Scientific Applications Research Articles

Preface

Introduction Under the patronage of H.E. Prof. Mahad Said Ali Baawain, Minister of Labour, the University of Technology and Applied Sciences (UTAS) - Suhar, Oman, has hosted the Second International Conference on Environmental Science and Engineering for Sustainable Development (ESESD 2024) on March 6th and 7th, 2024, continuing the event’s successful first iteration, which was held in March 2022. The conference provided an excellent forum for exchanging knowledge and findings in the theory, methodology, and applications among academicians, industry professionals, researchers, and students, who have presented their latest research outcomes, as well as solidifying networks. Prominently, the attendees have discussed how to use scientific ideas and cutting-edge technology to explore potential novel, sustainable solutions to pressing environmental problems and to foster new partnerships in various fields include, but not exclusive to: Carbon Neutrality, Pollution and Carbon Emission Management, Renewable Energy, Circular economy, Applications of Nanotechnology to Serve Environmental Issues, Materials Science and its Applications for Sustainability, Engineering Design to Serve Sustainability Purposes, AI and IoT Applications in Environment and Sustainable Development, Biological and Environmental Sciences in Sustainable Development, Human Behaviour and Societal Influences on Environmental Sustainability. The conference was organized in hybrid modes of both physical and virtual via online, in a way that enabled a broad spectrum of participation from more than 8 countries and different regions of the Sultanate of Oman. 146 abstracts were submitted to the conference. 71 abstracts were accepted for oral presentation in addition to 25 accepted for poster presentation, cf. the figures below. Furthermore, the conference privileged to have informative five plenary lectures, and three invited Speeches in its programme, as detailed below. List of Figures, Conference Programme, Conference Committee and Sponsors are available in this Pdf.

Effect of alkyl chains on the structural and optical properties of nH6BiN orthoconic antiferroelectric liquid crystals: Insights from DFT calculations

This research presents a detailed computational study of a homologous series of orthoconic antiferroelectric liquid crystalline compounds, nH6BiN (where n = 1 to 6), employing Density Functional Theory (DFT) with the B3LYP functional and 6-311G(d,p) basis set. We optimized the molecular geometry and used it as an input file for analyzing thermodynamic properties, vibrational spectroscopy, and evaluating non-linear optical (NLO) properties to investigate the impact of terminal chain length on these compounds. The electronic structure analysis, including HOMO-LUMO gap and reactivity parameters, indicated consistent electronic properties across the series. Raman spectroscopy confirmed structural regularity, with characteristic vibrational modes. Notably, non-linear optical properties enhanced with chain length, as evidenced by increasing dipole moments, polarizabilities, and hyperpolarizabilities. The results highlight the influence of terminal chain length on the structural, electronic, and optical properties of the nH6BiN compounds, providing valuable insights for material design. This comprehensive study provides insights into the influence of terminal chain length on the molecular properties of the nH6BiN series, offering a foundation for their potential application in advanced material science.

Development of two step reverse transcription droplet digital PCR (RT-ddPCR) for simultaneous identification of saliva and semen

Determination of the type of body fluids is essential for crime scene reconstruction and for improving the reliability of expert testimonies. Messenger RNA (mRNA) analysis by reverse transcription quantitative PCR (RT-qPCR) has been used in forensic genetics, particularly for body fluid identification. It is a relative quantification method that compares the Ct values of target and reference gene. Thus, the method is unsuitable for determining exact copy numbers of the target gene. To address this limitation, this study performed body fluid-specific mRNA analysis using two-step reverse transcription droplet digital PCR (RT-ddPCR), which is capable of absolute quantification. We found that RT-ddPCR was accurate and sensitive enough to detect as little as 1.5 copies/μl of complementary DNA (cDNA), making it suitable for application using casework samples. It was also highly specific for body fluids, as non-specific amplification did not occur. In addition, saliva-semen mixtures with ratios ranging from 1:50 to 50:1 were successfully identified. When comparing the results of RT-qPCR and RT-ddPCR, some samples were difficult to interpret because of the high Ct values of RT-qPCR. However, when the same samples were analyzed using RT-ddPCR, saliva and semen were distinctly identified. Thus, RT-ddPCR is useful for mixed samples (e.g., in sexual assault cases) with low amounts of DNA, which often leads to ambiguous results when using RT-qPCR. Other body fluids (e.g., vaginal fluid and menstrual blood) can also be identified by including additional markers. This study demonstrates the potential of RT-ddPCR for applications in forensic science.

