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At least 19 records

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗

Redox and volatility of Tc(CO)3 + compounds in waste glass melting

The behavior of non-pertechnetate (Tc(I)) species was studied by preparing three portions of dried low-activity waste-glass simulated feed, combining it with either the [fac-Tc(CO) (OH)] “tetramer,” the [fac-Tc(CO) (OH)(H O) ] “monohydroxo,” or the [fac-Tc(CO) Cl ] “trichloro,” and then heating samples to 600, 800, and 1000 °C. For the feeds and the heat-treated samples, Tc concentrations were measured by liquid scintillation counting (LSC) after NaOH and HNO fusion, and the results were used to determine the Tc volatility. For unheated samples and samples heated to 600 °C, the speciation of Tc was measured by X-ray absorption near-edge structure (XANES) analysis, while partitioning of Tc in the glass-forming melt was determined by leaching the samples in water and measuring the Tc concentration of the leachate. The current results are discussed in connection with previously reported data for Tc(VII) and Tc(IV) species to rationalize the potential mechanism on how different speciation of Tc affect its retention in glass. 3 4 3 2 2 3 3 3 2-

Luksic, SA↗

Covariation of Slab Tracers, Volatiles, and Oxidation During Subduction Initiation

Abstract Subduction‐related lavas have higher Fe 3+ /∑Fe than midocean ridge basalts (MORB). Hypotheses for this offset include imprint from subducting slabs and differentiation in thickened crust. These ideas are readily tested through examination of the time‐dependent evolution of slab‐derived signatures, thickening crust of the overriding plate, and evolving redox during subduction initiation. Here, we present Fe 3+ /ΣFe and volatile element abundances of volcanic glasses recovered from International Ocean Discovery Program (IODP) Expedition 352 to the Izu‐Bonin‐Mariana (IBM) forearc. The samples include forearc basalts (FAB) that are stratigraphically overlain by low‐ and high‐silica boninite lavas. The FAB glasses have 0.18–0.85 wt% H 2 O, 75–233 ppm CO 2 , S contents controlled by saturation with a sulfide phase (602–1,386 ppm), Ba/La from 3.9‐10, and Fe 3+ /ΣFe ratios from 0.136 to 0.177. These compositions are similar to MORB and suggest that decompression melting of dry and reduced mantle dominates the earliest stages of subduction initiation. Low‐ and high‐silica boninite glasses have 1.51–3.19 wt% H 2 O, CO 2 below detection, S contents below those required for sulfide saturation (5–235 ppm), Ba/La from 11 to 29, and Fe 3+ /∑Fe from 0.181 to 0.225. The compositions are broadly similar to modern arc lavas in the IBM arc. These data demonstrate that the establishment of fluid‐fluxed melting of the mantle, which occurs in just 0.6–1.2 my after subduction initiation, is synchronous with the production of oxidized, mantle‐derived magmas. The coherence of high Fe 3+ /∑Fe and Ba/La ratios with high H 2 O contents in Expedition 352 glasses and the modern IBM arc rocks strongly links the production of oxidized arc magmas to signatures of slab dehydration.

Brounce, Maryjo↗

Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events—Concept of event-based driving volatility

