Preparation of solid biofuel derived from palm kernel shell waste via pyrilysis and hydrogenation process

The need for energy is always expanding along with industrialization and population increase, and the availability of energy supplies cannot keep up with the mounting consumption. In 2000, one estimate predicted that about 20 million metric tons of CO2 will be released into the atmosphere yearly. While this pattern continues, extreme natural catastrophes, such as excessive rainfall and the ensuing floods, droughts, and local imbalance, are to be expected. The world's oil reserves are expected to run out by 2050. Considering the mentioned aspects there has been an elevating demand for renewable resources of energies. One of such mentionable sources of energy is palm oil leftovers or palm kernel shells (PKS). Low moisture content, compact and having a high calorific content are some of the mentionable factors contributing to the popularity of PKS. Considering the mentioned aspects, in this study, the potential of palm kernel shell waste as a solid biofuel by using pyrolysis and hydrogenation process has been evaluated along with analysing the impact of temperature in achieving a higher calorific value. In order to evaluate the heating values of the samples, Bomb calorimeter has been used and TGA analysis has been performed to evaluate the impact of temperature and associated changes in the weight of the sample. For analysing the compound group present in the samples, FTIR analysis has been conducted. The highest heating value of 25.96 MJ/kg was obtained for sample prepared at 300oC hydrogenation temperature at 1 hour with the use Ru/Mn/ce-65 as catalyst. Significant C-H stretching and vibration was observed at 2850 – 3000 cm-1 and 1120-1250 cm-1 wavelength which indicate increasing C-H adsorption at carbon surface that become a major contribution to higher heating value. In addition to that, temperature has been observed to have major impact on the performance of the samples in attaining higher calorific value as compared to reaction time. Therefore, PKS proved to have a great potential as green waste to be used as a high-quality solid biofuel for combustion purposes

Assessment of Blastability Index in massive limestone from Rawang Quarry, Selangor

The demand for construction materials produced by quarry rises in tandem with urbanization. Selangor is one of the highly populated states in Malaysia with residential projects now located very close or even next to quarry. Due to the fact that limestone consists of numerous weak spots in rock masses, it has always been thought that limestone quarry operation is riskier than common granite quarry operations. Geologically, limestone formation in Rawang sits uncomfortably on top of the older metamorphic rocks with its own unique joints system. The goal of the study was to identify the rock mass properties in massive limestone profile from a quarry in Rawang, Selangor and its relation to blast design as well as effects on the surrounding environment due to blasting. For a systematic study, the quarry face was divided into four (4) sections i.e., section A, section B, section C, and section D. The site mapping showed significant findings where section A is considered high potential of having excessive flyrock as it has the most joint number (J), joint plane spacing (JPS) and joint aperture (JA) with 31, 559.8 mm and 28.5 mm, respectively. When blasthole intersected with many joints, explosive energy escape through joints causing sudden drop in blasthole pressure and open joints extend up to the face thus creating high possibility of flyrock during blasting. The degree of difficulty to fragment rock in terms of Blastability Index (BI) was also calculated based on the geological mapping data. The results show that BI ranged from 49.18 to 59.26 percent throughout all study sections indicating that the rock mass at the quarry was easy to be blasted as per Blastibility Quality System (BQS). The calculated BI was also justified the suitability of blast design used during blasting at the quarry. The new site constants i.e., K and β for the study area were also calculated with USBM predictor at 40 and 1.0, while Langefors- Kihlstrom (LK) predictor at 6.8 and 1.07, respectively. Although at maximum charge per delay (Wmax) the blasting was being carried out safely with very minimal effects to the surrounding areas. Finally, correlations between all earlier findings such as BI, blast design and environment effects i.e., peak particle velocity (PPV) measured and predicted were justified the significant relation of rock mass properties and ground vibration effect due to blasting operation at the quarry

Photocatalyst composites of zinc oxide-doped titanium dioxide modified with sodium silicate for antibacterial applications

