Featured Post from VCU College of Engineering

Researchers use computer models and simulations to predict satellite resilience

Computational physics provides foundation for little-understood physical state generated by nuclear detonation in space.

Jan 27, 2023

4 min

Gennady Miloshevsky, Ph.D.

Computational physics is a field of nuance and detail. Using mathematics, researchers build computer models and simulations to test hypotheses within a digital environment. These numerical experiments are often used when practical testing is not feasible like when, for example, you must ascertain the durability of materials in a nuclear explosion.


Gennady Miloshevsky, Ph.D., is an associate professor of mechanical and nuclear engineering who specializes in computational physics with an emphasis on plasma, lasers and particle beams. He works to predict the behavior and state of materials when under extreme pressure, temperature and radiation.


With funding from the Defense Threat Reduction Agency (DTRA), an agency of the U.S. Department of Defense (DoD), Miloshevsky is studying the effect weapons of mass destruction have on satellites within Earth’s orbit. His work requires a distinct familiarity with our physical world and how different forms of energy interact with and within matter.


“Any satellite close to the detonation point would be destroyed,” says Miloshevsky, “However, beyond that initial area, surviving satellites could be subject to X-ray induced blow-off, thermo-mechanical shock and warm dense plasma formation take place on material surfaces. This causes damage to exposed optics, sensors and solar cells on satellites. Particularly dense surface plasmas can couple the solar cells to each other in gaps between unshielded active elements and to dielectric structures causing them to be destroyed. It would all depend on the distance from the detonation point and the orientation of the satellite.”


Part of Miloshevsky’s research involves developing methods to computationally simulate temperature, pressure and radiation in order to study the state known as “warm dense plasma,” which occurs between the solid and classical plasma states and exhibits the characteristics of both. A better understanding of this state of matter is a stepping stone to building more resilient materials.


“Warm dense plasma is highly transient and short lived,” says Miloshevsky. “The state occurs in several nanoseconds, so isolating it in a laboratory setting in order to characterize it is very complicated. A nuclear burst irradiates materials with high-intensity X-rays, resulting in the transition to warm dense plasma. Our DTRA research seeks to understand the fundamental physics of warm dense plasma, including its physical and electrical properties. It’s currently unclear how this may affect the choice of future materials for satellite components.”


A ban on nuclear testing means research into the effects of nuclear weapons is only possible through the use of computer codes to either model or simulate the many physics phenomena generated by a nuclear detonation.


Miloshevsky’s first research area includes quantifying and reducing the uncertainty of computer model material properties, such as diamond, under the conditions of a nuclear blast using REODP (Radiative Emissivity and Opacity of Dense Plasmas) computer code he developed. This code is used to investigate the ionization state and ion abundances for equilibrium and transient-dense plasmas. It helps predict the equations of state, transport and optical properties of materials in the category of warm dense plasma.


In a second research area, Miloshevsky works to understand and predict the interaction between X-rays and satellite surface materials (like silicon, germanium and other materials used to make solar panels) during a nuclear detonation in space. This uses MIRDIC (Modeling Ionizing Radiation Deep Insulator Charging) code developed in collaboration with NASA’s Marshall Space Flight Center for its Europa Lander project. This code helps anticipate charge production by blackbody X-rays in dielectrics and insulators of DoD space systems. It can also predict electrostatic material breakdown.


Also part of the second research area is work to understand X-ray-induced shock generation, material ablation and blow-off (when material is literally “blown off” the satellite in reaction to another force) within the vacuum of space. This is studied using MSM-LAMMPS (Momentum Scaling Model implemented within the Large-scale Atomic/Molecular Massively Parallel Simulator software package) code. It predicts material behavior at an atomic level within extreme environments, the nature and behavior of materials in highly non-equilibrium states, microscopic mechanisms of disintegration, blow-off, melting, ionization and warm dense plasma states.


