Physical Sciences and Mathematics Commons^™

การสังเคราะห์และการอบฟิล์มบาง Vo2 ที่ปลูกด้วยกระบวนการโซลเจลเพื่อนำไปใช้เป็นกระจกกันความร้อนอัจฉริยะ, พงศธรณ พันธ์บูรณะ

Chulalongkorn University Theses and Dissertations (Chula ETD)

ผู้ทดลองทำการทดลองเพื่อหาเงื่อนไขที่เหมาะสมสำหรับการปลูกฟิล์มบาง VO2 (M) ที่มีสมบัติ Semiconductor Metal transition (SMT) ซึ่งสามารถนำไปใช้ในการทดลองและใช้เป็นอุปกรณ์ต่างๆ เช่นกระจกกันความร้อนอัจฉริยะ (Smart Window) ผู้ทดลองปลูกฟิล์มบาง VO2 (M) ด้วยกระบวนการโซลเจลซึ่งเป็นวิธีที่มีความซับซ้อนไม่มากและค่าใช้จ่ายต่ำกว่าวิธีอื่น การทดลองนี้ศึกษาผลของตัวแปรทั้ง 5 ต่อการอบฟิล์มบาง VO2 ซึ่งตัวแปรทั้ง 5 ประกอบด้วย อุณหภูมิ เวลา บรรยากาศในขณะอบฟิล์ม ซับสเตรตและสารตั้งต้นที่ใช้ในการอบฟิล์ม ผู้ทดลองปลูกฟิล์มภายใต้อุณหภูมิต่างๆ (300, 400 และ 500 °C) และอบฟิล์มด้วยเวลาที่ต่างกัน (30, 60, 90 และ 120 นาที) ภายใต้บรรยากาศปกติและบรรยากาศที่มีออกซิเจนน้อย (ไนโตรเจนหรืออาร์กอน) การทดลองนี้ใช้ซับสเตรตสองชนิด (SiO2 และ Al2O3) และใช้สารตั้งต้นสองชนิด สารตั้งต้นชนิดแรกคือ VO(OC3H7)3 ที่มีอัตราส่วน V:O 1:4 และ เริ่มต้นด้วย V5+ สารตั้งต้นชนิดที่สองคือ VO(acac)2 ที่มีอัตราส่วน V:O 1:5 และ เริ่มต้นด้วย V4+ จากนั้นผู้ทดลองได้ตรวจสอบสมบัติและชนิดของฟิล์มด้วยการวัดความต้านทานที่อุณหภูมิต่างๆ ก่อนและหลังอบฟิล์ม ตรวจสอบโครงสร้างของฟิล์มโดยรามานสเปกโตรมิเตอร์และการวิเคราะห์การเลี้ยวเบนของรังสีเอกซ์ การทดลองให้ผลว่าอุณหภูมิที่สูงกว่าและเวลาที่นานกว่าในการอบทำให้ฟิล์มที่ได้มีสมบัติเข้าใกล้ VO2 (M) มากกว่าการใช้อุณหภูมิและเวลาในการอบที่น้อยกว่า นอกจากนั้นผู้ทดลองยังพบว่าเงื่อนไขที่เหมาะสมสำหรับการปลูกฟิล์มคือ การใช้ Al2O3 เป็นซับสเตรตโดยมี VO(OC3H7)3 เป็นสารตั้งต้นและทำการอบในบรรยากาศที่มีออกซิเจน น้อย ในการทดลองสุดท้ายผู้ทดลองปลูกฟิล์มบน Al2O3 โดยใช้ VO(OC3H7)3 เป็นสารตั้งต้นแล้วทำการอบที่อุณหภูมิ 500 °C นาน 120 นาที ภายใต้บรรยากาศที่มีออกซิเจนเป็นส่วนประกอบน้อย (อาร์กอน) ผลการวิเคราะห์การเลี้ยวเบนของรังสีเอกซ์และการใช้รามานสเปกโตรมิเตอร์ยืนยันว่าฟิล์มที่ได้เป็น VO2 (M) ที่ปนด้วย V6O13 ซึ่งมีสมบัติ SMT ที่ 79 °C และสามารถกั้นรังสีอินฟราเรดที่อุณหภูมิสูงได้เล็กน้อย …

Stability Of A Discrete-Time Infected-Aged Epidemic Model, Patchara Ploypetch

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, we consider a discrete-time infected-aged SIS epidemic model. The model is obtained from a continuous-time SIS epidemic model by applying Micken’s nonstandard finite difference method. We derive some basic properties of solutions including the boundedness and positivity of solutions. Furthermore, we obtain two parameters R0 and R∞ so that if R0 < 1 then the infection becomes extinct whereas if R∞ > 1 the the infection becomes permanent.

