arXiv subjects

Benjamin O. Tayo

Publications and source records attributed to Benjamin O. Tayo.

9 recordsLinked to original sources

arXiv2026

Machine Learning Framework for Magnetic Candidate Discovery in Cerium-Based Compounds

Cerium (Ce), the most abundant lanthanide, offers significant potential for addressing shortages in high-performance magnetic materials, particularly through the discovery of compounds suitable for gap magnets. However, predicting Ce-based ferromagnets with uniaxial magnetic anisotropy remains challenging because their magnetic behavior depends strongly on crystal structure, exchange geometry, and electronic interactions. Here, we present a physics-guided computational framework to screen known Ce-based crystal structures and identify promising Ising ferromagnets for future synthesis. A Random Forest classifier uses seven structural and SOAP descriptors, including unit-cell volume, density, atomic sites, space group, atomic density, Ce SOAP overlap, and transition-metal SOAP overlap, to prioritize candidate compounds. Selected crystallographic structures are then analyzed using Ising-model Monte Carlo simulations to characterize phase behavior and critical properties. Critical exponents extracted from simulated phase transitions provide quantitative insight into magnetic regimes and anisotropy-related effects. We further employ autoencoders trained on affinity-based features from simulated spin configurations to identify latent signatures of phase evolution and transition behavior. Together, this framework integrates structural screening, statistical-mechanical simulation, and machine learning to accelerate the identification of promising Ce-based magnetic materials and provide candidates for experimental synthesis and validation.

cond-mat.mtrl-sci↗

arXiv2022

DNA Base Detection Using Two-Dimensional Materials Beyond Graphene

The success of graphene for nanopore DNA sequencing has shown that it is possible to explore other potential single- and few-atom thick layers of 2D materials beyond graphene, and also that these materials can exhibit fascinating and technologically useful properties for DNA base detection that are superior to those of graphene. In this article, we review the state-of-the art of DNA base detection using 2D materials beyond graphene. Initially, we present an overview of nanopore-based DNA sequencing methods using biological and solid-state nanopores, and discuss several challenges that limit their use for single-base resolution. Then we outline the progress, challenges, and opportunities using graphene. Additionally, we discuss several potential 2D materials beyond graphene such as hexagonal boron nitride, elemental 2D materials beyond graphene, and 2D transition metal dichalcogenides. Finally, we highlight the potential of using van der Waals materials for advanced DNA base detection technologies.

cond-mat.mes-hall↗

arXiv2022

Evaluation of the Feasibility of Phosphorene for Electronic DNA Sequencing Using Density Functional Theory Calculations

Electronic DNA sequencing using two-dimensional (2D) materials such as graphene has recently emerged as the next-generation of DNA sequencing technology. Owing to its commercial availability and remarkable physical and conductive properties, graphene has been widely investigated for DNA sequencing by several theoretical and experimental groups. Despite this progress, sequencing using graphene remains a major challenge. This is due to the hydrophobic nature of graphene, which causes DNA bases to stick to its surface via strong π-π interactions, reducing translocation speed and increasing error rates. To circumvent this challenge, the scientific community has turned its attention to other 2D materials beyond graphene. One such material is phosphorene. In this article, we performed first-principle computational studies using density functional theory (DFT) to evaluate the ability of phosphorene to distinguish individual DNA bases using two detection principles, namely, nanopore and nanoribbon modalities. We observe that binding energies of DNA bases are lower in phosphorene compared to graphene. The energy gap modulations due to interaction with DNA bases are very significant in phosphorene compared to graphene. Our studies show that phosphorene is superior to graphene, and hence a promising alternative for electronic DNA sequencing.

cond-mat.mes-hall↗

arXiv2021

Identification of DNA Bases Using Nanopores Created in Finite-Size Nanoribbons from Graphene, Phosphorene, and Silicene

The success of graphene for nanopore DNA sequencing has shown that it is possible to explore other potential single-atom and few-atom thick layers of elemental 2D materials beyond graphene (e.g., phosphorene and silicene). Using density functional theory, we studied the interaction of DNA bases with nanopores created in finite-size nanoribbons from graphene, phosphorene, and silicene. We observe that binding energies of DNA bases using nanopores from phosphorene and silicene are generally smaller compared to graphene. The band gaps of phosphorene and silicene are significantly altered due to interaction with DNA bases compared to graphene. Our findings show that phosphorene and silicene are promising alternatives to graphene for DNA base detection using advanced detection principles such as transverse tunneling current measurement.

cond-mat.mes-hall↗

arXiv2021

Physisorption of DNA bases on finite-size nanoribbons from graphene, phosphorene, and silicene: Insights from density functional theory

