMP, BBP and BEHP onto WHB were as follows; equilibrium time was 25 minutes, maximum adsorbate concentration adsorbed at 0.1 g of WHB was 4 mg/L, temperature of 298 K was appropriate and 0.8 g of WHB was effective for the adsorption of above 67% of 10 mg/L of each selected phthalate. The kinetic data fitted the pseudo second order model with regression values for DMP, BBP and BEHP found to be 0.9987, 0.9984 and 0.9986, respectively. The Freundlich model demonstrated to be a good model for fitting the adsorption data, which was attributed to heterogenous distribution of charged functional groups at adsorption sites of WHB’s surface. The calculated thermodynamic parameters, namely; change in Gibb’s free energy (ΔG), change in enthalpy (ΔH) and change in entropy (ΔS) showed that the adsorption process was favorable, exothermic, spontaneous and of a physical type. This was due to the fact that all of them were negative values. Dimethyl phthalate was the most effectively removed by WHB as adsorbent. The removal efficiency decreased with increasing molecular weight of the phthalates. The findings demonstrated that WHB is a good low cost and environmentally adsorbent for removal of phthalates from water.
Modelling and Application of Response Surface Methodology for Optimization of Weight Gain of Eight Weeks Old Kenbro Served With Pumpkin (Cucurbita Pepo L) Seeds Extract
(Chuka University, 2019-09) Kinyua, Charles Mugendi
Extensive use of synthetic growth promoting antibiotics have become a threat to public health. Therefore, there is a need to search for bioactive phytochemicals that have positive effects on immune, growth and appetite status of the chicken. Such bioactive compounds can be obtained from plants. Pumpkin seeds have been found to be a valuable source of protein and bioactive compounds. Mathematical models have been used to study the effect of pumpkin extracts on the weight gain of chicken. However, most of these studies have focused on the levels of the application of pumpkin extract, rather than on optimising the levels of application on the weight gain of the chicken. Optimization is important since it provides information on the amount of pumpkin seed extracts that should be fed to the chicken without wastage. This study was conducted to evaluate the weight gained by the Kenbro chicken served with pumpkin (Cucurbita pepo L) seeds extract and examined the possible combination of the number of weeks and quantity of pumpkin seed extract that can result in maximum weight gain of the Kenbro chicken. The experiment was conducted using Random Complete Block Design at the poultry demonstration unit of Chuka University. Sixty- day old Kenbro chicks were randomly distributed to five treatments which contained 0, 50, 100, 150 and 200 ml of pumpkin seed extracts per litre of water. Each treatment was replicated three times with four chicken per replicate. The birds were fed with the same diets of finisher and starter feeds. The chickens were provided with enough feeds and water ad libitum in the morning at 8 am. The birds were weighed at the beginning of the experiment and thereafter at an interval of three days for eight weeks. Data was analysed using R statistical software. A Response surface model was fitted to the data and subjected to contour plots to characterize the nature of its turning point and to capture the combination of the number of weeks and quantity of pumpkin seed extract that brings maximum weight gain of the Kenbro chicken. The results showed that the average body weight gained was significant (p < 0.05). The birds served with 200 ml pumpkin seed extract for 4 weeks had the highest weight gain. The fitted Response Surface Model indicated that the number of weeks and quantity of pumpkin seed extract together with their interaction significantly (p < 0.05) determined the weight gain of Kenbro chickens. The study found that the quadratic model fitted using the data had an adjusted R-Squared value of 0.78. The optimal weight gain of 0.23 kg was achieved when the number of weeks was 3.18 with 192.40 ml of pumpkin seed extract. The number of weeks, pumpkin seed extract and their interaction play a key role in obtaining maximum weight gain of the Kenbro chicken. These factors should be put into consideration when developing a feeding system for Kenbro chickens. The study also guides the farmers on the optimization of Kenbro chicken production without incurring an extra cost in the input.
Modelling the Effects of Mindfulness Based Stress on Breast Cancer Survival Rate among Women in Meru and Nyeri Counties, Kenya, using Cox Proportional Hazard Model
(Chuka University, 2019-09) Mutwiri, Mwendwa N.