Superbugs have troubled and challenged mankind since the development of antibiotics could not keep up with the rate of bacterial evolution. To avoid cross-contamination, the emphasis should be placed on effective protection beginning with the surroundings. This study concentrated on the rapid sonochemical synthesis of photocatalyst sodium silicate loaded titanium dioxide and zinc oxide (TiO2@ZnO_Na2SiO3) composites as an antibacterial agent using short synthesis time and less hazardous solvents. Anatase was obtained as evidenced by X-ray diffraction (XRD) and high resolution transmission electron microscopy (HRTEM) analyses. Meanwhile, bonding present between the main element of the synthesized sample were confirmed by Fourier transform infrared spectroscopy (FTIR). Visible range was obtained for TiO2@ZnO samples while near ultraviolet range was obtained for TiO2@ZnO_Na2SiO3 samples as depicted by diffused reflectance ultraviolet-visible spectroscopy (DR UV-Vis). All TiO2@ZnO have lower recombination rate compared to ZnO whereas all TiO2@ZnO_Na2SiO3 samples have lower recombination rate compared to TiO2@ZnO (TiO2:ZnO = 1:0.1) composite as observed under fluorescence spectroscopy. All composites have irregular shape as noticed under scanning electron microscopy (SEM). Variation of ratios in TiO2:xZnO (x = 0.1, 0.2, 0.3, 0.4, and 0.5) and TiO2@ZnO_yNa2SiO3 volume percent (y = 2, 4, 6, 8, and 10) were made to obtain the best ratio for highest antibacterial activity. [email protected] was determined to be the optimal ratio by evaluating both physiochemical properties and antibacterial performance. [email protected] had a bacteria killing efficiency (BKE) of 78.68% against S. aureus and 99.99% against E. coli, due to its smallest crystallite size (55 nm), lowest band gap energy (2.68 eV), and lower recombination rate. The optimal ratio of TiO2@ZnO_10Na2SiO3 was obtained after further modification of previous ratio of [email protected] with Na2SiO3, which achieved a lower band gap energy (3.10 eV) and the lowest rate of recombination amongst other variants, with a BKE of 81.36% against S. aureus and 99.99% against E. coli. As seen under HRTEM image and amorphous XRD pattern, the loading of Na2SiO3 outside of TiO2@ZnO was successful. Therefore, this study has successfully synthesised a new antibacterial agent TiO2@ZnO_Na2SiO3

Chiller energy savings by waste cold recovery from liquid nitrogen bulk

Waste cold energy generated from the liquid nitrogen vaporization is usually abandoned when the gas supply system is pre-designed without cold integration. The purpose of this study is to investigate the potential for energy savings in a chiller system through the integration of waste cold recovery with thermal energy storage. The waste cold recovery system captures the waste cold generated during the operation of the liquid bulk nitrogen system and transfers it to a thermal energy storage system. This stored energy can then be utilized to supplement the chiller system during the targeted periods of peak demand, reducing its load and increasing its efficiency. The minimum of thermal energy storage capacity is determined by targeting the maximum peak shaving load through Cold Energy Storage Cascade Analysis (CESCA). The study analyses the feasibility of the waste cold recovery method in terms of energy savings, payback period and cost-effectiveness with peak load shaving of air-cooled and water-cooled chiller. Case study of 500 kg/h of liquid nitrogen revealed the significant energy savings at 124 MWh annually and avoided of 83 tCO2/year with minimum thermal energy storage capacity at seven tones of refrigeration. The simple payback period on air-cooled chiller is slightly better than water-cooled chiller which ranged from four to five years. The study concludes that the integration of waste cold recovery with thermal energy storage is a promising solution for liquid bulk nitrogen users looking for energy savings efforts and reduce their carbon footprint

Energy efficiency improvement and renewable energy implementation for copra oil extraction process

The global demand for coconut oil has become more as the shortage of raw material and war happening across the world. Each country needs to find or ensure they have adequate supply of food for the internal usage. The current copra oil extraction method is similar to other seeds available which is using the expeller press method. The process has been in the market for very long and has been used by most of the copra producers. To ensure the market player has a more competitive processing plant in terms of energy efficiency and less impact to the environment, this research help to fill the major gap which helps to reduce the impact. To do benchmarking and to obtain live data, the suitable key energy consumption indicator is identified based on the performance of the current operational system and all necessary improvement is added as needed to increase the production rate while reducing the energy consumption of the overall plant. All data and information is collected based on actual operation of a plant. The plants performance has been monitored and a lot of improvement needed to be done on many part of the operational features. The main feature which we have studied and implemented is the additional plant which is called the “Solvent Extraction Plant”. The adding of this feature will actually increase the overall capacity of the plant by nearly 40% while maintaining or reducing the overall energy consumption of the plant by 5%-8%. Other than the above improvement, Renewable energy is also implemented on the plant. 2 type of RE is implemented which is the Solar power system which will substitute or reduce the usage of the Grid supply by 5% with the available space. The capacity of the solar system can be optimized by increasing the space or changing the solar panel spec to a higher efficiency panels. As for the Biomass Boiler which is introduced to the plant, the main function to reduce the dependency on the bunker oil and to reduce carbon footprint. The biomass boiler is considered good for this plant as they have abundance of coconut shell which is underutilized at this moment. Thus we have the opportunity of fine tuning the copra extraction plant energy efficiency while increasing the overall capacity, our main aim is to improve and extend the same solution or technology to other Copra extraction plants in Malaysia. Even if a lot of players are aware of the technology but they have not implemented on the solution because of lack of experience and working models