Practical experiments in a lab use lasers to replicate the heat and pressure generated by X-ray radiation, shock and other physical effects of a nuclear detonation. Miloshevsky’s colleagues at the John Hopkins Extreme Materials Institute heat carbide diamond and silica materials typically found in solar panels to temperatures between 11,600 and 1,160,000 Kelvin using lasers at the University of Rochester and Pacific Northwest National Laboratory to observe this momentary transformation into warm dense plasma. Researchers use shadowgraphy, spectroscopy and other visual analytical methods to quantify the result. They can also investigate the depth, size and shape of the crater created by the laser within the material surface.


“Experimental and computational research are closely interconnected and complement each other,” says Miloshevsky. “The laser-material interaction is a complicated process that occurs on multiple space (nanometers to millimeters) and time (femtoseconds to milliseconds) scales with evolving and changing physics. Data measured in these experiments usually need physics insights from a computer model to be correctly interpreted and understood. Models can provide fine details of physics processes that cannot be revealed in the practical experiments due to the incredibly minute space and time scales. Conversely, data from physical experimentation can feed into a computer model so it can be further developed and refined to enhance the understanding of the experiment’s measured data.”


Miloshevsky’s recent topical review paper, Ultrafast laser matter interactions: modeling approaches, challenges, and prospects, details some of these advances in computational modeling and simulation development for laser-pulse interactions with solids and plasma.

Connect with:
Gennady Miloshevsky, Ph.D.

Gennady Miloshevsky, Ph.D.

Associate Professor, Department of Mechanical and Nuclear Engineering

Professor Miloshevsky researches computational physics with emphasis on effects of plasma, laser and particle beams on materials.

Materials Under Extreme ConditionsNuclear and Spacecraft MaterialsRadiation- and Plasma-Material InteractionsRadiation Transport and ShieldingPhysics of High Energy Densities

You might also like...

Check out some other posts from VCU College of Engineering

2 min

DARPA awards VCU $4.875 million for development of modular drug manufacturing platform

The Defense Advanced Research Projects Agency (DARPA) is funding a $13M grant for a Rutgers University and Virginia Commonwealth University (VCU) partnership through the EQUIP-A-Pharma program, with $4.175 million to James Ferri, Ph.D., professor in the Department of Chemical and Life Science Engineering at VCU, to develop a modular manufacturing platform for sterile liquid drug products. The 24-month grant supports Ferri’s project, “Modular Manufacturing of Sterile Liquid Drug Products,” which develops a continuous manufacturing platform capable of producing highly potent drug substances such as albuterol sulfate and bupivacaine hydrochloride. These drug substances are for use in sterile liquid products, where compliance with purity of the active pharmaceutical ingredient (API) and impurity profiles are characterized and controlled in real time throughout the manufacturing process. “This work enables agile continuous manufacturing of drug substance and end-to-end drug product manufacturing of several highly potent drug substances with real time quality control,” Ferri said. “The combination of dynamic modular operation and real-time quality control will increase the supply of critical medicines in the United States.” Drug shortages continue to receive national attention, with albuterol sulfate and bupivacaine hydrochloride both appearing on the U.S. Food and Drug Administration drug shortage list within the past year. The project develops technologies that enable distributed manufacturing approaches to essential medicines currently in shortage in the United States. The platform incorporates several innovative features including continuous flow synthesis for improved process performance, online spectroscopy for real-time quality control, and modular unit operations that can be rapidly configured for different drug products. Key technologies include heterogeneous catalytic flow reactors, in-line purification systems and advanced process analytical technologies. The continuous manufacturing approach offers significant advantages over traditional batch manufacturing, including improved process control, reduced waste and the ability to produce medicines closer to the point of care. The modular design enables rapid deployment and flexible manufacturing of multiple drug products using the same platform. Ferri is collaborating with researchers from Rutgers University on the project, which began in August 2024. The platform is designed to fit within a standard shipping container, enabling distributed manufacturing capabilities. The research directly addresses national security concerns about pharmaceutical supply chain vulnerabilities while advancing the field of continuous pharmaceutical manufacturing. Students involved in the project gain experience in cutting-edge manufacturing technologies that are increasingly important in addressing global health challenges.