Breast cancer remains the most commonly diagnosed cancer among women, affecting 34 women per every 100,000. This has led to high number of fatalities annually, which need to be mitigated. The main interest among many cancer survivors and their families is establishing other conventional therapies they can engage in to improve their prognosis and survival. Among some of the key therapies is the interest in working on mindfulness-based stress (MBS) that patients undergo after diagnosis as complementary and alternate measures. Regardless of this, there is little that is known about the effects of MBS factors on breast cancer survival. Management of breast cancer can be enhanced through modelling the effects of MBS on breast cancer survival rate. However, there is limited information on accuracy of existing models. This study focused on developing a model to predict the effect MBS factors have on breast cancer survival rate among women in Meru and Nyeri Counties. Both Primary data and Secondary data were used. Primary data was obtained using a structured questionnaire from the breast cancer survivors and the medical practioners while secondary data was obtained from records at Meru teaching and referral hospital and Nyeri level five hospital on the MBS variables (cost burden of treatment, stress on diagnosis, prolonged time taken to access treatment, poor diet, alcohol use, physical activity and lack of awareness) among breast cancer patients for the period 2012 to 2017. Mixed method research design was used in the study. Both quantitative and qualitative data used in the study was analysed using R software. Cox proportional hazard model was used in establishing the survival rates, with the breast cancer survival rate being dependent variable while MBS factors were the independent variables. Kaplain-Meier estimators were used in determining the varying effects which the MBS factors have on survival rate. Log-rank test was used to perform comparisons of survival curves using hypothesis tests on the patients‘ survival rate considering age. The likelihood ratio test showed that MBS factors are significant in predicting hazard rates ( = 66.7, p = 0.0000119). Treatment period was highly statistically significant (p = 0.00014) as compared to other covariates. Lack of awareness (p = 0.0010124), ease of coping with stress (p = 0.000514) and observing the right diet (p = 0.04092) were also found to significantly affect survival rate. Access of treatment immediately after diagnosis, availing the right information to the patients, helping patients to cope easily with stress and observing the right diet were found to be the best estimators in increasing breast cancer survival rate. The study therefore recommends use of the model in predicting breast cancer survival rates which can greatly improve breast cancer prognosis.
ON CHARACTERIZATION OF PERMUTATION GRAPHS
(Chuka University, 2020-12) Nyabate, Nyabuto Fancy
Graph theory is an area in discrete mathematics with numerous theoretical developments and many applications to practical problems in computer science, chemistry, biology and operational research. As a result, it has attracted much attention to researchers in many dimensions including graph labeling, graph coloring, combinatorics, graph isomorphism, matroid theory and graph representations among others. Many researchers in this area have also worked on permutation graphs paying attention to the properties of cyclic permutation graphs, including crossing numbers and isomorphism. So far isomorphism between two cyclic permutation graphs has been determined by positive and negative natural isomorphism. However, construction of other classes of permutations graphs and establishing an alternative approach for determining isomorphism between permutation graphs as well as finding some properties of permutation graphs would be of significance. The aim of this study was to develop a class of permutations, determine algebraic properties of the permutations, construct permutation graphs and establish some properties of the constructed graphs including isomorphism. A class of [nxk - permutations was first obtained by coming up with a bijection on a finite set, which resulted into permutations. Some algebraic properties were established, in particular, the permutations resulted in an abelian group as well as it formed a subgroup. Graphs were then constructed from these permutations and some properties including symmetry, unique, connectedness, distance and isomorphism determined by enumeration. The results of this research are of significance in other practical areas of application of graphs, including computer science, chemistry, biology, operational research and combinatorics.
SECURE CLOUD BASED APPROACH FOR MOBILE DEVICES USER DATA
(Chuka University, 2022-02) Mbae, Oscar
ABSTRACT In this era characterized by rapid technological innovations, mobile devices such as tablets and smartphones have become inevitable due to the variety of services they offer. As a result, computing capacity as well as storage needs of these devices are increasing tremendously. To ensure users continue to enjoy the portability, flexibility and accessibility that these devices continue to provide, there is need for a secure and user friendly data storage solution. However, despite the benefits of this technology, there are increased risks to the information that is accessible from the mobile devices. The main problem is the risk of private and confidential data being exposed to unauthorized persons and the risk of permanent loss or damage of that data. These problems are escalated by the fact that most information is stored in the devices’ internal memory, making them easily accessible. Mobile devices are susceptible to loss and the pins and patterns used as security controls are easy to by-pass because they have minimal encryptions. In the event of human error whereby the user forgets to delete downloaded confidential content from cloud-based platforms, it remains in the mobile device from where it can be accessed easily. This creates a need for secure ways of storing data in a cost-effective and convenient manner. The objective of this study was to design, implement and validate a secure cloud based approach for mobile devices’ user data. The study adopted design and development methodology which followed the entire design and development process from analyses to evaluation. From this methodology, the research employed the strategy of mixed method using a systematic process of collecting data, at first during prototype and then throughout the rest of study. This method allowed for continued development and implementation of the product. The solution was prototyped in an android based environment and developed using Java programming language together with MySQL for the database. The mobile data privacy solution proposed by this study provides a security solution to users to be able to store sensitive data and access it on their mobile devices. The solution focuses on securing the data on the mobile devices by storing it in an encrypted format and uploading it to the cloud. In addition, the downloaded data is timed to self-destruct after user consumption, eliminating unauthorized person or application from reading the information without a decryption key. The developed solution was able to provide security for the users’ confidential data while making it available. The tool enabled its users to store the selected sensitive files from their mobile devices in an encrypted format. To achieve this, we used the algorithm AES 256 to encrypt the data with a key only known to the user and upload it to the cloud for secure storage. The secure mobile tool was developed and fulfilled the requirements specification successfully. It met all the security parameters stated hence optimizing mobile user data storage security.
