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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June-October), aerosol particles reaching 3-5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ~350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ~100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Easy-Processable and Aging-Free All-Polymer Polysiloxane Composites

In this work, we report all-polymer polysiloxane composites that overcome the long-standing processing problems of silica-reinforced silicone rubbers. Polystyrene fillers are dispersed with styrene/dimethylsiloxane symmetric diblock and triblock copolymers that control the filler morphology, filler–matrix interactions, and filler–filler interactions. Surprisingly, the composites not only rival the traditional silica-reinforced polysiloxane in mechanical properties of cured materials but also have better processability and stability than the silica-filled compound before curing. Large amplitude oscillatory shear experiments demonstrate that the triblock copolymer addition strongly affects the rheological properties. We hypothesize that the bridges and entangled loops that were formed by the triblock copolymer can connect different PS domains to provide additional reinforcement. The aging effect that originates from PDMS chain adsorption on the filler particle surface is also avoided because of the thermodynamic repulsion between PS and PDMS phases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems. How soil organic carbon (SOC) forms and persists remains uncertain, which makes it challenging to understand how it will respond to climatic change. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Energy growth in VLVL → VLVL, VLVLh scattering to probe Higgs cubic and HEFT interactions

Abstract We compute the energy scales of perturbative unitarity violation inV L V L →V L V L hprocesses and compare them toV L V L →hhhprocess, whereV L refers to a longitudinal mode ofZorWboson, andhthe Higgs boson. Using these energy scales, we determine which process is more sensitive to potential modifications in the Higgs sector at high-energy colliders. Within the Higgs Effective Field Theory (HEFT), we consider the Higgs cubic coupling and other interactions with and without derivatives. Any HEFT interactions predict the perturbative unitarity violation at a finite scale, and in a generic case, the minimalistic process is 2 → 3 scattering. Our analysis reveals that the energy scales for unitarity violation inV L V L →V L V L handV L V L →hhhprocesses are similar across all scenarios considered. If the backgrounds are similar,V L V L hfinal states are more feasible becauseV L V L hhas higher branching ratios in cleaner decay modes thanhhh. We also investigate HEFT derivative interactions derived from various UV models. In these cases, bothV L V L →V L V L andV L V L →hhprocesses exhibit unitarity violating behavior. We demonstrate that the energy scales for unitarity violation inV L V L final states are comparable to or even lower than those in thehhfinal state.

Physics↗
DOE OSTI2025

Emergent properties of magnons coupled to microwave photons (Final Technical Report)

Studying the emergent properties of hybrid quantum material platforms holds great promise for advancing quantum technologies and transforming our ability to control quantum mechanical interactions. A key development in recent years is the recognition that magnons – the elementary quanta of spin waves – can serve as fundamental building blocks in quantum systems. Understanding the mechanisms behind the generation and control of hybrid quasiparticles based on magnons could pave the way for engineering new materials for quantum coherent processing and quantum computing. This research project focused on the precise control of light-matter interactions in magnetic hybrid systems and nanostructures, where light is carried by microwave photons and matter by magnons in engineered magnetic metamaterials. Furthermore, we investigated hybridized magnon interactions in magnetic nanostructures and devices. To this end, the project has developed new measurement techniques and systematically studied novel material systems for efficient magnon-photon coupling. A key focus was uncovering the fundamental mechanisms governing magnon-photon and magnon-phonon interactions – critical for utilizing magnons as coherent information transducers between carriers. Specifically, this research addressed: 1. Investigate the dispersion and collective properties of magnon hybrid systems in new material systems. 2. Develop magnonic hybrids with non-zero wavevectors and achieve effective control of magnon-polariton properties through engineered magnonic behaviors. 3. Determine how spin-orbit torques interact with electromagnetic fields in the strong coupling regime. This work generated new insights into the physics of magnonic hybrid systems and their emergent properties by broadening the range of material platforms and measurement techniques used to study magnon-photon and magnon-magnon coupling. The findings deepen our understanding of magnon-polaritons and lay the groundwork for novel spintronic devices with potential applications in quantum information science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Concept Study of Robotic Camera-Based Foreign Object Detection for EV Wireless Charging

