Events
Department of Mathematics and Statistics
Texas Tech University
 | Wednesday
Oct. 15
|
| Algebra and Number Theory
No Seminar
|
Abstract. This research focuses on the interface reactions in composite energetic materials involving TiO2 polymorphs and γ-Al2O3 surface, investigated through experimental and theoretical approaches. Using density functional theory (DFT), we examined the adsorption and decomposition of ammonium perchlorate (NH4ClO4) on rutile (110, 100, 001) and anatase (101, 001) TiO2 surfaces, revealing highly stable complexes stabilized by covalent and hydrogen bonds. Our calculations showed that adsorption energies range from -120 to -302. kJ/mol, with subsequent decomposition reactions being highly exergonic (ΔEdec ranging from -199 to -381. kJ/mol) and exothermic, releasing significant heat aligned with experimental observations. Notably, the anatase (101) surface exhibits greater reactivity than the rutile (110), an insight supported by experimental validation. The activation mechanisms are primarily entropy-driven across the TiO2 phases. Additionally, the study investigated alumina (Al2O3) passivation shells on aluminum particles and their reactions with halogenated species. DFT calculations demonstrated that iodine species (HI and I-) exhibit nearly triple the adsorption energies compared to fluorinated fragments, with energetically favorable adsorption but unfavorable exchange reactions with alumina. Differential scanning calorimetry (DSC) experiments confirmed the higher energy release during iodine-related reactions, highlighting potential pathways for alumina modification. These insights open avenues for tailoring surface chemistries to enhance energetic material performance.
When: 4:00 pm (Lubbock's local time is GMT -5)
Where: room Math 011 (Math Basement)
ZOOM details:
- Choice #1: use this link
Direct Link that embeds meeting and ID and passcode.
- Choice #2: join meeting using this link
Join Meeting, then you will have to input the ID and Passcode by hand:
* Meeting ID: 915 2866 2672
* Passcode: applied
Math Circle Fall Flyer
Adaptive cancer therapy is a new paradigm of treatment for non-curative disease that aims to prolong emergence of resistance, and thus treatment failure. Here we use a mathematical model to explore how incorporating treatment toxicity into the protocol of adaptive therapy can be beneficial by both extending time to treatment failure and improving the quality of life for the patient. I will then demonstrate how the assumptions used when constructing a mathematical model can impose bias in simulations, resulting in differences in treatment predictions. These differences and biases affect personalized treatment plans and are critical to understand in order to quantifying the uncertainty in model predictions of cancer therapy.
The Biomath seminar may be attended virtually Friday at 11:00 AM CDT (UTC-5) via this Zoom link.
Meeting ID: 938 8653 3169
Passcode: 883472
abstract noon CDT (UT-5)
Zoom link available from Dr. Brent Lindquist upon request.