The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. Here, this study focuses on the component of “driving volatility matrix” related to specific normal and safety-critical events, named “event-based volatility.” The research issue is characterizing volatility in instantaneous driving decisions in the longitudinal and lateral directions, and how it varies across drivers involved in normal driving, crash, and/or near-crash events. To explore the issue, a rigorous quasi-experimental study design is adopted to help compare driving behaviors in normal vs unsafe outcomes. Using a unique real-world naturalistic driving database from the 2nd Strategic Highway Research Program (SHRP), a test set of 9593 driving events featuring 2.2 million temporal samples of real-world driving are analyzed. This study features a plethora of kinematic sensors, video, and radar spatiotemporal data about vehicle movement and therefore offers the opportunity to initiate such exploration. By using information related to longitudinal and lateral accelerations and vehicular jerk, 24 different aggregate and segmented measures of driving volatility are proposed that captures variations in extreme instantaneous driving decisions. In doing so, careful attention is given to the issue of intentional vs. unintentional volatility. The volatility indices, as leading indicators of near-crash and crash events, are then linked with safety critical events, crash propensity, and other event specific explanatory variables. Owing to the presence of unobserved heterogeneity and omitted variable bias, fixed- and random-parameter discrete choice models are developed that relate crash propensity to unintentional driving volatility and other factors. Statistically significant evidence is found that driver volatilities in near-crash and crash events are significantly greater than volatility in normal driving events. After controlling for traffic, roadway, and unobserved factors, the results suggest that greater intentional volatility increases the likelihood of both crash and near-crash events. A one-unit increase in intentional volatility is associated with positive vehicular jerk in longitudinal direction increases the chance of crash and near-crash outcome by 15.79 and 12.52 percentage points, respectively. Importantly, intentional volatility in positive vehicular jerk in lateral direction has more negative consequences than intentional volatility in positive vehicular jerk in longitudinal direction. Compared to acceleration/deceleration, vehicular jerk can better characterize the volatility in microscopic instantaneous driving decisions prior to involvement in safety critical events. Finally, the magnitudes of correlations exhibit significant heterogeneity, and that accounting for the heterogeneous effects in the modeling framework can provide more reliable and accurate results. The study demonstrates the value of quasi-experimental study design and big data analytics for understanding extreme driving behaviors in safe vs. unsafe driving outcomes.

33 ADVANCED PROPULSION SYSTEMS↗

Volatility and Viscosity Are Correlated in Terpene Secondary Organic Aerosol Formed in a Flow Reactor

Secondary organic aerosol (SOA) is a complex mixture of largely unspeciated compounds. Volatility and viscosity of the bulk organic aerosol influence new particle formation, processing, and lifetime in the atmosphere. Relationships between these properties are well-defined for pure compounds, but currently unavailable for bulk organic aerosol. In this survey study, we characterized SOA formed from a range of biogenic precursors and conditions in an oxidation flow reactor for volatility (thermodenuder), viscosity (dimer coagulation, isolation, and coalescence), and oxidation state (aerosol chemical speciation monitor). We find linear trends in log-linear and log-log plots of single-parameter representations of volatility and viscosity, with higher condensed phase fractions of extremely low and low volatility material associated with increased viscosity (R=0.69). Per this relationship, a 10% increase in the contribution of these fractions (i.e., lower volatility) results in an increase in viscosity of approximately 200%. The viscosity (at 30°C) of SOA fell between $6.2 × 10^5$ to $8.0 × 10^8$ Pa s, and thus in the semi-solid range. SOA oxidation state ranged from -1.0 and 0.1, and was weakly anti-correlated with volatility (but not viscosity). We found larger SOA mass loadings generally associated with increased volatility and decreased viscosity. Overall, the results of this preliminary study are consistent with “molecular corridor”-style frameworks employing molecular mass and volatility to estimate viscosity to bulk real-world SOA.

54 ENVIRONMENTAL SCIENCES↗

Volatile Element Evidence of Local MORB Mantle Heterogeneity Beneath the Southwest Indian Ridge, 48°–51°E

Abstract The mantle source beneath the Southwest Indian Ridge (SWIR) reflects a complex history of contamination. Magmatic volatile contents are vital tracers of these kinds of heterogeneities, which may fractionate otherwise constant volatile/non‐volatile elemental ratios, such as the H 2 O/Ce ratio. Although several studies have recently used trace element and isotopic data to address mantle source heterogeneity and magmatic processes at SWIR 48°–51°E region, volatile element constraints provide a valuable test of models for the origins of mantle heterogeneities in this region. Here, we present new data for nine rare basaltic glass samples from the 48°–51°E region, which enable careful assessment of the effects of primary versus secondary processes on the glass volatile contents. These samples are strongly affected by variable extents of carbon degassing, and shallow assimilation of Cl‐rich fluid, but also reveal consistently high H 2 O/Ce ratios (458.8 ± 14.9), among the highest in MORBs, that cannot be explained by late‐stage secondary processes, crustal assimilation, or simple melting of peridotite mantle at variable depths. Instead, the high H 2 O/Ce ratios are features of the mantle source composition. The 48°–51°E region is notably more depleted in highly incompatible trace elements relative to other regions of the SWIR, although this depletion is not apparent in H 2 O, which is similarly abundant throughout the SWIR. We link the high H 2 O/Ce ratios in these glasses with other trace element characteristics diagnostic of subduction and fluid addition, suggesting that the mantle source reflects signatures of a refractory mantle residue that previously melted within a subduction zone.