Wireless charging of an electric vehicle (EV) is an emerging charging technology promising convenient, autonomous, and highly efficient EV charging without requiring heavy gauge cables. However, due to the strong electromagnetic field created by this process that surrounds the wireless charger, the presence of foreign objects can detrimentally interact with it, thus affecting wireless power transfer (WPT) performance or leading to harmful and unwanted safety risks. This paper presents the results for a concept study on a robotic camera-based foreign object detection (FOD) system, as a supplement to the industry-existing overlapped FOD coil array method, for EV wireless charging. A Raspberry PI 4 control board and compatible Raspberry PI Camera Module 2 are used to implement camera-based object detection. The FOD program was developed using a state-of-the-art deep learning object detection model with the OpenCV and Pytorch library and is compatible with camera module hardware. A dry-run test with Raspberry PI and a camera module was conducted and the preliminary FOD function was verified. The feasibility assessment is also validated by comparing the performance of five existing state-of-the-art deep learning object detection models for vehicles, animals, persons, and metals subsets, respectively. Satisfactory performance on the benchmark datasets is observed by the tests, but further improvements are needed in future work when detecting small-sized metallic objects. A programable robotic car is also under development as ongoing work for carrying the Raspberry PI and camera module while moving for the maintenance process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Simulations of nonradiative processes in semiconductor nanocrystals

The description of carrier dynamics in spatially confined semiconductor nanocrystals (NCs), which have enhanced electron–hole and exciton–phonon interactions, is a great challenge for modern computational science. These NCs typically contain thousands of atoms and tens of thousands of valence electrons with discrete spectra at low excitation energies, similar to atoms and molecules, that converge to the continuum bulk limit at higher energies. Computational methods developed for molecules are limited to very small nanoclusters, and methods for bulk systems with periodic boundary conditions are not suitable due to the lack of translational symmetry in NCs. This perspective focuses on our recent efforts in developing a unified atomistic model based on the semiempirical pseudopotential approach, which is parameterized by first-principle calculations and validated against experimental measurements, to describe two of the main nonradiative relaxation processes of quantum confined excitons: exciton cooling and Auger recombination. Here, we focus on the description of both electron–hole and exciton–phonon interactions in our approach and discuss the role of size, shape, and interfacing on the electronic properties and dynamics for II–VI and III–V semiconductor NCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Facet-dependent growth and dissolution of hematite resulting from autocatalytic interactions with Fe(II) and oxalic acid

The ability to simultaneously monitor the flux of iron atoms within the solution and solid phases can provide considerable insight into mechanisms of iron oxide mineral transformations. The autocatalytic interaction between hematite and Fe(II)-oxalate has long been of interest for its environmental and industrial relevance. In this study we take advantage of iron isotopic labelling and mass-sensitive imaging at the single particle scale to determine how changes in solution composition correlate with the morphologic evolution of faceted, micrometer-sized hematite platelets. Net dissolution is confirmed through analyses of aqueous iron chemistry, as well as by quantitative atomic force microscopy. Isotopic mapping techniques show that Fe(II) readily adsorbs to (001) and (012) surfaces in the absence of oxalate, but when oxalate is present selective dissolution of the (001) surface prevails and 57Fe deposition via recrystallization is not observed. Comparison between particle microtopographies following reaction with Fe(II), oxalate, and Fe(II)-oxalate show substantially different behavior, consistent with distinct mechanisms of interaction with hematite surfaces. The extensive characterization conducted on the coupled solution/solid dynamics in this system provides new insight for distinguishing crystal growth, dissolution, and recrystallization processes.

Taylor, Sandra D. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2022

X 17 boson and the H 3 ( p , e + e – ) He 4 and He 3 ( n , e + e – ) He 4 processes: A theoretical analysis

The present work deals with e + – e – pair production in the four-nucleon system. We first analyze the process as a purely electromagnetic one in the context of a state-of-the-art approach to nuclear strong-interaction dynamics and nuclear electromagnetic currents, derived from chiral effective field theory ( χ EFT ) . Next, we examine how the exchange of a hypothetical low-mass boson would impact the cross section for such a process. We consider several possibilities, that this boson is either a scalar, pseudoscalar, vector, or axial particle. The ab initio calculations use exact hyperspherical-harmonics methods to describe the bound state and low-energy spectrum of the A = 4 continuum, and they fully account for initial state interaction effects in the 3 + 1 clusters. While electromagnetic interactions are treated to high orders in the chiral expansion, the interactions of the hypothetical boson with nucleons are modeled in leading-order χ EFT (albeit, in some instances, selected subleading contributions are also accounted for). We also provide an overview of possible future experiments probing pair production in the A = 4 system at a number of candidate facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Damage and Failure in a Statistical Crack Model

In this paper I will take a close look at a statistical crack model (SCM) as is used in engineering computer codes to simulate fracture at high strain rates. My general goal is to understand the macroscopic behavior effected by the microphysical processes incorporated into an SCM. More specifically, I will assess the importance of including local interactions between cracks into the growth laws of an SCM. My strategy will be to construct a numerical laboratory that represents a single computational cell containing a realization of a statistical distribution of cracks. The cracks will evolve by the microphysical models of the SCM, leading to quantifiable damage and failure of the computational cell. I will use the numerical data generated by randomly generated ensembles of the fracture process to establish scaling laws that will modify and simplify the implementation of the SCM into large scale engineering codes.

