Results for “Modal Analysis” — Page 73

NASA NTRS1987

Decoupled dynamic analysis of combined systems by iterative determination of interface accelerations

A dynamic analysis technique is presented that can be used to determine the response of a discrete model of a large linear structural system composed of multiple substructures. The technique circumvents the costly computation of the modal characteristics of the combined system. This is accomplished by relying on a predictor-corrector scheme to converge iteratively to the interface accelerations of the combined system, while the equations of motions of the individual structures are integrated separately. In this regard, the temporal slopes of the interface accelerations (jerks) are computed at each time point of integration to predict the interface accelerations at the next time point. The proposed technique is exemplified by conducting a Space Shuttle landing loads analysis; the obtained numerical data demonstrate its reliability and efficiency.

Spanos, P. D.↗

DOE OSTI2014

TH-A-16A-01: Image Quality for the Radiation Oncology Physicist: Review of the Fundamentals and Implementation

The expansion and integration of diagnostic imaging technologies such as On Board Imaging (OBI) and Cone Beam Computed Tomography (CBCT) into radiation oncology has required radiation oncology physicists to be responsible for and become familiar with assessing image quality. Unfortunately many radiation oncology physicists have had little or no training or experience in measuring and assessing image quality. Many physicists have turned to automated QA analysis software without having a fundamental understanding of image quality measures. This session will review the basic image quality measures of imaging technologies used in the radiation oncology clinic, such as low contrast resolution, high contrast resolution, uniformity, noise, and contrast scale, and how to measure and assess them in a meaningful way. Additionally a discussion of the implementation of an image quality assurance program in compliance with Task Group recommendations will be presented along with the advantages and disadvantages of automated analysis methods. Learning Objectives: Review and understanding of the fundamentals of image quality. Review and understanding of the basic image quality measures of imaging modalities used in the radiation oncology clinic. Understand how to implement an image quality assurance program and to assess basic image quality measures in a meaningful way.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

WE-FG-202-03: Quantitative CT-Based Analysis to Assess Lung Injury Following Proton Radiotherapy

Purpose: Relative to photon alternatives, the increased dose-conformity associated with proton therapy is expected to reduce the extent of radiation-induced lung toxicity. However, analysis of follow-up data is yet to be published in this area. In this study we retrospectively analyzed late-phase HU changes for proton therapy cohorts of chest wall and lung patients. Methods: From our institution’s register of patients treated using double-scattered protons, all chest wall and stereotactic lung cases (treated 2011–2012 and 2008–2014 respectively) were initially considered. Follow-up CT data were accessible for 10 chest wall cases (prescribed 50.4 GyRBE in 28 fractions) and 16 lung cases (prescribed 42–50 GyRBE in 3–4 fractions). CT time-points ranged from 0.5–3.5 years post-treatment. Planning doses were recalculated using TOPAS Monte Carlo simulations and mapped onto the follow-up images using deformable registration. Excluding internal target volumes, changes in HU between each patient’s planning and follow-up CT(s) were evaluated for dose bins of 2–30 GyRBE (2 GyRBE increments). Results: Linear increases in HU per unit dose, with correlations statistically significant at the 1% level (one-sided Spearman’s rank test), were evident for all 10 chest wall cases and 14/16 lung cases. The mean changes in HU/Gy were: 1.76 (SD=0.73) for the chest wall cohort, and 1.40 (SD=0.87) for the lung cohort. The median scan times post treatment were 21 and 12 months respectively. All 26 patients developed solid consolidation (scar-like radiographic opacities) within the exposed lung(s). Conclusion: Analysis of follow-up CTs revealed statistically significant correlations in HU-change/dose for two proton cohorts (lung and chest wall). Quantitatively, the late-phase changes we report broadly match published photon data. Further analysis of such radiographic changes, particularly via matched cohort studies drawing upon consistent imaging protocols, could play an important role in elucidating inter-modality differences and provide insight into proton RBE for lung injury. Tracy Underwood gratefully acknowledges the support of the European Commission under an FP7 Marie Curie International Outgoing Fellowship for Career Development (#630064). This work was also funded under U19 grant CA 021239 (PI: Delaney).

