Welcome!

Established in 2003, our science fair has been a cornerstone for young innovators, igniting a passion for science, technology, engineering, and math (STEM) in the next generation. Each year, hundreds of students from across the region dedicate countless hours to developing innovative projects. They are the future scientists, engineers, and problem-solvers who will shape our world.

Central Kentucky Regional Science and Engineering Fair

Saturday, March 7, 2026

@ Paul Laurence Dunbar High School

Awards

Fair Director: Elizabeth Pelphrey

Contact: ckyrsef@gmail.com

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2025 ISEF Finalists from CKRSEF

MATS054 - Machining Effects on Titanium Surface IntegrityUnderstanding the effects of machining processes and parameters on the surface integrity of materials is crucial to the manufacturing industry, as the ability to predict residual stress (RS) allows manufacturers to accurately choose cutting parameters that result in optimum RS. Parts with near-surface compressive RS and minimum near-surface tensile RS are more durable and therefore have longer lifespans, which can reduce costs and material waste. The goals of this study were to demonstrate the significant impact of using sharp vs. worn tools and to validate the combination of the hole-drilling method and Digital Image Correlation (DIC) as an efficient and accurate technique for studying RS.\n\nTo study the RS caused by sharp vs. worn tools, Ti-6Al4V was cut with a custom in-situ machine. The hole-drilling method and DIC were utilized to create strain fields, and a Matlab code was used to determine optimal virtual strain gauge orientations. RS vs. sub-surface depth values were then calculated using the software H-Drill. It was observed that the use of sharp tools resulted in desired near-surface compressive RS, while the use of worn tools resulted in undesirable near-surface tensile RS. The use of worn tools also resulted in a maximum stress depth that was roughly greater than twice that of samples cut with sharp tools.\n\nOverall, the use of worn tools is shown to have detrimental effects on the surface integrity of machined parts, and the hole-drilling method combined with DIC analysis is an efficient and accurate method for studying RS thus far.

MATS014 - Doping in Organic Electrochemical TransistorsOrganic electrochemical transistors (OECTs) are among the most powerful transistors to date by combining both ionic and electronic conduction. This unique mechanism makes these devices desirable for implantable bioelectronics in the human body, particularly as biosensors, deep brain stimulators, pacemakers, and artificial muscles, reducing reliance on invasive medical procedures. However, electron-conducting (n-type) OECTs, suitable for bioelectronic applications, historically suffer from instability and low performance, limiting their practical application. Chemical doping was investigated as a novel and cost-effective method to enhance device performance, successfully identifying a new dopant and unique doping techniques. Various organic salts were explored as potential dopants because of their strong Lewis base makeup. Current-voltage tests and electrochemical impedance spectroscopy characterized and compared undoped and salt-doped n-type OECT performance. Doping with tetrabutylammonium chloride (Bu4NCl) salt improves the device’s transconductance, mobility, signal-to-noise ratio, threshold signal, and capacitance. The Bu4NCl dopant’s statistically significant improvements in metrics yield a 97% improvement in amplification and a 77% improvement in switching speed and charge storage. Doping with Bu4NCl is optimized at a concentration of 20 molar percentage and a solvent blend of chlorobenzene to chloroform at a 1:5 ratio, enabling the salt to promote charge transfer and delocalization in the polymer network. Bu4NCl is identified as a new dopant to fabricate n-type OECTs with high performance. This study is the first to explore dopants, doping concentration, and solvent design in conjunction, advancing chemical doping in tailoring OECTs to become commercially viable.