Wang, Wei↗

Nanoscale Imaging and Control of Volatile and Non-Volatile Resistive Switching in VO 2

Control of the metal-insulator phase transition is vital for emerging neuromorphic and memristive technologies. The ability to alter the electrically driven transition between volatile and non-volatile states is particularly important for quantum-materials-based emulation of neurons and synapses. The major challenge of this implementation is to understand and control the nanoscale mechanisms behind these two fundamental switching modalities. In this study, in situ X-ray nanoimaging is used to follow the evolution of the nanostructure and disorder in the archetypal Mott insulator VO 2 during an electrically driven transition. Our findings demonstrate selective and reversible stabilization of either the insulating or metallic phases achieved by manipulating the defect concentration. This mechanism enables us to alter the local switching response between volatile and persistent regimes and demonstrates a new possibility for nanoscale control of the resistive switching in Mott materials.

36 MATERIALS SCIENCE↗

A Simple Criterion for Feasibility of Heat Integration between Distillation Streams Based on Relative Volatilities

In a multicomponent distillation configuration, there are numerous sources and sinks of heat, and a potential way to reduce the heat duty requirement is to perform heat integration. Unfortunately, an algorithmic search of the optimal heat integration opportunities is intractable when the required temperatures of intermediate streams are computed via complex models. Instead, in this work, we introduce pressure-scaled pseudo relative volatility, a new metric to compare stream temperatures. Here, we justify the use of pseudo relative volatility by proving that this variable is a monotonically increasing function of the liquid fraction in a saturated mixture stream. Using this metric, we derive a shortcut criterion to check the feasibility of various heat integration opportunities, such as thermal coupling via heat transfer (TCH). The advantage of this approach is that it circumvents the need for explicit temperatures and instead relies on composition, component relative volatilities, and pressure—quantities that are readily available in shortcut models for optimization of distillation configurations. Leveraging this fact, we propose a new optimization framework that identifies feasible TCHs that we consider within the formulation while minimizing the total heat duty of a distillation configuration. We demonstrate, on a few examples, that our formulation can identify heat duty efficient configurations, some of which are multieffect configurations. Using this methodology, we discover configurations that are not only simpler than the fully thermally coupled (FTC) configuration but also have a much lower heat duty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

Development of an in situ dual-channel thermal desorption gas chromatography instrument for consistent quantification of volatile, intermediate-volatility and semivolatile organic compounds

Abstract. Aerosols are a source of great uncertainty in radiative forcing predictions and have poorly understood health impacts. Most aerosol mass is formed in the atmosphere from reactive gas-phase organic precursors, forming secondary organic aerosol (SOA). Semivolatile organic compounds (SVOCs) (effective saturation concentration, C*, of 10−1–103 µg m−3) comprise a large fraction of organic aerosol, while intermediate-volatility organic compounds (IVOCs) (C* of 103–106 µg m−3) and volatile organic compounds (VOCs) (C* ≥ 106 µg m−3) are gas-phase precursors to SOA and ozone. The Comprehensive Thermal Desorption Aerosol Gas Chromatograph (cTAG) is the first single instrument simultaneously quantitative for a broad range of compound-specific VOCs, IVOCs and SVOCs. cTAG is a two-channel instrument which measures concentrations of C5–C16 alkane-equivalent-volatility VOCs and IVOCs on one channel and C14–C32 SVOCs on the other coupled to a single high-resolution time-of-flight mass spectrometer, achieving consistent quantification across 15 orders of magnitude of vapor pressure. cTAG obtains concentrations hourly and gas–particle partitioning for SVOCs every other hour, enabling observation of the evolution of these species through oxidation and partitioning into the particle phase. Online derivatization for the SVOC channel enables detection of more polar and oxidized species. In this work we present design details and data evaluating key parameters of instrument performance such as I/VOC collector design optimization, linearity and reproducibility of calibration curves obtained using a custom liquid evaporation system for I/VOCs and the effect of an ozone removal filter on instrument performance. Example timelines of precursors with secondary products are shown, and analysis of a subset of compounds detectable by cTAG demonstrates some of the analytical possibilities with this instrument.