60 APPLIED LIFE SCIENCES↗

NASA NTRS1987

Improvements to the fastex flutter analysis computer code

Modifications to the FASTEX flutter analysis computer code (UDFASTEX) are described. The objectives were to increase the problem size capacity of FASTEX, reduce run times by modification of the modal interpolation procedure, and to add new user features. All modifications to the program are operable on the VAX 11/700 series computers under the VAX operating system. Interfaces were provided to aid in the inclusion of alternate aerodynamic and flutter eigenvalue calculations. Plots can be made of the flutter velocity, display and frequency data. A preliminary capability was also developed to plot contours of unsteady pressure amplitude and phase. The relevant equations of motion, modal interpolation procedures, and control system considerations are described and software developments are summarized. Additional information documenting input instructions, procedures, and details of the plate spline algorithm is found in the appendices.

Taylor, Ronald F.↗

NASA NTRS1977

Numerical analysis of free vibrations of damped rotating structures

This paper is concerned with the efficient numerical solution of damped and undamped free vibration problems of rotating structures. While structural discretization is achieved by the finite element method, the associated eigenproblem solution is effected by a combined Sturm sequence and inverse iteration technique that enables the computation of a few required roots only without having to compute any other. For structures of complex configurations, a modal synthesis technique is also presented, which is based on appropriate combinations of eigenproblem solution of various structural components. Such numerical procedures are general in nature, which fully exploit matrix sparsity inherent in finite element discretizations, and prove to be most efficient for the vibration analysis of any damped rotating structure, such as rotating machineries, helicopter and turbine blades, spinning space stations, among others.

Gupta, K. K.↗

NASA NTRS2000

Modal Survey Test of the SOTV 2X3 Meter Off-Axis Inflatable Concentrator

NASA's Marshall Space Flight Center has had several projects involving inflatable space structures. Projects in solar thermal propulsion have had the most involvement, primarily inflatable concentrators. A flight project called Shooting Star Experiment initiated the first detailed design, analysis and testing effort involving an inflatable concentrator that supported a Fresnel lens. The lens was to concentrate the sun's rays to provide an extremely large heat transfer for an experimental solar propulsion engine. Since the conclusion of this experiment, research and development activities for solar propulsion at Marshall Space Flight Center have continued both in the solar propulsion engine technology as well as inflatable space structures. Experience gained in conducting modal survey tests of inflatable structures for the Shooting Star Experiment has been used by dynamic test engineers at Marshall Space Flight Center to conduct a modal survey test on a Solar Orbital Transfer Vehicle (SOTV) off-axis inflatable concentrator. This paper describes how both previously learned test methods and new test methods that address the unique test requirements for inflatable structures were used. Effects of the inherent nonlinear response of the inflatable concentrator on test methods and test results are noted as well. Nine analytical mode shapes were successfully correlated to test mode shapes. The paper concludes with several "lessons learned" applicable to future dynamics testing and shows how Marshall Space Flight Center has utilized traditional and new methods for modal survey testing of inflatable space structures.

Engberg, Robert C.↗

NASA NTRS1987

Power flow as a complement to statistical energy analysis and finite element analysis

Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.

Cuschieri, J. M.↗

DOE OSTI2020

Current measurements in the intermittent-contact mode of atomic force microscopy using the Fourier method: a feasibility analysis