3 min

Neutrons by the trillions: Using computational physics to understand nuclear reactors

Zeyun Wu, Ph.D., associate professor in the mechanical and nuclear engineering department at VCU Engineering, is reshaping the future of nuclear power. Nuclear reactors are among the most complex engineered systems on earth, with different physical processes interacting simultaneously across various scales. Even the world's most powerful computers cannot simulate every detail of an operating reactor at once. With a background in computational reactor physics, Wu’s research develops modeling and simulation techniques crucial to understanding next-generation nuclear reactors. By creating these advanced tools, his research eliminates the need for costly physical experimentation while ensuring the safety, efficiency and environmental sustainability of future nuclear power plants. Wu's research focuses on understanding reactor behavior through two aspects: multi-physics and multi-scale modeling. The multi-physics approach integrates various physical phenomena, such as nuclear physics reactions, fluid dynamics, heat transfer and structural mechanics, into a unified simulation framework. The multi-scale modeling technique addresses the vast range of physical scales involved, from subatomic neutron interactions to meter-sized reactor components. Wu’s research can simulate the complex phenomena within reactors at different scales. These models, developed using advanced numerical methods, help predict reactor behavior under various conditions. One of the models Wu uses tracks neutron behavior, a fundamental aspect to understand nuclear reactions. His simulations track trillions of neutrons as they move through various reactor materials, cause fission events and generate power. "What drives power is actually the neutron," explained Wu. "Once an atom splits, along with the nuclear energy release, lots of neutrons come out. We're talking about 1012 to 1013 neutrons per second. Our code tracks each neutron to understand where it comes from and where it goes." By understanding neutron distribution across space, time and energy domains, Wu's team can predict power distribution throughout the reactor core. This helps identify potential hotspots – areas of heightened thermal activity that could pose safety challenges. Beyond neutron behavior, Wu's research also explores how cooling fluids interact with neutrons and carry away thermal energy, a field known as thermal hydraulics, because how the reactor components are cooled significantly affects the neutron behavior as well. This also explains why the multi-physics modeling becomes essential for nuclear reactor simulations. Wu founded the Computational Applied Reactor Physics Laboratory (CARPL) to continue his research in nuclear reactor modeling and simulation. Undergraduate and master’s students learn to use established nuclear simulation codes to analyze reactor problems – skills highly valued in the industry and national labs. Ph.D. students build on theoretical foundations to deepen their understanding, enhance existing models, and develop new ones. “My area of research has been continually evolving for the past 60 years or so,” said Wu. “Most of the codes we use have been developed by national labs, like Oak Ridge National Lab, but these codes aren’t perfect. National labs hire Ph.D. level students with this niche to identify deficits in the code, correct errors and even add new functions and improve them.” Looking forward, Wu hopes his research will have a real-world impact on the upcoming shift in nuclear power in America. Over the next 20 to 30 years, the nation's approximately 90 light-water-cooled nuclear reactors reach the end of their operational lifetimes. Light water refers to ordinary water (H₂O), used in most existing reactors to both cool the system and slow down neutrons to sustain the nuclear reaction. To replace them, experts are looking toward advanced, non-light-water-cooled reactors, such as the Molten Uranium Breeder Reactor (MUBR) shown in the figure. Computational methods and tools like Wu’s research lab developed will be essential to their development and implementation. Non-light-water cooled reactors offer significant advantages over the older designs. Some can operate at higher temperatures while others produce substantially less nuclear waste, addressing one of the industry's persistent challenges. "Unlike traditional water reactors, where we have decades of operational experience and established analysis tools, these new designs present unique challenges," explained Wu. "Companies like Dominion employ large teams of analysts who use well-tested computational tools to maintain their existing reactors, but those same tools aren't calibrated for these next-generation reactors. Our research is developing the computational methods and simulations these advanced reactors will need. When these new reactors come online, the methodologies we're creating now can be quickly converted into production-level nuclear codes, providing immediate practical value to industry.”