Deep learning based x-ray spectrometer for high repetition rate characterization of betatron radiation

Betatron radiation produced from a laser-wakefield accelerator is a broadband, hard x-ray (>1 keV) source that has been used in a variety of applications in medicine, engineering, and fundamental science. Further development and optimization of stable, high repetition rate (HRR) (>1 Hz) betatron sources will provide a means to extend their application base to include single-shot dynamical measurements of ultrafast processes or dense materials. Recent advances in laser technology used in such experiments have enabled increases in shot-rate and system stability, providing improved statistical analysis and detailed parameter scans. However, unique challenges exist at high repetition rate, where data throughput and source optimization are now limited by diagnostic acquisition rates and analysis. Here, we present the development of a machine-learning algorithm for the real-time analysis of betatron radiation. We report on the fielding of this deep learning algorithm for online source characterization at the Institut National de la Recherche Scientifique's Advanced Laser Light Source. By fine-tuning an algorithm originally trained on a fully synthetic dataset using a subset of experimental data, the algorithm can predict the betatron critical energy with a percent error of 7.2 % with a reconstruction time of 1.5 ms, providing a valuable tool for real-time, multi-objective optimization at HRR.

Modeling enzyme competition in eicosanoid metabolism in macrophage cells using a cybernetic framework

Cellular metabolism is a complex process involving the consumption and production of metabolites, as well as the regulation of enzyme synthesis and activity. Modeling of metabolic processes is important to understand the underlying mechanisms, with a wide range of applications in metabolic engineering and health sciences. Cybernetic modeling is a powerful technique that accounts for unknown intricate regulatory mechanisms in complex cellular processes. It models regulation as goal-oriented, where the levels and activities of enzymes are modulated by the cybernetic control variables to achieve the cybernetic objective. This study used cybernetic model to study the enzyme competition between arachidonic acid (AA) and eicosapentaenoic acid (EPA) metabolism in murine macrophages. AA and EPA compete for the shared enzyme cyclooxygenase. Upon external stimuli, AA produces proinflammatory 2-series prostaglandins and EPA metabolizes to antiinflammatory 3-series prostaglandins, where proinflammatory and antiinflammatory responses are necessary for homeostasis. The cybernetic model adequately captured the experimental data for control and EPA-supplemented conditions. The model is validated by performing an F-test, conducting leave-one-out-metabolite cross-validation, and predicting an unseen experimental condition. The cybernetic variables provide insights into the competition between AA and EPA for the cyclooxygenase enzyme. Predictions from our model suggest that the system undergoes a switch from a predominantly proinflammatory state in the control to an antiinflammatory state with EPA-supplementation. The model can also be used to analytically determine the AA and EPA concentrations required for the switch to occur. The quantitative outcomes enhance understanding of proinflammatory and antiinflammatory metabolism in RAW 264.7 macrophages.

Predicting solvation free energies for neutral molecules in any solvent with openCOSMO-RS

In this study, we introduce openCOSMO-RS 24a, an improved version of the open-source COSMO-RS model parameterized using quantum chemical calculations from ORCA 6.0, leveraging a comprehensive dataset that includes solvation free energies, partition coefficients, and infinite dilution activity coefficients for various solutes and solvents mainly at 25 °C. This is the first version of the model also capable of predicting solvation free energies based on ORCA calculations. Additionally, we develop a Quantitative Structure-Property Relationships model to predict molar volumes of the solvents, an essential requirement for predicting solvation free energies and partition coefficients from structure alone. Our results show that openCOSMO-RS 24a achieves an average absolute deviation of 0.45 kcal mol1 for solvation free energies, 0.76 for the logarithm of the partition coefficients, and 0.51 for the logarithm of infinite dilution activity coefficients, demonstrating improvements over the previous openCOSMO-RS 22 parameterization and comparable results to COSMOtherm 24 BP-TZVP. The user interface was extended to be able use it as solvation model directly from within ORCA 6.0 or from the command line to provide researchers with a robust tool for applications in chemical and materials science.

Synthesis of Graphene Oxide by Modified New Hummer Method

AbstractGraphene oxide (GO) has been synthesized by modified new Hummer's method with the help of Graphite flakes with sodium nitrite due to its various applications in physical, chemical, and medical sciences. The structure and morphology of GO are characterized using XRD, FTIR, RAMAN spectroscopy, and SEM. The results confirm that the synthesized material is graphene oxide (GO). The synthesized graphene oxide is used in perovskite solar cell as ETL layer.