Atomic force microscopy (AFM) is an important tool for measuring a variety of nanoscale surface properties, such as topography, viscoelasticity, electrical potential and conductivity. Some of these properties are measured using contact methods (static contact or intermittent contact), while others are measured using noncontact methods. Some properties can be measured using different approaches. Conductivity, in particular, is mapped using the contact-mode method. However, this modality can be destructive to delicate samples, since it involves continuously dragging the cantilever tip on the surface during the raster scan, while a constant tip–sample force is applied. In this paper we discuss a possible approach to develop an intermittent-contact conductive AFM mode based on Fourier analysis, whereby the measured current response consists of higher harmonics of the cantilever oscillation frequency. Such an approach may enable the characterization of soft samples with less damage than contact-mode imaging. To explore its feasibility, we derive the analytical form of the tip–sample current that would be obtained for attractive (noncontact) and repulsive (intermittent-contact) dynamic AFM characterization, and compare it with results obtained from numerical simulations. Although significant instrumentation challenges are anticipated, the modelling results are promising and suggest that Fourier-based higher-harmonics current measurement may enable the development of a reliable intermittent-contact conductive AFM method.

14 SOLAR ENERGY↗

DOE OSTI2012

Impact of Primary Gleason Grade on Risk Stratification for Gleason Score 7 Prostate Cancers

Purpose: To evaluate the primary Gleason grade (GG) in Gleason score (GS) 7 prostate cancers for risk of non-organ-confined disease with the goal of optimizing radiotherapy treatment option counseling. Methods: One thousand three hundred thirty-three patients with pathologic GS7 were identified in the Duke Prostate Center research database. Clinical factors including age, race, clinical stage, prostate-specific antigen at diagnosis, and pathologic stage were obtained. Data were stratified by prostate-specific antigen and clinical stage at diagnosis into adapted D'Amico risk groups. Univariate and multivariate analyses were performed evaluating for association of primary GG with pathologic outcome. Results: Nine hundred seventy-nine patients had primary GG3 and 354 had GG4. On univariate analyses, GG4 was associated with an increased risk of non-organ-confined disease. On multivariate analysis, GG4 was independently associated with seminal vesicle invasion (SVI) but not extracapsular extension. Patients with otherwise low-risk disease and primary GG3 had a very low risk of SVI (4%). Conclusions: Primary GG4 in GS7 cancers is associated with increased risk of SVI compared with primary GG3. Otherwise low-risk patients with GS 3+4 have a very low risk of SVI and may be candidates for prostate-only radiotherapy modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

SU-E-T-441: Gamma Passing Rates for IMRT QA and VMAT QA

Purpose: This study compares gamma passing rates for a cohort of similar intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) quality assurance (QA) plans to determine the equivalence of the patient specific QA plan delivery. The passing criterion is 90% gamma index with 3% dose difference (DD), 3mm distance-to-agreement (DTA) and a dose threshold of 10%. Methods: Gamma passing results of previously treated IMRT QA plans, delivered to Sun Nuclear MapCheck phantom, and VMAT QA plans, delivered to ScandiDos Delta4 phantom, are organized by anatomical site and treatment machine. Both Varian and Elekta machines are included. Pairs of IMRT and VMAT plans are matched based on site, machine, and PTV volume to ensure similar plan cohorts. A two-tailed t-test analysis of the data with an alpha of 0.05 determines if there exists a statistically significant difference. Power was calculated to detect a difference of 4%; all data sets were strong with above a 0.8 power. Results: The first data set consisting of 20 matched pairs of prostate plans was statistically insignificant (p-value=0.90, Power=0.99). The 14 matched pairs set of head and neck plans has a statistically significant Result (p-value=0.028, Power=0.88). The head and neck IMRT gamma indexes have a mean of 93.1% and range of 82%-100% while the VMAT gamma indexes have a mean of 96.7% and range of 92%-100%. The two combined data sets of matched plans had a statistically insignificant Result (p-value=0.073, Power=0.99). Conclusion: Overall, IMRT and VMAT have equivalent passing rates when comparing the gamma analysis using a passing criterion of 3% DD and 3mm DTA. When separated by site, prostate IMRT and VMAT plans have equivalent passing rates while head and neck plans have a statistically significant variation of passing rates. The passing rates for the two modalities are independent of delivery machine for matched PTV target volumes.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Modal parameters of space structures in 1 G and 0 G