42 ENGINEERING↗
DOE OSTI2022

Basic Energy Sciences Roundtable: Foundational Science for Carbon Dioxide Removal Technologies (Brochure)

Basic research to identify and understand the fundamental principles governing carbon dioxide removal processes of capture, conversion, and storage is essential for achieving zero carbon emissions by 2050. In March 2022, the Office of Basic Energy Sciences (BES)—in coordination with the US Department of Energy (DOE) technology Offices of Energy Efficiency and Renewable Energy, Fossil Energy and Carbon Management, and Nuclear Energy—held a roundtable titled, “Foundational Science for Carbon Dioxide Removal Technologies,” to discuss the scientific and technical barriers for CO 2 capture, conversion, and storage. Five priority research opportunities were identified to address these scientific and technical challenges and accelerate progress toward the realization of zero carbon emissions. The PROs are as follows: 1) Master Interfacial Processes of CO2 Transport and Reactivity Across Multiple Length and Time Scales; 2) Create Materials that Simultaneously Exhibit Multiple Properties for CO 2 Capture and Release or Conversion; 3) Discover Unconventional Pathways for Energy-Efficient CO 2 Capture, Release, and Conversion; 4) Control Multiphase Interactions Required for CO 2 Conversion into Minerals and Materials; and 5) Achieve Predictive Understanding of Coupled Processes in Complex Subsurface Geologic Systems for Secure Carbon Storage.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Aerosol-Cloud Interactions From Aviation Soot Emissions

Current models estimate global aviation contributes approximately 5% to the total anthropogenic climate forcing, with aerosol-cloud interactions having the greatest effect. However, radiative forcing estimates from aviation aerosol-cloud interactions remain undetermined. There is an expected significant increase in aircraft emissions with aviation demand expected to rise by over 4% per year. Soot may play an important role in the ice nucleation of aircraft-induced cirrus formation due to a high emission rate, but the ice nucleating properties are poorly constrained. Understanding the microphysical processes leading to atmospheric ice crystal formation is crucial for the reliable parameterization of aerosol-cloud interactions in climate models due to their impact on precipitation and cloud radiative properties. Ice nucleation of aircraft-emitted soot is potentially affected by particle morphology with condensation of supercooled water occurring in pores followed by ice nucleation. However, soot has heterogeneous properties and undergoes atmospheric aging and oxidation that could change surface properties and contribute to complex ice nucleation processes. Further, this review synthesizes current knowledge of ice nucleation catalyzed by aviation in the cirrus regime and its effects on global radiative forcing. Further research is required to determine the ice nucleation and microphysical processes of cirrus cloud formation from aviation emissions in both controlled laboratory and field investigations to inform models for more accurate climate predictions and to provide efficient mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Effect of CMAS viscosity on the infiltration depth in thermal barrier coatings of different microstructures

Calcium magnesium aluminum silicate (CMAS) is one of the leading concerns for the gas turbine industry. The effects of CMAS viscosity and the coating microstructure on CMAS infiltration depth were explored by conducting a time dependent interaction study. Three CMAS compositions were used from literature, and their viscosities predicted through FactSage viscosity module were drastically different. The interaction was carried out on three different TBCs synthesized using the solution precursor plasma spray process (SPPS): two of the TBCs were made of yttrium aluminum garnet (YAG) having different microstructures that promote different modes of CMAS infiltration, and one TBC was made of gadolinium zirconate (GZO). All samples had stress relieving vertical cracks and different intensities of horizontally banded porosity, (inter pass boundaries IPBs). A concentration of 100 mg/cm 2 of CMAS was applied on the TBCs which were then subjected to a 5-minute interaction at 1300 °C. Samples were analyzed using scanning electron microscopy (SEM), electron dispersive X-ray spectroscopy (EDXS), and transmission electron microscopy (TEM). Low viscosity CMAS readily penetrated the TBCs while more viscous CMAS showed less penetration. The depth of CMAS infiltration depended on the coating microstructure. In the YAG with IPBs, the CMAS spread horizontally in the IPBs before infiltrating deeper, resulting in reduced infiltration depth compared to other samples in spite of having wider vertical cracks. TEM and EDXS analysis were performed to investigate the phases present in the CMAS-TBC interaction region in YAG. Two regions were chosen, the top TBC surface in direct contact with the sea of CMAS, and the region at the CMAS penetration ended within the coating. Finally, the results showed that no secondary phases like apatite were observed in YAG, thus it can be concluded that the arrest of CMAS happened solely because of CMAS viscosity and the short infiltration time.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Membrane Contactor Enabling Energy-Efficient CO 2 Capture from Point Sources with Deep Eutectic Solvents