Photocatalytic degradation of phenol and polycyclic aromatic hydrocarbons in water by novel acid soluble collagen-polyvinylpyrrolidone polymer embedded in Nitrogen-TiO2

Herein, we have synthesized acid-soluble collagen (ASC), polyvinylpyrrolidone (PVP), and nitrogen-doped titanium dioxide to form a novel hybrid photocatalyst nanocomposite (N-TiO2/ASC-PVP). The results of XRD, SEM and TEM revealed that the as-synthesized photocatalyst was composed of spheroidal particles, which were smaller than undoped TiO2.XPS analysis revealed that N was effectively incorporated into the lattice of TiO2 through substituting oxygen atoms, and N might coexist in the form of substitutional N (O–Ti–N) and interstitial N (TiON). The N-TiO2/ASC-PVP composite calcined at 200 and 400 °C exhibited high photocatalytic degradation rates for phenol, naphthalene (Nap), fluoranthene (Flu), phenanthrene (Phe), pyrene (Pyr), benz[a]anthracene (BaA), and anthracene (Ana), achieving a 98.6 % removal rate within 120 min at a dosage of 10 mg/L. The enhanced visible light photocatalytic activity was mainly attributed to the smaller crystal size, more surface hydroxyl groups, stronger light absorption in visible region and narrower band gap energy. This innovative hybrid photocatalyst holds immense potential for applications in materials science and nanotechnology, promising to revolutionize various industries.

The effect of ceramides on skin absorption by Raman spectroscopy.

Ceramides are essential epidermal constituents that play a critical role in skin moisturization treatment as a raw material in cosmetics formulation. Recently, ceramides have been known to be frequently applied in various cosmetic formulations. Despite ceramide's beneficial characteristics, academic research regarding ceramides and their skin absorption remains insufficient. Therefore, our study conducted clinical research employing Raman spectroscopy to investigate the effects of ceramides on skin absorption to enhance the understanding of ceramides' dermatological functionality and their topical application in cosmetics science. Twenty healthy individuals with dry skin have participated in this clinical trial. In this double-arm designed trial, the test group received an investigational product with ceramides (5000ppm) and a control group received an investigational product without the ceramides while all other components remained identical. The subjects visited the clinical research center and acclimatized for 30 min in constant humidity and temperature for equilibrium, subsequently conducting a measurement. Before the trial, the research subject's target site (lower arm area) was kept clean, devoid of any cosmetic administering 24h before the trial when investigational product was topically applied. Our findings with Raman spectroscopy statistically demonstrate that skin absorption amount, speed and depth for both groups improved overall (p<0.05) after administration of the investigational product. Notably, the test group received an investigational product with ceramides (5000ppm) indicating superior effectiveness across all parameters compared to a control group from comparison analysis of each parameter (p<0.05). This study concludes that ceramide-containing cosmetics provide a beneficial effect on skin absorption via visual and statistical results of Raman spectroscopy analysis.

BODIPY: synthesis, modification, and applications in sensing and biomedicine

BODIPY chromophores (4,4-difluoro-4-bora-3a,4a-diaza-s-indacene) are one of the most versatile fluorophores which are commonly used in a variety of scientific fields. The combination of excellent photophysical properties with the possibility of easy chemical modification of structure, chemical and photostability determines the application of BODIPY in biomedicine, photocatalysis, analytical chemistry and materials science. This review summarizes approaches to the synthesis and modification of BODIPY, discussing both classical and recently-published synthetic and postfunctionalization approaches. An influence of BODIPY structure and various postfunctionalization methods on photophysical properties of the fluorophores and their potential applications in biomedicine, materials science and biosensorics are also discussed.&lt;br&gt; The bibliography includes 344 references.