Analytic and experimental results are presented from a study of the changes in the modal parameters of space structural test articles from one- to zero-gravity. Deployable, erectable, and rotary modules was assembled to form three one- and two-dimensional structures, in which variations in bracing wire and rotary joint preload could be introduced. The structures were modeled as if hanging from a suspension system in one gravity, and unconstrained, as if free floating in zero-gravity. The analysis is compared with ground experimental measurements, which were made on a spring-wire suspension system with a nominal plunge frequency of one Hertz, and with measurements made on the Shuttle middeck. The degree of change in linear modal parameters as well as the change in nonlinear nature of the response is examined. Trends in modal parameters are presented as a function of force amplitude, joint preload, reassembly, shipset, suspension, and ambient gravity level.

Bicos, Andrew S.↗

DOE OSTI2015

TU-G-303-00: Radiomics: Advances in the Use of Quantitative Imaging Used for Predictive Modeling

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-01: Radiomics: Quantitative Imaging in the Service of Improved Treatment Decision Making

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-02: Robust Radiomics Methods for PET and CT Imaging

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-03: Machine Learning to Improve Human Learning From Longitudinal Image Sets

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-04: Radiomics and the Coming Pan-Omics Revolution

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

NASA NTRS2009

Design and Analysis of the International X-Ray Observatory Mirror Modules

The Soft X-Ray Telescope (SXT) modules are the fundamental focusing assemblies on NASA's next major X-ray telescope mission, the International X-Ray Observatory (IXO). The preliminary design and analysis of these assemblies has been completed, addressing the major engineering challenges and leading to an understanding of the factors effecting module performance. Each of the 60 modules in the Flight Mirror Assembly (FMA) supports 200-300 densely packed 0.4 mm thick glass mirror segments in order to meet the unprecedented effective area required to achieve the scientific objectives of the mission. Detailed Finite Element Analysis (FEA), materials testing, and environmental testing have been completed to ensure the modules can be successfully launched. Resulting stress margins are positive based on detailed FEA, a large factor of safety, and a design strength determined by robust characterization of the glass properties. FEA correlates well with the results of the successful modal, vibration, and acoustic environmental tests. Deformation of the module due to on-orbit thermal conditions is also a major design driver. A preliminary thermal control system has been designed and the sensitivity of module optical performance to various thermal loads has been determined using optomechanical analysis methods developed for this unique assembly. This design and analysis furthers the goal of building a module that demonstrates the ability to meet IXO requirements, which is the current focus of the IXO FMA technology development team.

McClelland, Ryan S.↗

DOE OSTI2014

Micro-Spectroscopic Imaging and Characterization of Individually Identified Ice Nucleating Particles from a Case Field Study

The effect of anthropogenic and biogenic organic particles on atmospheric glaciation processes is poorly understood. We use an optical microscopy (OM) setup to identify the location of ice nuclei (IN) active in immersion freezing and deposition ice nucleation for temperatures of 200-273 K within a large population of particles sampled from an ambient environment. Applying multi-modal micro-spectroscopy methods we characterize the physicochemical properties of individual IN in particle populations collected in central California. Chemical composition and mixing state analysis of particle populations are performed to identify characteristic particle-type classes. All particle-types contained organic material. Particles in these samples take up water at subsaturated conditions, induce immersion freezing at subsaturated and saturated conditions above 226 K, and act as deposition IN below 226 K. The identified IN belong to the most common particle-type classes observed in the field samples: organic coated sea salt, Na-rich, and secondary and refractory carbonaceous particles. Based on these observations, we suggest that the IN are not always particles with unique chemical composition and exceptional ice nucleation propensity; rather, they are common particles in the ambient particle population. Thus, particle composition and morphology alone are insufficient to assess their potential to act as IN. The results suggest that particle-type abundance is also a crucial factor in determining the ice nucleation efficiency of specific IN types. These findings emphasize that ubiquitous organic particles can induce ice nucleation under atmospherically relevant conditions and that they may play an important role in atmospheric glaciation processes.

Environmental Molecular Sciences Laboratory↗