Developing Test Statistics For Familial Dna Searches Through Classification Ideas, Chanagarn Laoiam

Chulalongkorn University Theses and Dissertations (Chula ETD)

In a familial DNA search, the test statistic used for concluding a relationship is the likelihood ratio. In the traditional way, it is assumed that all individuals have the same genetic background ; however, population substructure typically exists and allele frequencies differ among subpopulations. To address this issue, a number of modified likelihood ratio statistics have been proposed. One is to apply the likelihood ratio framework to the average available allele frequencies (LRLAF). Another well-known three statistics are taking the maximum, minimum and average of all available likelihood ratios (LRMAX, LRMIN or LRAVG, respectively). In this thesis, two new likelihood …

Classification Of Metal Hydride Superconductors Using Machine Learning, Vichayuth Imchitr

Chulalongkorn University Theses and Dissertations (Chula ETD)

Metal hydrides are currently the main approach in the quest for high-temperature superconductors, as they exhibit a wide range of superconducting critical temperatures (TC). The key ingredient for determining the superconducting critical temperature is the phonon in the material. However, calculating the phonon via the first-principle method requires high computational costs and is time-consuming. To expedite the search for new superconducting hydrides, machine learning has been applied to scan for potential high-TC materials before performing phonon calculations. However, this method has limitations due to the limited number of available training samples, and the selection of input features for the task …

Thermodynamic Stability Prediction Of Multi-Transition-Metal Mxenes, Chayanon Atthapak

Chulalongkorn University Theses and Dissertations (Chula ETD)

Over the past decade, the largest group of two-dimensional alloys like transition metal carbides/nitrides (MXenes), have attracted a lot of attention in the material science community due to their alloying behaviors and their wide range of applications. However, the phase stability of multi-transition-metal MXenes has so far barely been validated. For this reason, examinations of the stability of multi-transition-metal MXenes from the theoretical aspect are highly of importance for future experimental synthesis and characterization of the materials. In this work, the proponent aims at investigating the thermodynamic stability of (Mo-Ti-V)3C2 MXenes, by performing computational simulations based on density functional theory …

Thermal Conductivity Studies Of Nitrogen Subsituted Single-Layered Diamond Using Density Functional Theory Simulation, Sakarn Khamkaeo

Chulalongkorn University Theses and Dissertations (Chula ETD)

Recently, a promising two-dimensional material known as single-layered diamond or diamane has emerged, combining the interesting properties of bulk diamond with the exceptional thermal conductivity characteristic of two-dimensional materials. However, diamane’s stability requires high pressure unless its surfaces are passivated, for example, hydrogen or fluorine. Later, N-substituted diamane has been introduced as a solution, providing both stability and fascinating hardness properties. This thesis investigates the thermal properties of nitrogen-containing diamane using computational simulations with the density functional theory and the Boltzmann transport equation. The results show the out-of-plane vibration mode of N-substituted diamane, along with the calculated thermal conductivity with …

Synthesis And Biological Activities Of Acyl Derivatives Of Hydroxylated Eudesmanolides, Rawinnipha Wettayanugul

Chulalongkorn University Theses and Dissertations (Chula ETD)

This research focused on the synthesis of two hydroxylated eudesmanolides, reynosin (RNS, 2) and santamarine (STM, 3) from costunolide (1) isolated from Saussurea lappa roots, and the synthesis of their acyl derivatives to study on their biological activities. A total of 20 acyl derivatives of hydroxylated eudesmanolides, including 14 new compounds: 2(a-c), 3b, 3c, 3e, 3f, 3(h-j), and 3(l-o). The compounds were then evaluated for their anti-melanogenic, anti-colorectal cancer, and anti-inflammatory activities. It was observed that STM (3) exhibited anti-melanogenic and anti-colorectal cancer activity with IC50 values of 8.02 and 15.55 µM, respectively, which was greater than RNS (2) (IC50 …