Enhancing testing efficacy of high-density SNP microarrays to distinguish pedigrees belonging to the same kinship class

Kinship testing, which involves genotyping genetic markers and comparing their profiles between individuals, holds significant applications in forensic science. However, the prevalent use of independent markers often lacks the discriminatory power to distinguish pedigrees belong to the same kinship class. While numerous studies have attempted to address this challenge through diverse approaches, the testing efficacy of high-density SNP microarrays in combination with the likelihood approach remains unclear.In this study, we further explored the utilization of linked autosomal SNPs derived from microarrays with the likelihood approach. Several SNP panels with differing numbers of loci were developed and putative pedigrees were constructed to evaluated to test their efficacy in distinguishing second-degree relationships, including grandparent-grandchild, half-siblings, and avuncular. Our findings indicate that the use of high-density SNP microarrays is theoretically feasible for discriminating second-degree relationships, with balanced classification rates ranging from 0.444 to 0.853.Moreover, to optimize the practical effectiveness of discriminating pedigrees belonging to the same kinship class, several other aspects such as adding additional SNPs or an additional relative and examining the effects of genotype errors and population selection were discussed. Our results revealed that the employment of denser marker sets with more accurate genotyping methods may be beneficial. Additionally, the inclusion of additional relatives and the selection of an appropriate reference population also appear to be crucial factors for enhancing the accuracy of kinship testing.In conclusion, our study provides insights into the potential of high-density SNPs in kinship testing and highlights the need for further optimization and examination into various factors that may contribute to enhancing testing efficacy.

A Survey On Image Registration Techniques Using FFT

Image Registration is the process of straightening two or more images of the same scene with testimonial to a particular image. The images are captured from various sensors at different times and at multiple viewpoints. Thus, to get a better picture of any change of a scene/object over a considerable period of time image registration is important. Image registration finds application in medical sciences, remote sensing and in computer vision. This paper presents a detailed review of several approaches which are classified accordingly along with their contributions and drawbacks. The main steps of an image registration procedure are also discussed. Different performance measures are presented that determine the registration quality and accuracy. The scope for the future research are presented as well. Applications based on Fast Fourier Transform (FFT) such as signal and image processing require high computational power, plus the ability to experiment with algorithms. Reconfigurable hardware devices in the form of Field Programmable Gate Arrays (FPGAs) have been proposed as a way of obtaining high performance at an economical price. At present, however, users must program FPGAs at a very low level and have a detailed knowledge of the architecture of the device being used. To try to reconcile the dual requirements of high performance and ease of development, this paper reports on the design and realization of a High-Level framework for the implementation of 1-D and 2-D FFTs for real-time applications. Results show that the parallel implementation of 2-D FFT achieves virtually linear speed-up and real-time performance for large matrix sizes. Finally, an FPGA-based parametrizable environment based on the developed parallel 2-D FFT architecture is presented as a solution for frequency domain image filtering application

Understanding healthcare professionals’ responses to patient complaints in secondary and tertiary care in the UK: A systematic review and behavioural analysis using the Theoretical Domains Framework

BackgroundThe path of a complaint and patient satisfaction with complaint resolution is often dependent on the responses of healthcare professionals (HCPs). It is therefore important to understand the influences shaping HCP behaviour. This systematic review aimed to (1) identify the key actors, behaviours and factors influencing HCPs’ responses to complaints, and (2) apply behavioural science frameworks to classify these influences and provide recommendations for more effective complaints handling behaviours.MethodsA systematic literature review of UK published and unpublished (so-called grey literature) studies was conducted (PROSPERO registration: CRD42022301980). Five electronic databases [Scopus, MEDLINE/Ovid, Embase, Cumulated Index to Nursing and Allied Health Literature (CINAHL) and Health Management Information Consortium (HMIC)] were searched up to September 2021. Eligibility criteria included studies reporting primary data, conducted in secondary and tertiary care, written in English and published between 2001 and 2021 (studies from primary care, mental health, forensic, paediatric or dental care services were excluded). Extracted data included study characteristics, participant quotations from qualitative studies, results from questionnaire and survey studies, case studies reported in commentaries and descriptions, and summaries of results from reports. Data were synthesized narratively using inductive thematic analysis, followed by deductive mapping to the Theoretical Domains Framework (TDF).ResultsIn all, 22 articles and three reports met the inclusion criteria. A total of 8 actors, 22 behaviours and 24 influences on behaviour were found. Key factors influencing effective handling of complaints included HCPs’ knowledge of procedures, communication skills and training, available time and resources, inherent contradictions within the role, role authority, HCPs’ beliefs about their ability to handle complaints, beliefs about the value of complaints, managerial and peer support and organizational culture and emotions. Themes mapped onto nine TDF domains: knowledge, skills, environmental context and resources, social/professional role and identity, social influences, beliefs about capability, intentions and beliefs about consequences and emotions. Recommendations were generated using the Behaviour Change Wheel approach.ConclusionsThrough the application of behavioural science, we identified a wide range of individual, social/organizational and environmental influences on complaints handling. Our behavioural analysis informed recommendations for future intervention strategies, with particular emphasis on reframing and building on the positive aspects of complaints as an underutilized source of feedback at an individual and organizational level.

