Author: Alec Linot, Postdoctoral Scholar and IDRE Fellow – Department of Mechanical and Aerospace Engineering In industrial processes involving fluids, vast amounts of energy are lost as dissipation due to turbulent drag. The energy production required to sustain these processes accounts for 5% of all manmade carbon dioxide (Jimenez 2013). Consequently, even small improvements toward...
Read More Optimal perturbations in high-dimensional unsteady aerodynamic flows

IDRE Fellow: Dr. Olivia Sanderfoot (Postdoctoral Scholar) Faculty Mentor:  Dr. Morgan Tingley (Associate Professor) Department: Ecology & Evolutionary Biology Project Description: Climate change coupled with a legacy of fire suppression is driving an increase in the frequency, intensity, and severity of wildfires1,2, prompting the United Nations to declare a worldwide “wildfire crisis3.” The record-breaking 2020 wildfire season in the...
Read More Integrating long-term ecological monitoring data and high-resolution atmospheric models to investigate avian responses to wildfire smoke

We are working towards creating a joint experimental/theoretical/computational framework to explore the behavior of liquids which have programmable interactions. Inspired by liquid liquid phase separation as a mechanism of organization in biological systems, we are looking in depth at systems containing both chemical reactions (interconversion of species) and phase separation (weak multivalent interactions between species)....
Read More Simulations of Programmable Liquids

The properties of cementitious binders are controlled by their composition and structure at different scales. However, the complexity of their disordered, multi-scale structure makes it challenging to elucidate such linkages. In particular, due to a lack of physical models, predicting the strength development of concretes remains challenging. As an alternative route to physics-based models, machine...
Read More Prediction of Concrete’s Strength Enabled by Machine Learning Methods

Recent studies in nanophotonic structures and metamaterials have showcased remarkable applications such as invisibility cloaks, perfect lenses, radiative cooling, and light trapping for solar cells. However, current design methodologies require computationally-intensive, time-consuming, and iterative processes to realize structurally-complex devices. For example, finite-element analysis (FEA) simulation and other “forward design” methods involve a series of trial-and-error...
Read More Machine Learning-based Inverse Design of Thermal Photonic Metasurfaces

Wound healing is a systems-level program governed by complex inter and intracellular networks. After wounding, receptor activation causes intracellular signaling cascades inducing downstream transcriptional changes specific to the dose and identity of the ligand. Although these networks have been rigorously studied, establishing a direct mapping between signaling and gene expression is still an open question. I...
Read More Decoding NF-κB Dynamics Using A High-Throughput, Information-Based Approach

The quasi-static particle-in-cell (PIC) algorithm is extensively utilized to model short-pulse or high-energy charged particle interacting with plasma. Compared to the very computationally intensive full three-dimensional (3D) explicit PIC code, the quasi-static PIC codes are able to speed up the simulations by orders of magnitude, which allows for modeling the physical problems requiring massive computing...
Read More Highly efficient quasi-static particle-in-cell algorithm using azimuthal Fourier decomposition

Naturally occurring chorus emissions are a class of electromagnetic waves found in the space environments of the Earth and other magnetized planets. They play an essential role in accelerating high-energy electrons forming the hazardous radiation belt environment. Chorus typically occurs in two distinct frequency bands separated by a gap. The origin of this two-band structure...
Read More NASA’s spacecraft data reveals the origin of two-band chorus in outer space

The Indus River Basin (IRB) is a large river basin supporting 237 million people, but a limited gauge network means that there are relatively few measurements upon which to base water management decisions. With new globally available data products like the Multi-Error-Removed Improved Terrain (MERIT) DEM and the FAO’s Harmonized World Soil Database (HWSD) and...
Read More Calibrating a hydrological model in the Indus River Basin

Developing novel glasses with new, improved properties and functionalities is crucial to address major challenges in energy, communications and infrastructure. A data-driven machine learning (ML) technique is a potential method to accelerate the discovery in novel glass; however, there are some intrinsic limitations embedded in such ML models. For example, the use of traditional ML...
Read More Topology-informed machine learning for the prediction of glass stiffness

Despite recent advances related to smartphone cover screens, glass still breaks. Brittleness remains the main limitation of glass, as the risk of fracture often raises safety and reliability concerns. Throughout history, glass has been associated with danger and, in fact, it has been estimated that 15-to-30% of injuries are related to broken glass. Here, we...
Read More Overcoming the Brittleness of Glass by Nanoscale Phase Separation

Atomistic simulations can offer direct access to the atomic structure of glasses, which is otherwise invisible from conventional experiments. However, molecular dynamics (MD) simulations of glasses based on the melt-quenching technique remain plagued by the use of high cooling rates, while reverse Monte Carlo (RMC) modeling can yield non-unique solutions. Here, we adopt the force-enhanced...
Read More New Insights into the Structure of Sodium Silicate Glasses by Force-Enhanced Atomic Refinement

Large-scale simulations of many of today’s interesting problems in plasma physics suffer from severe load balance issues, including plasma-based acceleration and magnetic reconnection with pair production due to quantum-electrodynamic effects.  Contemporary particle-in-cell codes must be designed to efficiently utilize a new fleet of exascale computing architectures.  We discuss the implementation of dynamic load balancing by...
Read More Dynamic Load Balancing with Enhanced OpenMP Parallelism in OSIRIS

BACKGROUND: A specific aspect of the hypospadias phenotype that may contribute to long-term outcomes is the presence of ventral penile curvature and the adequacy of its surgical correction. The current gold standard to assess this angle is intraoperative goniometry of an erect penis. Beyond its potential technical limitations, an angle measured by goniometry cannot be...
Read More Measurement Accuracy of 3-Dimensional Modeling Technologies versus Standard Goniometry for Assessment of Angulation

A range of nonlinear wave structures, including Langmuir waves, unipolar electric fields and bipolar electric fields, are often observed in association with whistler-mode chorus waves in the near-Earth space. We demonstrate that the three seemingly different nonlinear wave structures originate from the same nonlinear electron trapping process by whistler-mode chorus waves. Only a single quantity,...
Read More Unified view of nonlinear wave structures associated with whistler-mode chorus

Understanding the response of glasses to indentation (e.g., permanent densification or shear flow) is critical to developing new ultrahard glasses for cover screen applications. However, the linkages between the compositions of glasses and their response to indentation remain unclear. Here, we conduct some peridynamic simulations to model the nanoindentation of silicate glasses with varying compositions....
Read More New insights into the response to indentation of glasses from peridynamic simulations