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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Elucidating molecular scale interactions underlying the freezing behavior of salt solutions in silica nanopores

Elucidating the influence of nanoscale confinement on the freezing behavior of salt solutions is of fundamental interest to environmental security and materials science and engineering. Specific structural information such as the coordination environment of ions in confined aqueous medium, effects on the extended hexagonal network of water molecules and their mutual non-bonding interactions in confinement are sparse in the literature along with the change in the dynamical characteristics of water in the presence of ions. To address these knowledge gaps, the current study is focused on investigating the influence of reduced dimensionality arising from nanoscale confinement on the structural evolution of salt solutions on freezing and the associated fluid–surface interactions. In this regard, operando wide-angle X-ray scattering (WAXS) measurements and classical molecular dynamics (MD) simulations are conducted with water and 0.5 M CaCl 2 , MgCl 2 and KCl solutions confined in 4 nm sized SBA-15 silica pores upon cooling from 300 K to 200 K. The freezing point of the salt solutions is depressed to 235 K which is about 10 K lower than that of confined water. The translational dynamics of confined salt solutions indicates shifts in the fragile-to-strong dynamical crossover to a lower temperature compared to pure water. The strong electrostatic attraction between the cations and the surrounding water molecules contributes to the freezing point depression in confined salt solutions. These insights unlock the molecular-scale basis and mechanisms underlying the freezing behavior of confined salt solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Tribological behaviors of nanotwinned Al alloys

Wear-induced damages cause significant materials loss each year. Al alloys are widely used by industry but usually have low wear resistance. Here, we compare the tribological behaviors of ultrafine grained Al, a nanoprecipitate hardened Al 7075 alloy and nanotwinned Al–Ni alloys using the nanoscratch. The nanotwinned Al–Ni alloys exhibit lower coefficient of friction and much greater wear resistance than the Al and Al 7075 alloys. Additionally, the enhanced wear properties of Al–Ni alloys arise from their high strength and the evolution of nanotwinned microstructures into gradient nanograins during wear. These findings on fundamental wear mechanisms in nanotwinned alloys may advance the discovery of wear-resistant metallic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spatiotemporal Reaction Dynamics Control in Two‐Photon Polymerization for Enhancing Writing Characteristics

Since 2001, 3D microfabrication based on two‐photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high‐energy physics. The in‐volume fabrication capability due to the threshold behavior of two‐photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in‐volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, a comprehensive study is performed on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, photothermal effect, microscale mechanics, and voxel stacking process. Based on the study, a nonsequential fabrication method is established to simultaneously improve key writing characteristics of TPP and realize sharp features, high speeds, large overhang structure, and smooth surfaces. The method established in this work can be applied to improve the performance of functional devices for various fields.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Layer-by-Layer Freezing of Nanoconfined Water

Abstract Nanoconfined water plays a pivotal role in a vast number of fields ranging from biological and materials sciences to catalysis, nanofluidics and geochemistry. Here, we report the freezing and melting behavior of water (D 2 O) nanoconfined in architected silica-based matrices including Vycor glass and mesoporous silica SBA-15 and SBA-16 with pore diameters ranging between 4–15 nm, which are investigated using differential scanning calorimetry and 2 H nuclear magnetic resonance spectroscopy. The results provide compelling evidence that the extreme dynamical heterogeneity of water molecules is preserved over distances as small as a few angstroms. Solidification progresses in a layer-by-layer fashion with a coexistence of liquid-like and solid-like dynamical fraction at all temperatures during the transition process. The previously reported fragile-to-strong dynamic transition in nanoconfined water is argued to be a direct consequence of the layer-by-layer solidification.

