Main Library

Fri7:30 am - 5:00 pm
Open

Reference Desk

Fri10:00 am - 5:00 pm
Open

Digital Fabrication Lab

Fri10:00 am - 3:00 pm
Open

Germans from Russia Heritage Collection

Fri8:00 am - 4:00 pm
Open

NDSU Archives

Fri8:00 am - 4:00 pm
Open

Business Learning Center

Fri7:30 am - 4:00 pm *
Open

Klai Juba Wald Architectural Studies Library

Mon12:00 pm - 4:00 pm
Closed

P. N. Haakenson Health Sciences Library

Fri8:00 am - 4:00 pm
Open

NDSU Nursing at Sanford Health Library

Mon7:30 am - 4:00 pm *
Closed
Home LURA Recipient 2021

LURA Recipient 2021

May 3, 2021

Join us in congratulating NDSU Libraries Undergraduate Research Award (LURA) 2021 recipient, Marvellous Ngongang! This award recognizes excellence in the use of library resources in completing an undergraduate research project. Marvellous's project is titled "A Refractive Index Study of a Diverse Set of Polymeric Materials by QSPR with Quantum-Chemical and Additive Descriptors."

Marvellous is a senior majoring in Biochemistry and Molecular Biology, set to graduate in May 2021. She works as a Resident Assistant at Burgum Hall, and also works in Research Lab 1. In her spare time, she likes to spend quality time with family and friends and binge watch tv. After college, she will be working in the lab at Aldevron, a biological science company.

Marvellous advises other students to remember that resources are not limited to the physical library buildings. She stated, "Step out of your comfort zone and start by exploring the available online resources because they are very helpful and it’s easy to maneuver through the site!" 

"I would like to give a special thank you to Dr. Rasulev for being a great supervisor and including me in this project. I would also like to thank my other lab members and NDSU Libraries for their readily available resources," stated Marvellous.

Project Abstract:
In silico methods is a cost- and time-effective way to synthesize materials. Refractive index (n) is an important characteristic of an optical material. This work contains a quantitative structure–property relationship (QSPR) model that was developed to predict the (n) of 262 polymers collected from various sources. Several models were created, where a four-variable model showed the best predictive performance. The best model’s predictability was validated using the leave-one-out technique, external set, and y-scrambling methods. For (n), ionization potential, polarizability, 2D and 3D geometrical descriptors were the most influential. The model can be used to predict (n) for untested polymers. Details will be available on the NDSU Repository soon.

We congratulate Marvellous on this award and her upcoming graduation, and look forward to her future successes.

For undergraduate students who may be interested in this award opportunity, please visit the LURA page for additional information. 

 

 

 

 

 

 

 

 

 

 

 

Sunday Monday Tuesday Wednesday Thursday Friday Saturday
27
28
29
30
1
2
3
 
 
 
 
 
 
 
4
5
6
7
8
9
10
 
 
 
 
 
 
 
11
12
13
14
15
16
17
 
 
 
 
 
 
 
18
19
20
21
22
23
24
 
 
 
 
 
 
 
25
26
27
28
29
30
31