ROBO019 - Improving Generalizability in Continual LearningWhile pre-training with supervised or self-supervised learning has recently shown great promise in continual learning (CL) by learning generalizable features, it requires a large, external dataset, similar to the target dataset. These types of datasets are available for popular benchmarking datasets but are often not available in real-world applications. As a result, many works still train randomly initialized models from scratch. However, no such works have investigated alternative measures to introduce generalizable features. Thus, self-supervised label augmentation (SSLA) is revisited in this work in a subset of CL, exemplar-free class-incremental learning (EFCIL). While SSLA has been previously proposed, it was utilized in an extremely naive manner, which is found to be harmful to performance with modern EFCIL algorithms. Due to this, two modifications based in theoretical observations are proposed to better fit SSLA to the EFCIL context: performing SSLA on only the initial task and performing knowledge distillation on only non-augmented class logits. Furthermore, SSLA is limited due to its reliance on either rotation or color-variant features, which may not be present in all datasets. Therefore, a novel augmentation for SSLA using binary low-pass and high-pass filters on the frequency domain of images is proposed for such settings. The proposed methods are evaluated on CIFAR-100, Tiny-ImageNet, and Skin23 and achieved significant gains in last task accuracy over the state-of-the-art with +2.5%. +2.7%, and over the baseline with +0.4% respectively.

TMED068 - Overcoming Docetaxel Resistance in Prostate CancerAcquired drug resistance is one of the biggest obstacles in cancer treatment, leading to increased chances of cancer relapses and progression. To combat drug resistances and to improve treatment outcomes, combination treatments, where multiple therapeutic agents are given simultaneously, are widely utilized in current cancer treatment protocols. In this study, the novel drug Obatoclax, a BCL-2 (B-Cell Lymphoma 2 Protein) inhibitor, was used in combination with 25 nM Docetaxel to evaluate their effects on prostate cancer apoptosis pathways. First, an Obatoclax treatment concentration of 4 nM was determined using Cell Viability Assays on PC3 Taxol-Resistant (TR) and DU145 TR prostate cancer cells. Then, Western Blots and Colony Formation Assays were performed with a combination of Obatoclax (4nM) and Docetaxel (25nM) to measure apoptosis and the molecular effects of the treatment. Results indicated that there was a very significant reduction of cancer cell colonies, a large reduction of PARP (Poly ADP-Ribose Polymerase) concentration, and a large increase of C-PARP (Cleaved - PARP) concentration. The results suggested that the treatment caused a strong apoptotic effect within TR prostate cancer cells, and may significantly improve chemotherapeutic efficiency and patient prognosis. Ongoing research includes using Western Blots to evaluate other indicators of apoptosis, such as BCL-2, BAX (BCL-2 Associated X), and BCL-2 XL (BCL-2 Extra Large) proteins.\n

CBIO015 - Novel Genes in Alzheimer’s, LATE, & Co-OccurrenceThis project investigates the genetic mechanisms underlying Alzheimer's Disease (AD) and Limbic-Predominant Age-Related TDP-43 Encephalopathy (LATE) and their co-occurrence by analyzing differential gene expression in specific cell types within the Dorsolateral Prefrontal Cortex (DLPFC) using the SEA-AD (Seattle Alzheimer's Disease) Single-Cell RNA(scRNAseq) sequencing dataset. The study is divided into three key steps: (1) sorting subjects into four groups based on their disease status—control, LATE-NC, ADNC, and mixed AD-LATE, (2) performing statistical analysis using multinomial logistic regression to evaluate demographic and genetic factors such as age, sex, education, cognitive scores, and APOE4 genotype, and (3) analyzing gene expression profiles of microglial and astrocyte cells to identify genes that are significantly upregulated or downregulated in relation to the different disease groups. This research provides the first comprehensive single-cell RNA sequencing analysis of LATE and mixed AD-LATE pathology, uncovering novel genetic signatures. UBE2B and SYT1 were upregulated in AD, implicating synaptic and proteasomal dysfunction. Most notably, the upregulation of ARL17B in LATE suggests a previously unidentified mechanism where impaired protein trafficking may exacerbate TDP-43 accumulation—a hallmark of LATE pathology. Additionally, ABCC1 upregulation in the mixed pathology group may indicate a compensatory mechanism mitigating AD pathology. Furthermore, the downregulation of mitochondrial genes such as MT-ATP8 and MT-ND2 in LATE and mixed groups indicates disrupted energy metabolism, a key contributor to neurodegenerative progression. This novel research establishes new biomarkers and therapeutic targets for these understudied neurodegenerative diseases