6 min

College of Engineering researchers develop technology to increase production of biologic pharmaceuticals for diabetes treatment

Chemical and Life Science Engineering Professor Michael “Pete” Peters, Ph.D., is investigating more efficient ways to manufacture biologic pharmaceuticals using a radial flow bioreactor he developed. With applications in vaccines and other personalized therapeutic treatments, biologics are versatile. Their genetic base can be manipulated to create a variety of effects from fighting infections by stimulating an immune response to weight loss by producing a specific hormone in the body. Ozempic, Wegovy and Victoza are some of the brand names for Glucagon-Like Peptide-1 (GLP-1) receptor agonists used to treat diabetes. These drugs mimic the GLP-1 peptide, a hormone naturally produced in the body that regulates appetite, hunger and blood sugar. “I have a lot of experience with helical peptides like GLP-1 from my work with COVID therapeutics,” says Peters. “When it was discovered that these biologic pharmaceuticals can help with weight loss, demand spiked. These drug types were designed for people with type-2 diabetes and those diabetic patients couldn’t get their GLP-1 treatments. We wanted to find a way for manufacturers to scale up production to meet demand, especially now that further study of GLP-1 has revealed other applications for the drug, like smoking cessation.” Continuous Manufacturing of Biologic Pharmaceuticals Pharmaceuticals come in two basic forms: small-molecule and biologic. Small-molecule medicines are synthetically produced via chemical reactions while biologics are produced from microorganisms. Both types of medications are traditionally produced in a batch process, where base materials are fed into a staged system that produces “batches” of the small-molecule or biologic medication. This process is similar to a chef baking a single cake. Once these materials are exhausted, the batch is complete and the entire system needs to be reset before the next batch begins. “ The batch process can be cumbersome,” says Peters. “Shutting the whole process down and starting it up costs time and money. And if you want a second batch, you have to go through the entire process again after sterilization. Scaling the manufacturing process up is another problem because doubling the system size doesn’t equate to doubling the product. In engineering, that’s called nonlinear phenomena.” Continuous manufacturing improves efficiency and scalability by creating a system where production is ongoing over time rather than staged. These manufacturing techniques can lead to “end-to-end” continuous manufacturing, which is ideal for producing high-demand biologic pharmaceuticals like Ozempic, Wegovy and Victoza. Virginia Commonwealth University’s Medicines for All Institute is also focused on these production innovations. Peters’ continuous manufacturing system for biologics is called a radial flow bioreactor. A disk containing the microorganisms used for production sits on a fixture with a tube coming up through the center of the disk. As the transport fluid comes up the tube, the laminar flow created by its exiting the tube spreads it evenly and continuously over the disk. The interaction between the transport medium coming up the tube and the microorganisms on the disk creates the biological pharmaceutical, which is then taken away by the flow of the transport medium for continuous collection. Flowing the transport medium liquid over a disc coated with biologic-producing microorganisms allows the radial flow bioreactor to continuously produce biologic pharmaceuticals. “There are many advantages to a radial flow bioreactor,” says Peters. “It takes minutes to switch out the disk with the biologic-producing microorganisms. While continuously producing your biologic pharmaceutical, a manufacturer could have another disk in an incubator. Once the microorganisms in the incubator have grown to completely cover the disk, flow of the transport medium liquid to the radial flow bioreactor is shut off. The disk is replaced and then the transport medium flow resumes. That’s minutes for a production changeover instead of the many hours it takes to reset a system in the batch flow process.” The Building Blocks of Biologic Pharmaceuticals Biologic pharmaceuticals are natural molecules created by genetically manipulating microorganisms, like bacteria or mammalian cells. The technology involves designing and inserting a DNA plasmid that carries genetic instructions to the cells. This genetic code is a nucleotide sequence used by the cell to create proteins capable of performing a diverse range of functions within the body. Like musical notes, each nucleotide represents specific genetic information. The arrangement of these sequences, like notes in a song, changes what the cell is instructed to do. In the same way notes can be arranged to create different