54 ENVIRONMENTAL SCIENCES↗

Volatile Organic Compounds in Bankhead National Forest (AMF3). August to September, 2025

The formation of atmospheric aerosols through the transformation of volatile organic compounds (VOCs) is a fundamental process in aerosol-climate interactions, as these particles serve as cloud condensation nuclei and ultimately influence Earth’s radiative balance. However, there remains a critical need to quantify the effects of multiple coexisting VOC precursors on aerosol formation beyond the limitations of laboratory-scale studies. This research aims to advance the mechanistic understanding of secondary organic aerosol formation in the southeastern United States by investigating interactions among coexisting VOC precursors observed at the third ARM Mobile Facility located in the Bankhead National Forest. The dataset was generated from the deployment of Oak Ridge National Laboratory’s PTR-TOF 6000 X2 Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS) for the real-time, continuous monitoring of VOCs from August 21 to September 15, 2025. To minimize sampling artifacts and compound losses, the PTR-ToF-MS inlet was connected to the cabin flow line by replacing the existing Tygon tubing with 1/2-inch outer diameter perfluoroalkoxy (PFA) tubing. The instrument operated on an hourly measurement cycle consisting of 8 minutes of zero-air measurements followed by 52 minutes of ambient air sampling, with a temporal resolution of 10 seconds. The dataset includes concentrations, reported in ppb, of methanol, acetone, acetonitrile, isoprene, methyl vinyl ketone and methacrolein (MVK + MACR), monoterpenes, benzene, toluene, and catechol.

Atmospheric concentration of volatile organic comp↗

Carbon-based volatile and non-volatile memristors

An ultrathin, carbon-based memristor with a moiré superlattice potential shows prominent ferroelectric resistance switching. The memristor includes a bilayer material, such as Bernal-stacked bilayer graphene, encapsulated between two layers of a layered material, such as hexagonal boron nitride. At least one of the encapsulating layers is rotationally aligned with the bilayer to create the moiré superlattice potential. The memristor exhibits ultrafast and robust resistance switching between multiple resistance states at high temperatures. The memristor, which may be volatile or nonvolatile, may be suitable for neuromorphic computing.

Jarillo-Herrero, Pablo↗

Automating methods for estimating metabolite volatility

The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc , we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

59 BASIC BIOLOGICAL SCIENCES↗

Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions

Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

54 ENVIRONMENTAL SCIENCES↗

Exploring Intentional Driving Volatility in Naturalistic Driving Environment Prior to Involvement in Unsafe Events

The sequence of instantaneous driving decisions and its variations prior to involvement in safety critical events, defined as event-based volatility, can be a leading indicator of safety. The research issue is characterizing volatility in instantaneous driving decisions in longitudinal and lateral directions, and how it varies across drivers involved in normal driving, crash, and near-crash events. A rigorous quasi-experimental study design is adopted to help compare driving behaviors in normal vs unsafe outcomes. Using a unique real-world naturalistic driving database from the SHRP 2, a test set of 9,593 driving events featuring 2.2 million temporal samples of real-world driving are analyzed. Twenty-four aggregate and segmented driving volatility measures based on acceleration and vehicular jerk are proposed, capturing variations in intentional and unintentional extreme instantaneous driving decisions. Given the possibility of unobserved heterogeneity/omitted variable bias, fixed- and random-parameter discrete choice models are developed that relate crash propensity to driving volatility and other factors. Statistically significant evidence is found that driver volatilities in near-crash and crash events are significantly greater than volatility in normal driving events. After controlling for traffic, roadway, and unobserved factors, the results suggest that greater intentional volatility increases the likelihood of both crash and near-crash events. Importantly, intentional volatility in longitudinal negative jerk has more negative consequences than intentional volatility in positive vehicular jerk. Compared to acceleration/deceleration, vehicular jerk can better characterize the volatility in microscopic driving decisions. The study demonstrates the value of big data analytics for understanding extreme driving behaviors in safe vs. unsafe driving outcomes.

Wali, Behram↗