Development of drilling non-productive time reduction framework using lean six sigma methodology for buntal exploration wells

Drilling Non-Productive Time (NPT) is loss time incurred when drilling activity has to be stopped or rate of penetration is very low during a drilling operation. Drilling NPT results in drilling cost overruns and delay in drilling schedule. Presently, there are several methods which are being deployed to mitigate drilling NPT and these methods would fall into either the anticipative or targeted category. Anticipative category focuses on development of model, database, and risk management framework to enhance information sharing and decision-making among drilling operation stakeholder while the targeted category revolves around deployment of surgical solutions which focus on one or a handful of drilling NPT categories such as wellbore instability, equipment failure etc. Both categories generally lack Drilling NPT severity assessment, validation of Root Causes and derivation of Root Cause Analysis-centric solutions, resulting in knee-jerk reactions to Drilling NPT mitigation. This study, therefore, aims to develop a Drilling NPT reduction framework using Lean Six Sigma (a process improvement methodology) based on retrospective drilling data from Buntal Exploration Wells. Lean Six Sigma advocates data-driven analytics and decision-making in solving operational problems. The drilling NPT reduction framework will follow the DMAIC (Define, Measure, Analyse, Improve and Control) stage-gate model of Lean Six Sigma. In the case of Buntal Exploration Wells, it is observed that the drilling process is not capable from operational and financial standpoints in meeting the Drilling Plan requirements (as illustrated by Process Capability Indexes which are lower than 1.0). In view of retrospective nature of the available drilling data, root causes are validated graphically and qualitatively with equipment failure appearing as the leading contributor of Drilling NPT. Potential solutions are then ideated based on the validated root causes or Vital Few Factors. It is expected that the Drilling NPT reduction framework will pave way for future research through capitalization on quantitative data and continuous feedback from the drilling fraternity

The characteristics and potency of limestone-based carbonate hydroxyapatite to viability and proliferation of human umbilical cord mesenchymal stem cell

Background: Limestone primarily consists of CaCO3 (calcium carbonate), which have a similarity to one of human bone component, hydroxyapatite (HA), an element of apatite group (Ca10(PO4)6(OH)2). There were several setbacks in the use of artificial hydroxyapatite in the bone repair process; one of them was its relatively higher crystallinity level compared to those of human bone apatite. The addition of carbonate element to hydroxyapatite could improve its characteristics, such as increasing the solubility, decreasing the crystallinity, and changing the morphology of the crystal. That caused carbonate hydroxyapatite is preferable to help in the bone repair process. Aims: This study aimed to find the effect of limestone-based CHA on viability and proliferation of hUMSCs, thus discovering the potential of CHA as a bone graft biomaterial candidate derived from limestone. Methods: This study used FTIR, EDX, and XRD assays to CHA powder sample derived from limestone found in Padalarang and Cirebon extracted by BBK. Two grams of the sample were placed in the sample holder and examined by computer software. EDX assay was conducted three times in three different points, and the means were recorded. In the XRD assay, a carbon tip was put to the sample holder to allow sample attachment. The recorded data was compared to JCPDS data. Toxicity and proliferation examination of CHA were conducted through MTT assay in human umbilical cord mesenchymal stem cell (hUCMSC) cell lines with four different doses: 50µg/ml, 25µg/ml, 12,5µg/ml, and 6,25µg/ml. Results: Limestone-based CA has hydroxyl (OH-), phosphate (PO42-), and carbonate (CO32-) functional groups. It has crystal particle formation and consists of O, Ca, and P elements. The result of the MTT assay showed limestone-based CHA is not toxic in all concentrations and has the proliferative ability. There were significant differences between the control and treatment groups. Conclusion: CHA has OH-, PO42-, and CO32- function group. It has crystal particle formation and O, Ca, and P elements as its composition, with a Ca/P ratio of 1,67. It shows no toxicity to hUCMSC in all doses and has the ability to stimulate hUCMSC proliferation