Green nanotechnology for the enhancement of antibacterial properties in lining leather: MgO-chitosan nanocomposite coating

Antimicrobial nanomaterials have received a lot of interest in recent years due to their potential to fight against microbial degradation, a common problem in leather products. In this study, a nanocomposite was synthesized with MgO nanoparticles prepared by Aloe vera leaf extract and chitosan (CS), as an innovative solution to this problem. Three nanocomposite samples (C1, C2, and C3) were formulated with varying ratios of MgO and chitosan and evaluated for antimicrobial efficacy against Escherichia coli and Bacillus subtilis. Leather treated with MgO/Chitosan nanocomposite (MgO/Chitosan-1:1) exhibited substantial inhibition zones of 13 mm and 12 mm against E. coli and B. subtilis, respectively. Characterization of MgO nanoparticles, chitosan, and MgO/CS nanocomposite was performed through FTIR, XRD, SEM, TGA, and cytotoxicity tests. The average particle size and crystallite size of MgO nanoparticles were found as 136 nm and 10.3 nm, respectively and a weight loss of 67 % for MgO/CS nanocomposite in thermogravimetric analysis. FTIR confirmed the successful incorporation of MgO nanoparticles into the chitosan matrix, evidenced by the presence of characteristic functional groups. Application of nanocomposite onto lining leather via spraying resulted in finished leather with improved color rub fastness, perspiration fastness, and thermal stability compared to untreated leather. In comparison to dry color rub fastness, wet color rub fastness was notably improved by the MgO/CS nanocomposite, with gray scale ratings ranging from 4/5 to 5. Perspiration fastness was marginally enhanced by the MgO/CS coating, with gray scale ratings ranging from 4/5 to 5 for both grain and flesh samples. Specifically, the coated leather exhibited a water vapor permeability (WVP) of 9.94 mg cm−2.hr−1 that was lower than both uncoated (12.37 mg cm−2.hr−1) and PVA-coated (11.22 mg cm−2.hr−1) leather. This study presents a promising solution to the challenge of microbial degradation in leather products and highlights the potential of natural sources for synthesizing functional nanocomposites with diverse applications in materials science and biotechnology.

Model risk management in stress testing: The road up to here

This paper reviews the historical evolution of the quantitative models, model usage and model risk management (MRM) in large US banks since the 1980s. It comments on the most significant model-related events through this period. Some of these events were associated with contexts of great stress to the financial system. The paper identifies the main features of modelling in finance and economics that distinguish it from its application in the natural sciences. Then it presents the different types of models used in the large banks' stress testing programmes, the specific characteristics and risks of each type of model and the best practices for the implementation of sound model risk management, and it suggests a proper way to interpret the results of stress testing and capital assessment in the presence of model risks. The paper discusses the future evolution of MRM towards the implementation of a `fully fledged risk management framework` along the lines of other risk management disciplines, including risk identification, measurement, monitoring, reporting, limiting and capitalisation. It acknowledges the enhancements and opportunities offered by advances in the use of artificial intelligence and machine learning as well as increases in computational power. The paper concludes by noting that the model risk management framework that has been enforced by the Federal Reserve's stress testing and capital planning programmes has substantially strengthened the capital position, profitability and resilience of the large banks in the US.

Linear Algebra :Eigen Value and Eigen Vectors and Their Applications

Abstract: Linear algebra is the branch of mathematics that concerned with the study of vectors,vector spaces(linear spaces), linear maps(linear transformations') and system of linear equations. Linear space is the central theme in modern mathematics that is widely used in both abstract algebra and functional analysis.Linear algebra also has a concrete representation in analytical geometry and in generalized operator theory. It has extensive applications in natural sciences as well as social sciences. Here in this paper we are presenting a study on linear algebra and associated linear equations, also the eigen values and eigen vectors as a subtopic and few applications of it.the work basically focuses n eigen values and eigen vectors their useful properties including some applications of it.

Creation of Metal-Complex-Integrated Tensegrity Triangle DNA Crystals.

Structural DNA nanotechnology is an emerging field and is expected to be used for various applications in materials science. In this study, we designed a DNA tensegrity triangle to accommodate the bipyridine complexes with metal ions (Ni2+ and Fe2+) at the center of the space within the triangle. A metal-bipyridine-incorporated DNA tensegrity triangle was crystalized, and the presence of metals within it was confirmed through X-ray crystal structure analysis. A signal of the anomalous dispersion effect derived from metal was observed in the center of the DNA triangle.