Naturally Derived Polymeric Gel For Bio-Catalysis And Wound Dressing, Yuwaporn Pinyakit

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, two types of polymeric gels made from naturally derived polymers have been developed for bio-catalysis and wound dressing applications. In the first part, the heterogeneous biocatalyst with tunable geometry was fabricated using a 3D printing technique. The hydrogel-based ink as a supporting material for the immobilization of laccase was prepared from alginate (Alg) combined with Pluronic® F127-dimethacrylate (F127-DMA). Chemically crosslinked F127-DMA hydrogel with an optimized Alg composition exhibited good water swelling, mass transfer, and mechanical stability. To enhance the interaction between substrate and enzyme, the printed constructs with various surface-to-volume ratio (S/V) and geometrical designs (cubic, cylinder, …

Water Quality Prediction On Bang Pakong River Under Climate Change Using Data-Driven Models., Phuoc Thanh Ho

Chulalongkorn University Theses and Dissertations (Chula ETD)

The Bang Pakong River, Chachoengsao Province, Thailand, is one of the most important rivers in the eastern part of Thailand due to its primary role in water supplies. However, the deterioration in the quality of the BPKR is critical due to anthropogenic activities and climate change since the 2000s. Therefore, the study aimed to establish ARMAX and MLP-ANN models to forecast some water quality parameters in the near future and predict general water quality indexes of the river, supported by correlation analysis between water quality parameters with climate and land use. The analysis results revealed that when agricultural land decreased …

Phenotype-Genotype Analysis Of Caucasian Patients With High Risk Of Osteoarthritis, Yanfei Wang, Jacqueline Chyr, Pora Kim, Weiling Zhao, Xiaobo Zhou

Faculty, Staff and Student Publications

Background: Osteoarthritis (OA) is a common cause of disability and pain around the world. Epidemiologic studies of family history have revealed evidence of genetic influence on OA. Although many efforts have been devoted to exploring genetic biomarkers, the mechanism behind this complex disease remains unclear. The identified genetic risk variants only explain a small proportion of the disease phenotype. Traditional genome-wide association study (GWAS) focuses on radiographic evidence of OA and excludes sex chromosome information in the analysis. However, gender differences in OA are multifactorial, with a higher frequency in women, indicating that the chromosome X plays an essential role …

Automated Identification Of Missing Is-A Relations In The Human Phenotype Ontology, Maryamsadat Mohtashamian, Ran Hu, Rashmie Abeysinghe, Xubing Hao, Hua Xu, Licong Cui

Faculty, Staff and Student Publications

Auditing the Human Phenotype Ontology (HPO) is necessary to provide accurate terminology for its use in clinical research. We investigate an approach leveraging the lexical features of concepts in HPO to identify missing IS-A relations among HPO concepts. We first model the names of HPO concepts as sets of words in lower case. Then, we generate two types of concept-pairs which have at least a single common word: (1) Linked concept-pairs generated from concept-pairs having an IS-A relation; (2) Unlinked concept-pairs generated from concept-pairs without an IS- A relation. Concept-pairs generate Derived Term Pairs (DTPs) emphasizing unique lexical information of …

Cost Of Care For Asylum Seekers And Refugees Entering The United States: The Case Of Volunteer Medical Providers In El Paso, Texas, Rigoberto I Delgado, Manuel De La Rosa, Marlon A Picado, Lisa Ayoub-Rodriguez, Celia E Gonzalez, Leopold Gemoets

Faculty, Staff and Student Publications

BACKGROUND: Between October 2018, and February 2020, the United States saw an unprecedented increase in the number of asylum seekers and refugees arriving unexpectedly at international crossings along the US-Mexico Border. Many of these migrants needed proper medical attention, and consequently created significant pressure on local health systems. In El Paso, Texas, volunteer clinicians, collaborating closely with religious organizations and non-governmental organizations, provided outpatient medical care for the new arrivals; the county hospital provided in-patient care at local tax payers' expense. The objective of this study was to estimate costs of healthcare services offered by these volunteers in order to …

A Nomogram For Predicting Upper Urinary Tract Damage Risk In Children With Neurogenic Bladder, Qi Li, Miao Cai, Qingsong Pu, Shengde Wu, Xing Liu, Tao Lin, Dawei He, Jianguo Wen, Guanghui Wei

Faculty, Staff and Student Publications

PURPOSE: To establish a predictive model for upper urinary tract damage (UUTD) in children with neurogenic bladder (NB) and verify its efficacy.