Self-perceptions and actual performance of critical reading skills among Malaysian engineering students

Students at any level need critical reading skills, especially in higher learning institutions. Students are required to extensively read, critically engage, and carefully question the content quality and factual veracity. In the era of information technology, anyone can create and publish information without peer review. Although the importance of critical reading skills is generally acknowledged, little is known about the critical reading skills of Diploma level students in the local context. Thus, this article examines Diploma students' critical reading abilities based on self-perceptions and performance when reading English texts. The study employed a quantitative research method based on a descriptive survey design. The research sample consisted of 44 engineering major Diploma students selected using a simple random cluster sampling design from a university in the southern region of Malaysia. Data was collected using a questionnaire. Besides, a critical reading comprehension test was distributed online through course teachers. Prior to collecting data, the questionnaire and the comprehension test were subjected to reliability testing. The findings indicate that Diploma students overestimated their critical reading skills compared to their actual performance, as they scored below average for some of Bloom’s Taxonomy critical thinking skills. It is believed that the findings of this study would assist teachers in developing novel techniques to help students develop critical thinking skills. The pedagogical implications for language acquisition and instruction and future potential study areas are also discussed

Partially hydrolyzed polyacrylamide apparent viscosity in porous media enhancement by silica dioxide nanoparticles under high temperature and high salinity

Polymer flooding effectiveness is hindered by high temperature and high salinity due to polymer degradation. Researchers proposed the addition of nanoparticle to improve polymer stability to withstand reservoir conditions. Therefore, extensive rheological study and flooding test of partially hydrolyzed polyacrylamide (HPAM) solutions with silica dioxide nanoparticles (SiO2 NPs) were carried out under high temperature and high salinity conditions. Shear viscosity of HPAM-SiO2 NPs in rheological study was measured using rheometer while apparent viscosity in porous media was calculated from flooding test and modelled using a numerical model. Apparent viscosity includes shear viscosity and elongational viscosity. Shear viscosity was estimated from Carreau-Yasuda model and elongational viscosity was correlated with Deborah number via relaxation time. At T=80°C the shear viscosity and apparent viscosity in porous media of HPAM-SiO2 NPs are 50% and 64% higher than HPAM. The results further shows that HPAM-SiO2 NPs' shear viscosity and apparent viscosity in porous media at 60,000 ppm of NaCl are 39% and 53% higher than HPAM, respectively. Nevertheless, enhanced apparent viscosity of HPAM-SiO2 NPs was owed to the formation of stable and dense interwoven HPAM molecules induced from the hydrogen bonds and alkoxysilane (Si-O-Si) crosslinks between SiO2 NPs and HPAM. This study suggested that the addition of SiO2 NPs could significantly improves the HPAM apparent viscosity in porous media under high temperature and high salinity producing ideal mobility control agent

Fake news detection on social media platforms using machine learning algorithms

The rapid growth of advanced technology and social media platforms has changed the way of retrieving information or news for the whole world. However, it is undeniable that there is some fake news which is purposely created to disseminate false information to the public. The rapid spreading of fake news brings a significant negative impact on individuals, culture and country. Although there are some existing fake news detection methods like manual fact-checking websites and tools, they are time-consuming for fake news detection and cannot provide real time detection. Hence, an automated machine learning based approach is required for fake news detection since fake news can be disseminated rapidly through online social media platforms. This project aims to propose and construct an effective hybrid machine learning based algorithm for automated fake news detection. This algorithm will assist people in differentiating real and fake news, reduce the threats to national security by preventing the wide spread of fake news and maintain the news ecosystem's genuineness equilibrium. The project flow started with the dataset collection which includes both real and fake news. This dataset is publicly available and it is obtained from Kaggle website. Next, some text pre-processing techniques, i.e., lower case conversion, punctuation and stopwords removal and lemmatization will be applied to the raw data. Furthermore, Term Frequency – Inverse Document Frequency (TF-IDF) is the technique applied for text vectorization in this project. Two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM) are implemented to classify the real and fake news. In addition, two hybrid ensemble models, namely voting classifier and stacking classifier are constructed by combining three individual base classifiers, i.e. RF, SVM and Logistic Regression (LR). Hybrid ensemble model is an approach that combines several models to improve the prediction accuracy. These hybrid classifiers can detect fake news in real time and effectively prevent the fake news from being disseminated widely through social media platforms. In this project, stacking classifier performs better than voting classifier, achieving an accuracy of 91.06% as compare to the classification accuracy of 90.41% obtained by voting classifier