A rapid compression large-volume press with a high pressure jump above 10GPa within milliseconds.

A high pressure jump through a rapid compression within milliseconds (ms) provides an important approach for searching novel matters and investigating their physical and chemical properties. Herein, we report a unique rapid-compression large volume press with a high pressure jump above 10GPa within 20ms by introducing a Walker-type module and hydraulic accumulators. The sample pressure can be rapidly increased from 1-5GPa to 12-16GPa by different modest compression rates varying from 10-2 to 633.5 GPa/s. The rapid pressure jump on the specimen has been successfully verified through the observed rapid phase transition of ZnTe from semiconductor to metal transitions, as evidenced by the variation in its electrical conductivity. The highest pressure jump of 10.2GPa within a rise time of 16.1ms is achieved, which is significantly higher than previous results (5.8GPa within 20ms) using a Bridgman-type anvils in such an apparatus. We found that rapid compression significantly enhances the phase transformation of C70 fullerene from a disordered graphite to an amorphous phase compared to static high-pressure experiments. The high pressure jump technique developed in this study will thus have great applications in materials science, physics, chemistry, and earth science.

Preface: 13th Ranshofener Leichtmetalltage

Abstract What strategies are available to minimize resource consumption in the light metal industry through recycling and energy efficiency? How can lightweight design make mobility more sustainable? And what role will artificial intelligence play in future processes in the metal processing industry? These and other questions are addressed at the 13th Ranshofener Leichtmetalltage 2024, which take place on the 26th–27th of September 2024 at the Hotel Gut Brandlhof in Saalfelden, Austria, and are organized in accordance with the criteria of the Austrian Ecolabel for Green Events. Under the guiding theme of “Light Metals Innovations for Environmental and Economic Sustainability”, this year’s conference offers an exciting program in three sessions “Digitalization in the Context of Circularity”, “Sustainable Process Development” and “Innovative Light Metals and their Characterization”. The focus is on decarbonization and digitalization in process and material development as well as the material characterization of light metals. A balanced spectrum of international presentations from universities, RTOs and industry provides participants with an up-to-date overview of the latest scientific findings and successful light metal applications. The 13th Ranshofener Leichtmetalltage 2024 are thus clearly focused on decarbonization and digitalization – even in times of diverse challenges. The first session, “Digitalization in the Context of Circularity”, highlights best-practice examples from the aluminium industry, the balance between sustainability and performance in metal processing and the implementation of complex geometries using wire-based additive manufacturing. The second session, “Sustainable Process Development”, is dedicated to the decarbonization and reduced material consumption of industrial processes, for example through GigaCasting, or the use of innovative recycling technologies. The third session, “Innovative Light Metals and their Characterization”, addresses forward-looking topics such as the development of special aluminium alloys for additive manufacturing, the use of old car scrap for innovative alloys and the decarbonization of the magnesium industry. The conference proceedings contain scientific contributions to the conference. We would like to thank all the authors for their high-quality work and the participants of the 13th Ranshofener Leichtmetalltage 2024 for their interest. We wish you stimulating reading and creative impulses! List of Scientific committee, Organizing committee are available in this Pdf.

Preparation of La-doped SrTiO3 ceramics with colossal permittivity and high insulation resistivity via controlling the particle diameters of the powders

Ceramic capacitors are widely studied and applied in the electronic industry. We utilized the sand-milling technique to produce a series of La-doped SrTiO3 powders with varying particle diameters and investigated the effect of particle size on the resulting dielectric properties for the first time. We found that reducing the particle diameter significantly enhances the permittivity from approximately 7000 to 32000 (at 1 kHz, room temperature). Furthermore, a colossal permittivity of ∼32000 (at 1 kHz, room temperature), combined with ultra-high resistivity (>7 × 1011 Ω cm), low loss (0.004), and excellent frequency/temperature stability, were simultaneously achieved in the ceramic. Lastly, the sintering temperature is as low as 1360 °C, making it suitable for industrial production. By analyzing scanning electron microscopy (SEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) results, we discuss the possible mechanism behind the enhancement of permittivity with increased sand-milling time. The low sintering temperature and highly controllable permittivity of the ceramics by adjusting the sand-milling time of the powders offer a new strategy for the scientific study and industrial application of materials with colossal permittivity.