We demonstrate a scalable and energy-efficient hollow fiber membrane contactor (HFMC)-based process using a green solvent for CO 2 capture. This process uses a deep eutectic solvent (DES) in an HFMC to provide close interfacial interactions and contact between the DES and CO 2 . This approach overcomes disadvantages associated with direct absorption in DES and could potentially be applied to a variety of solvent-based CO 2 capture methods. Commercial low-cost polymer hollow fiber membranes (e.g., microporous polypropylene) were evaluated for CO 2 capture with reline, a prototypical DES. Single-gas measurements showed that the DES-based polypropylene HFMC can capture and separate CO 2 while rejecting N2. From a mixed gas containing 50 mol % N 2 and 50 mol % CO ν , the DES-based HFMC separated CO 2 with a purity of 96.9 mol %. The effect of several process parameters including solvent flow rate, pressure, and temperature on the CO 2 separation performance was studied. The flux of the recovered CO 2 was 67.43 mmole/m 2 /h at a feed pressure of 4 bar. In situ Fourier transform infrared (FTIR) measurements combined with density functional theory (DFT)-based molecular dynamics simulations revealed that reline absorbs CO 2 by physical absorption without forming a new chemical compound, and CO 2 separation by reline occurs via the pressure swing mechanism. This research provides fundamental insights about physical solvent-based separation processes and a pathway toward practical deployment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗
DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cryogenic Detector Development for SuperCDMS

The dark matter (DM) problem is currently one of the most pressing issues facing physics. This thesis presents some of my work and contributions to the detectors employed by the Super Cryogenic Dark Matter Search (SuperCDMS), one of the many experiments currently investigating DM. First, we present an overview of astrophysical and cosmological observations to give insight into our current understanding of DM and its role in the universe. Some potential particle DM candidates are also discussed. Then we describe the SuperCDMS experiment and relevant detector technologies. We go into particular detail in discussing the phonon sensors, deriving the relationships that define their fundamental working principles and describing their practical deployment. We also discuss the main noise contributions to the phonon sensors which can limit experimental sensitivity. We then present some work related to reconstruction of event position in the detectors, including new analysis techniques and a n ovel cryogenic calibration source mover we have developed and tested. We also present tests of improving experimental scalability by increasing individual detector masses using the largest-diameter cryogenic Si detectors yet operated. We present first experimental results from the novel use of $(n,\gamma)$ processes to calibrate the low energy nuclear recoil energy scale. This work is essential to understand how DM-nuclear interactions will manifest in semiconductor detectors. We also take a short look at the newest, most sensitive detectors currently operated by SuperCDMS and discuss how they are allowing new insights into critical physics processes in all SuperCDMS detectors. Finally, we demonstrate how some of the various improvements discussed in this work can improve the experimental reach of the next generation of SuperCDMS at SNOLAB.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Lifetime of actin-dependent protein nanoclusters

Protein nanoclusters (PNCs) are dynamic collections of a few proteins that spatially organize in nanometer-length clusters. PNCs are one of the principal forms of spatial organization of membrane proteins, and they have been shown or hypothesized to be important in various cellular processes, including cell signaling. PNCs show remarkable diversity in size, shape, and lifetime. In particular, the lifetime of PNCs can vary over a wide range of timescales. The diversity in size and shape can be explained by the interaction of the clustering proteins with the actin cytoskeleton or the lipid membrane, but very little is known about the processes that determine the lifetime of the nanoclusters. In this paper, using mathematical modeling of the cluster dynamics, we model the biophysical processes that determine the lifetime of actin-dependent PNCs. In particular, we investigated the role of actin aster fragmentation, which had been suggested to be a key determinant of the PNC lifetime, and we found that it is important only for a small class of PNCs. A simple extension of our model allowed us to investigate the kinetics of protein-ligand interaction near PNCs. We found an anomalous increase in the lifetime of ligands near PNCs, which agrees remarkably well with experimental data on RAS-RAF kinetics. In particular, analysis of the RAS-RAF data through our model provides falsifiable predictions and novel hypotheses that will not only shed light on the role of RAS-RAF kinetics in various cancers, but also will be useful in studying membrane protein clustering in general.

59 BASIC BIOLOGICAL SCIENCES↗