The ability to detect and discriminate DNA bases by reading it directly using simple and cost-effective methods is an important problem whose solution can produce significant value for areas such as cancer and human genetic disorders. Two-dimensional (2D) materials have emerged as revolutionary materials for electronic DNA sequencing with strong potentials for fast, single-nucleotide direct-read DNA sequencing with a minimum amount of consumables. Among 2D materials, graphene is the most explored for DNA sequencing. This is due to its commercial availability. The major hindrance of graphene is its hydrophobicity, which causes DNA bases to stick to its surface, slowing down translocation speed, and making single-base discrimination difficult as multiple bases interact with graphene at any given time. It is therefore essential that other elemental 2D materials beyond graphene be investigated. Using density functional theory (DFT), we studied the electronic interaction of DNA bases physisorped onto the surface of nanoribbons from graphene, phosphorene, and silicene. By comparing the change in energy band gap, binding energy and density of states (DOS), we observe that phosphorene performs better than graphene and silicene for DNA sequencing using the physisorption modality.

cond-mat.mes-hall↗

arXiv2018

Efficient design of a one-hour unit test for introductory physics

Designing a one-hour unit test for an introductory physics class can be quite challenging. We present an efficient format of a one-hour unit test that utilizes question groups for quantitative free-response problems and a binary system (True or False) for conceptual questions. This format promotes coherence and allows the instructor to test a wide variety of topics in a one-hour exam. For the 4 semesters in which the design has been implemented, average unit test scores have increased from 76% using traditional test format, to 79% using the efficient design.

physics.ed-ph↗

arXiv2018

Grade inflation in introductory physics: the influence of out-of-class assignments

We report the results of statistical analysis performed on course grades for calculus-based introductory physics for data collected over a four-year period. We consider two important categories of scores: proctored (in-class proctored exams only) and proctored plus out-of-class (in-class proctored exams plus out-of-class assignments). The analysis revealed significant grade inflation in the proctored plus out-of-class scores. Quantile plots were used to compare the observed data and data modeled using the normal distribution. These plots revealed negligible correlation between the observed and modeled data for the proctored plus out-of-class scores, while a strong correlation is observed for the proctored scores. Using the proctored grade distribution as a reference, we performed goodness-of-fit tests using the Bayesian probability fit and the original reference proportions. Using the expected counts from the two different methods, we found p-values of 0.023 and 0.008. Both p-values support the hypothesis that there is significant difference in proctored plus out-of-class grade distribution compared to the reference. Further analysis showed that approximately 25% of all grades are shifted towards higher grades. Our studies clearly show that grade inflation induced by out-of-class assignments is a crucial issue in assessment that has to be addressed. By comparing the degree of inflation in our grade distribution with the national average, we found it to be about 50% less severe.

physics.ed-ph↗

arXiv2015

Band gap engineering in finite elongated graphene nanoribbon heterojunctions: Tight-binding model

A simple model based on the divide and conquer rule and tight-binding (TB) approximation is employed for studying the role of finite size effect on the electronic properties of elongated graphene nanoribbon (GNR) heterojunctions. In our model, the GNR heterojunction is divided into three parts: a left (L) part, middle (M) part, and right (R) part. The left part is a GNR of width $W_{L}$, the middle part is a GNR of width $W_{M}$, and the right part is a GNR of width $W_{R}$. We assume that the left and right parts of the GNR heterojunction interact with the middle part only. Under this approximation, the Hamiltonian of the system can be expressed as a block tridiagonal matrix. The matrix elements of the tridiagonal matrix are computed using real space nearest neighbor orthogonal TB approximation. The electronic structure of the GNR heterojunction is analyzed by computing the density of states. We demonstrate that for heterojunctions for which $W_{L} = W_{R}$, the band gap of the system can be tuned continuously by varying the length of the middle part, thus providing a new approach to band gap engineering in GNRs. Our TB results were compared with calculations employing divide and conquer rule in combination with density functional theory (DFT) and were found to agree nicely.

cond-mat.mes-hall↗

arXiv2014

Effective mass versus band gap in graphene nanoribbons: influence of H-passivation and uniaxial strain

A simple model which combines tight-binding (TB) approximation with parameters derived from first principle calculations is developed for studying the influence of edge passivation and uniaxial strain on electron effective mass of armchair graphene nanoribbons (AGNRs). We show that these effects can be described within the same model Hamiltonian by simply modifying the model parameters i.e., the hopping integrals and onsite energies. Our model reveals a linear dependence of effective mass on band gap for H-passivated AGNRs for small band gaps. For large band gap, the effective mass dependence on band gap is parabolic and analytic fits were derived for AGNRs belonging to different families. Both band gap and effective mass exhibit a nearly periodic zigzag variation under strain, indicating that the effective mass remains proportional to the band gap even when strain is applied. Our calculations could be used for studying carrier mobility in intrinsic AGNRs semiconductors where carrier scattering by phonons is the dominant scattering mechanism.

cond-mat.mes-hall↗