musical compositions, nucleotide sequences can completely alter a cell’s behavior. Microorganisms transcribe the inserted DNA into a much smaller, mRNA coded molecule. Then the mRNA molecule has its nucleotide code translated into a chain of amino acids, forming a polypeptide that eventually folds into a protein that can act within the body. “One of the disadvantages of biologic design is the wide range of molecular conformations biological molecules can adopt,” says Peters. “Small-molecule medications, on the other hand, are typically more rigid, but difficult to design via first-principle engineering methods. A lot of my focus has been on helical peptides, like GLP-1, that are a programmable biologic pharmaceutical designed from first principles and have the stability of a small-molecule.” The stability Peters describes comes from the helical peptide’s structure, an alpha helix where the amino acid chain coils into a spiral that twists clockwise. Hydrogen bonds that occur between the peptide’s backbone creates a repeating pattern that pulls the helix tightly together to resist conformational changes. “It’s why we used it in our COVID therapeutic and makes it an excellent candidate for GLP-1 continuous production because of its relative stability,” says Peters. Programming The Cell Chemical and Life Science Engineering Assistant Professor Leah Spangler, Ph.D., is an expert at instructing cells to make specific things. Her material science background employs proteins to build or manipulate products not found in nature, like purifying rare-earth elements for use in electronics. “My lab’s function is to make proteins every day,” says Spangler. “The kind of proteins we make depends entirely on the project they are for. More specifically I use proteins to make things that don’t occur in nature. The reason proteins don’t build things like solar cells or the quantum dots used in LCD TVs is because nature is not going to evolve a solar cell or a display surface. Nature doesn’t know what either of those things are. However, proteins can be instructed to build these items, if we code them to.” Spangler is collaborating with Peters in the development of his radial flow bioreactor, specifically to engineer a microorganismal bacteria cell capable of continuously producing biologic pharmaceuticals. “We build proteins by leveraging bacteria to make them for us,” says Spangler. “It’s a well known technology. For this project, we’re hypothesizing that Escherichia coli (E. coli) can be modified to make GLP-1. Personally, I like working with E. coli because it’s a simple bacteria that has been thoroughly studied, so there’s lots of tools available for working with it compared to other cell types.” Development of the process and technique to use E. coli with the radial flow bioreactor is ongoing. “Working with Dr. Spangler has been a game changer for me,” says Peters. “She came to the College of Engineering with a background in protein engineering and an expertise with bacteria. Most of my work was in mammalian cells, so it’s been a great collaboration. We’ve been able to work together and develop this bioreactor to produce GLP-1.” Other Radial Flow Bioreactor Applications Similar to how the GLP-1 peptide has found applications beyond diabetes treatment, the radial flow bioreactor can also be used in different roles. Peters is currently exploring the reactor’s viability for harnessing solar energy. “One of the things we’ve done with the internal disc is to use it as a solar panel,” says Peters. “The disk can be a black body that absorbs light and gets warm. If you run water through the system, water also absorbs the radiation’s energy. The radial flow pattern automatically optimizes energy driving forces with fluid residence time. That makes for a very effective solar heating system. This heating system is a simple proof of concept. Our next step is to determine a method that harnesses solar radiation to create electricity in a continuous manner.” The radial flow bioreactor can also be implemented for environmental cleanup. With a disk tailored for water filtration, desalination or bioremediation, untreated water can be pushed through the system until it reaches a satisfactory level of purification. “The continuous bioreactor design is based on first principles of engineering that our students are learning through their undergraduate education,” says Peters. “The nonlinear scaling laws and performance predictions are fundamentally based. In this day of continued emphasis on empirical AI algorithms, the diminishing understanding of fundamental physics, chemistry, biology and mathematics that underlie engineering principles is a challenge. It’s important we not let first-principles and fundamental understanding be degraded from our educational mission, and projects like the radial flow bioreactor help students see these important fundamentals in action.”

View all posts
Powered by