METHODS: A retrospective study was conducted that consisted of a training cohort with 167 NB patients and a validation cohort with 100 NB children. The clinical data of the two groups were compared first, and then univariate and multivariate logistic regression analyses were performed on the training cohort to identify predictors and develop the nomogram. The accuracy and clinical usefulness of the nomogram were verified by receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses.

RESULTS: …

Racial And Socioeconomic Disparities In Patients With Meningioma: A Retrospective Cohort Study, Hudin N Jackson, Caroline C Hadley, A Basit Khan, Ron Gadot, James C Bayley, Arya Shetty, Jacob Mandel, Ali Jalali, K Kelly Gallagher, Alex D Sweeney, Arif O Harmanci, Akdes S Harmanci, Tiemo Klisch, Shankar P Gopinath, Ganesh Rao, Daniel Yoshor, Akash J Patel

Faculty, Staff and Student Publications

BACKGROUND: Meningiomas are the most common intracranial neoplasms. Although genomic analysis has helped elucidate differences in survival, there is evidence that racial disparities may influence outcomes. African Americans have a higher incidence of meningiomas and poorer survival outcomes. The etiology of these disparities remains unclear, but may include a combination of pathophysiology and other factors.

OBJECTIVE: To determine factors that contribute to different clinical outcomes in racial populations.

METHODS: We retrospectively reviewed 305 patients who underwent resection for meningiomas at a single tertiary care facility. We used descriptive statistics and univariate, multivariable, and Kaplan-Meier analyses to study clinical, radiographical, and …

Risk Of Alzheimer's Disease Following Influenza Vaccination: A Claims-Based Cohort Study Using Propensity Score Matching, Avram S Bukhbinder, Yaobin Ling, Omar Hasan, Xiaoqian Jiang, Yejin Kim, Kamal N Phelps, Rosemarie E Schmandt, Albert Amran, Ryan Coburn, Srivathsan Ramesh, Qian Xiao, Paul E Schulz

Faculty, Staff and Student Publications

BACKGROUND: Prior studies have found a reduced risk of dementia of any etiology following influenza vaccination in selected populations, including veterans and patients with serious chronic health conditions. However, the effect of influenza vaccination on Alzheimer's disease (AD) risk in a general cohort of older US adults has not been characterized.

OBJECTIVE: To compare the risk of incident AD between patients with and without prior influenza vaccination in a large US claims database.

METHODS: Deidentified claims data spanning September 1, 2009 through August 31, 2019 were used. Eligible patients were free of dementia during the 6-year look-back period and≥65 years …

Fairly Predicting Graft Failure In Liver Transplant For Organ Assigning, Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

Liver transplant is an essential therapy performed for severe liver diseases. The fact of scarce liver resources makes the organ assigning crucial. Model for End-stage Liver Disease (MELD) score is a widely adopted criterion when making organ distribution decisions. However, it ignores post-transplant outcomes and organ/donor features. These limitations motivate the emergence of machine learning (ML) models. Unfortunately, ML models could be unfair and trigger bias against certain groups of people. To tackle this problem, this work proposes a fair machine learning framework targeting graft failure prediction in liver transplant. Specifically, knowledge distillation is employed to handle dense and sparse …

Facilitating Federated Genomic Data Analysis By Identifying Record Correlations While Ensuring Privacy, Leonard Dervishi, Xinyue Wang, Wentao Li, Anisa Halimi, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

Faculty, Staff and Student Publications

With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and the data is still siloed across different repositories. Analyzing all of this data would be transformative for genomics research. However, the data is sensitive, and therefore cannot be easily centralized. Furthermore, there may be correlations in the data, which if not detected, can impact the analysis. In this paper, we take the first step towards identifying correlated records across multiple data repositories in a privacy-preserving manner. The proposed framework, based on random shuffling, synthetic record …

Caries Risk Documentation And Prevention: Emeasures For Dental Electronic Health Records, Suhasini Bangar, Ana Neumann, Joel M White, Alfa Yansane, Todd R Johnson, Gregory W Olson, Shwetha V Kumar, Krishna K Kookal, Aram Kim, Enihomo Obadan-Udoh, Elizabeth Mertz, Kristen Simmons, Joanna Mullins, Ryan Brandon, Muhammad F Walji, Elsbeth Kalenderian

Faculty, Staff and Student Publications

BACKGROUND: Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures).