STRUCTURAL, OPTICAL, AND SURFACE POTENTIAL CHARACTERIZATION OF NICKEL, ZINC DOPED MAGNESIUM FERRITES SYNTHESIZED USING SOL-GEL AUTO-COMBUSTION METHOD
(Chuka University, 2022-09) ALEX, NJOROGE
Nano-sized spinel ferrites have attracted heightened scientific focus due to their interesting structural, morphological, magnetic, optical, and electrical properties. Metal substitution in the structural equation of the spinel ferrite (MFe2O4) plays important roles in the modification of its physical properties in order to suits specific applications, like gas sensing. Recently, air pollution has greatly increased, e.g., leakage of liquid petroleum gas (LPG). This lead to deaths, fire outbreaks and other health complication. As a result, there is demand for effective gas sensors with lower limits of detection. Sensing material especially the ferrites are limited in their sensitivity and operate at high temperatures. Among the ferrites, Mg-Zn ferrites are most important magnetic oxide due to their properties. Substitution of any magnetic ion by replacing Zn2+ in Mg-Zn ferrite plays an important role in modifying its properties and hence enhancing its sensing properties. This work, aimed at contributing to the effort focused to improve ferrite sensing properties and overcome these limitations by ternary ionic substitution. Consequently, NixZn0.5-xMg0.5Fe2O4 (x = 0, 0.1, 0.3 and 0.5) ferrite nanoparticles were synthesized by Citra gel auto-combustion method at a pH 7 and characterized for their structural, elemental composition, electronic and optical properties. Pre-elemental analysis by x-ray fluorescence revealed the expected stoichiometry of the synthesized nanoferrites with low amount of impurities. X-ray Diffraction analysis confirmed cubic spinel nature of the samples with crystalline size between 26.90-43.34 nm using Debye Scherrer equation, 8.94 – 26.38 nm using Modified Debye Scherrer plots and 11.60 – 23.86 nm using Halder Wagner plots. The most intense peak was at a miller indices (311), which is a characteristic of a spinel ferrites. Nickel substitution brought variation in the lattice constants which were in the range of 8.3436 – 8.4149 Å. Both Williamson – Hall and Halder- Wagner plots revealed all sample to possess compressive micro strain. Further structural properties by Fourier transform spectroscopy showed prominent peak at range of 350 – 450 cm-1 which are vibration of metal oxygen bond in octahedral sites while vibrations at 500 – 600 cm-1 which are vibration in tetrahedral sites, a characteristics of spinel ferrites with metal oxygen bond stretching. Optical properties by UV-Vis showed the samples optical band gap in the range of 4.19 – 4.21 eV, refractive index in the range of 2.048 – 2.562 and optical dielectric constant in the range 5.062 – 5.070. Kelvin probe scans revealed a low potential material and more interesting was the negative surface potential. The work function for the area scan was in the range 4.536 – 4.588 eV while for the line scan was in the range 4.341 – 4.5673 eV. Electrical conductivities of the samples were found to increase with increase in nickel content, this was determined from the calculation of length jump which was found to decrease from 2.975 Å to 2.942 Å. Similar results of variation of electrical conductivity were found by calculation of unshared edges which were found to decrease with nickel content from 6.9773 – 6.9181 Å. In summary, the synthesized nanoferrites have properties which could find their applications in fabrications of effective gas sensors, based on their size, band gap, length jump, and surface potential obtained.

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