OBJECTIVE: We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year.

METHODS: Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For …

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, And Beyond, Robert El-Kareh, Dean F Sittig

Faculty, Staff and Student Publications

Patient care in intensive care environments is complex, time-sensitive, and data-rich, factors that make these settings particularly well-suited to clinical decision support (CDS). A wide range of CDS interventions have been used in intensive care unit environments. The field needs well-designed studies to identify the most effective CDS approaches. Evolving artificial intelligence and machine learning models may reduce information-overload and enable teams to take better advantage of the large volume of patient data available to them. It is vital to effectively integrate new CDS into clinical workflows and to align closely with the cognitive processes of frontline clinicians.

Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue

Civil & Environmental Engineering Faculty Publications

Meteotsunamis pose a unique threat to coastal communities and often lead to damage of coastal infrastructure, deluge of nearby property, and loss of life and injury. The Great Lakes are a known hot-spot of meteotsunami activity and serve as an important region for investigation of essential hydrodynamic processes and model forecast requirements in meteotsunami-induced coastal flooding. For this work, we developed an advanced hydrodynamic model and evaluate key model attributes and dynamic processes, including: (1) coastal model grid resolution and wetting and drying process in low-lying zones, (2) coastal infrastructure, including breakwaters and associated submerging and overtopping processes, (3) annual/seasonal …

Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang

Civil & Environmental Engineering Faculty Publications

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …

Editorial: Coastal Flooding: Modeling, Monitoring, And Protection Systems, Valentina Prigiobbe, Clint Dawson, Yao Hu, Hatim O. Sharif, Navid Tahvildari

Civil & Environmental Engineering Faculty Publications

Coastal flooding has received significant attention in recent years due to future sea-level rise (SLR) projections and intensification of precipitation, which will exacerbate frequent flooding, coastal erosion, and eventually create permanently inundated low-elevation land. Coastal governments will be forced to implement measures to manage risk on the population and infrastructure and build protection systems to mitigate or adapt to the negative impacts of flooding. Research in this area is required to establish holistic frameworks for timely and accurate flooding forecast and design of protection systems.

Recent Advancements In Electrochemical Conversion Of Carbon Dioxide, Nandan Nag, Amit Kumar, Sumit Sharma, Sandeep Kumar, Amit K. Thakur

Civil & Environmental Engineering Faculty Publications

Electrochemical reduction of carbon dioxide into eco-friendly and clean products is a promising approach to eradicate pollution. Although carbon dioxide emission is inhibited by the advent of renewable sources of energy, it is present in the atmosphere and needs to be cleaned. The reduction of carbon dioxide from atmospheric gases can be accomplished by its adsorption and subsequent transportation to electrolytic chambers, where it is reduced to hydrocarbons, organic acids or carbonates. This review focuses on developing a three compartment electrochemical cell to reduce carbon dioxide used as a catholyte. Various factors affecting the electrochemical reduction of carbon dioxide and …

Distributed Partial Differential Equation Solving With Julia Fast Fourier Transform Library, Christopher E. Mottola

Honors Theses and Capstones

Scientific computing relies on advanced computational and mathematical techniques to solve complex problems in scientific domains. For the numerical rendering of spectral, nonlinear, and dynamic phenomena, there is a growing need for greater availability of a broad class of Fourier-based algorithms to perform large scale operations on multidimensional data in distributed and optimized ways. To this effect, the Julia programming language is new and has significant advantages compared to other common languages used in scientific computing. The research presented here formulates a basis for further development in high-performance scientific computing of periodic partial differential equations through the application of distributed …

Investigating Signs Of Orbital Decay In The Tres-1 Exoplanetary System, Amanda F. Wester

Honors Theses and Capstones

Transit observations of exoplanetary systems can be used to investigate orbital decay. TrES-1b is an exoplanet hypothesized to be experiencing orbital decay due to observed transit timing variations (TTVs) [12]. Numerous transits must be observed to establish a long term pattern to conclusively determine if the planet’s orbit is decaying. Measurements were made using the UNH Observatory where 2 transits were observed of the TrES-1b transiting system on February 27, 2022 and March 5, 2022. A CCD camera was used to image the transit and capture calibration images. The software AstroImageJ (AIJ) was used to calibrate the images and perform …

Perspectives On Determinism In Quantum Mechanics: Born, Bohm, And The 'Quantal Newtonian' Laws, Viraht Sahni

Publications and Research

Quantum mechanics has a deterministic Schrödinger equation for the wave function. The Göttingen-Copenhagen statistical interpretation is based on the Born Rule that interprets the wave function as a ‘probability amplitude’. A precept of this interpretation is the lack of determinism in quantum mechanics. The Bohm interpretation is that the wave function is a source of a field experienced by the electrons, thereby attributing determinism to quantum theory. In this paper we present a new perspective on such determinism. The ideas are based on the equations of motion or ‘Quantal Newtonian’ Laws obeyed by each electron. These Laws, derived from the …

A Framework For Near-Real Time Monitoring Of Diversity Patterns Based On Indirect Remote Sensing, With An Application In The Brazilian Atlantic Rainforest, Andrea Paz, Thiago S. Silva, Ana C. Carnaval

Publications and Research

Monitoring biodiversity change is key to effective conservation policy. While it is difficult to establish in situ biodiversity monitoring programs at broad geographical scales, remote sensing advances allow for near-real time Earth observations that may help with this goal. We combine periodical and freely available remote sensing information describing temperature and precipitation with curated biological information from several groups of animals and plants in the Brazilian Atlantic rainforest to design an indirect remote sensing framework that monitors potential loss and gain of biodiversity in near-real time. Using data from biological collections and information from repeated field inventories, we demonstrate that …

Magnetoexcitons In Phosphorene Monolayers, Bilayers, And Van Der Waals Heterostructures, Roman Ya. Kezerashvili, Anastasia Spiridonova, Andrew Dublin

Publications and Research

We study direct and indirect excitons in Rydberg states in phosphorene monolayers, bilayers, and van der Waals (vdW) heterostructure in an external magnetic field within the framework of the effective-mass approximation. The magnetic field is applied perpendicular to the monolayer or heterostructure and is varied between 0 and 60 T. Binding energies of magnetoexcitons are calculated by numerical integration of the Schrödinger equation using the Rytova-Keldysh potential for direct magnetoexcitons and both the Rytova-Keldysh and Coulomb potentials for indirect magnetoexcitons. The latter aids in the understanding of the role of screening in phosphorene. We report the magnetic field energy contribution …

Fano 3-Folds, Reflexive Polytopes And Brane Brick Models, Sebastían Franco, Rak-Kyeong Seong

Publications and Research

Reflexive polytopes in n dimensions have attracted much attention both in mathematics and theoretical physics due to their connection to Fano n-folds and mirror symmetry. This work focuses on the 18 regular reflexive polytopes corresponding to smooth Fano 3-folds. For the first time, we show that all 18 regular reflexive polytopes have corresponding 2d (0, 2) gauge theories realized by brane brick models. These 2d gauge theories can be considered as the worldvolume theories of D1-branes probing the toric Calabi-Yau 4-singularities whose toric diagrams are given by the associated regular reflexive polytopes. The generators of the mesonic moduli …

Characterizing Changes In Extreme Ozone Levels Under 2050s Climate Conditions: An Extreme-Value Analysis In California, Bradley Wilson, Mariah Pope, Jeremy R. Porter, Edward Kearns, Evelyn Shu, Mark Bauer, Neil Freeman, Mike Amodeo, David Melecio-Vazquez, Ho Hsieh, Maggie Tarasovitch

Publications and Research

Ground-level ozone has a well established climate penalty associated with changing meteorological conditions under future climate change, but most existing research focuses exclusively on ozone-temperature relationships defined at specific locations. Using an extreme-value theory approach, we model relationships between temperature, humidity, and vapor pressure deficit and maximum daily 8 h ozone concentrations (MDA8) across California using a combination of ozone station network data and Community Multiscale Air Quality Modeling System (CMAQ) model output from 2008 to 2017. We use a spatial regression with time varying bias coefficients to fuse station observations and modeled output into a spatially explicit gridded ozone …