42 ENGINEERING↗
DOE OSTI2021

Magnetoelastic coupling and spin contributions to entropy and thermal transport in biferroic yttrium orthochromite

Direct engineering of material properties through exploitation of spin, phonon, and charge-coupled degrees of freedom is an active area of development in materials science. However, the relative contribution of the competing orders to controlling the desired behavior is challenging to decipher. In particular, the independent role of phonons, magnons, and electrons, quasiparticle coupling, and relative contributions to the phase transition free energy largely remain unexplored, especially for magnetic phase transitions. Here, we study the lattice and magnetic dynamics of biferroic yttrium orthochromite using Raman, infrared, and inelastic neutron spectroscopy techniques, supporting our experimental results with first-principles lattice dynamics and spin-wave simulations across the antiferromagnetic transition at T N ~ 138 K. Spectroscopy data and simulations together with the heat capacity (C p ) measurements, allow us to quantify individual entropic contributions from phonons (0.01 ± 0.01k B atom -1 ), dilational (0.03 ± 0.01k B atom -1 ), and magnons (0.11 ± 0.01k B atom -1 ) across TN. High-resolution phonon measurements conducted in a magnetic field show that anomalous T-dependence of phonon energies across TN originates from magnetoelastic coupling. Additionally, phonon scattering is primarily governed by the phonon–phonon coupling, with little contribution from magnon–phonon coupling, short-range spin correlations, or magnetostriction effects; a conclusion further supported by our thermal conductivity measurements conducted up to 14 T, and phenomenological modeling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections

Abstract In many fields of science and engineering, we frequently encounter experiments or simulations datasets that describe the behavior of complex systems and uncovering human interpretable patterns between their inputs and outputs via exploratory data analysis is essential for building intuition and facilitating discovery. Often, we resort to 2D embeddings for examining these high-dimensional relationships (e.g. dimensionality reduction). However, most existing embedding methods treat the dimensions as coordinates for samples in a high-dimensional space, which fail to capture the potential functional relationships, and the few methods that do take function into consideration either only focus on linear patterns or produce non-linear embeddings that are hard to interpret. To address these challenges, we proposed function preserving projections (FPP), which construct 2D linear embeddings optimized to reveal interpretable yet potentially non-linear patterns between the domain and the range of a high-dimensional function. The intuition here is that humans are good at understanding potentially non-linear patterns in 2D but unable to interpret non-linear mapping from high-dimensional space to 2D. Therefore, we should restrict the projection to linear but not the pattern we are seeking. Using FPP on real-world datasets, one can obtain fundamentally new insights about high-dimensional relationships in extremely large datasets that could not be processed with existing dimension reduction methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Guide to Making XPS Measurements on Nanoparticles

This guide briefly summarizes issues and considerations important for the use of X-ray Photoelectron Spectroscopy (XPS) for characterizing nanoparticles, which are important in many areas of science and technology. Because the surfaces play a major role in determining nanoparticle behaviors, XPS is an increasingly useful tool for understanding their properties, including addressing variations and non-reproducibility issues associated with these materials. The unusual physical and chemical behaviors of these particles must be considered in preparing and characterizing these materials. This guide is one of a series intended to highlight best practices in the use of XPS.

Baer, Donald R.↗
DOE OSTI2026

The emergent photophysics and photochemistry of molecular polaritons: a theoretical and computational investigation (Final Technical Report)

When molecules are placed between closely spaced mirrors, they interact strongly with the photons that are trapped between them, generating new quantum states which are no longer exclusively material nor photonic alone, but rather, coherent superpositions of both. These hybrid states are known as molecular polaritons, given that they arise from the strong interaction between the electric field of light and the electrical polarization of the molecules. Recently, experimental advances in nano‐ and microfabrication of molecular polariton architectures have successfully demonstrated their feasibility to control the rate and outcome of a certain class of chemical reactions in condensed phases. Importantly, these reactions proceed in strongly dissipative environments such as liquid solvents and lossy mirrors that allow for photons to escape from their confinement. The purpose of this research is to formulate quantum mechanical theories and computational tools that can elucidate the origin of these intriguing phenomena and simultaneously predict capabilities that this new generation of molecular materials affords. Attention is placed on harnessing polaritons to carry out photophysics and photochemistry that challenge currently existing paradigms, such as the optimization of energy conversion processes in organic solar cell or light‐emitting devices, or unconventional phenomena such as long‐range excitation energy transfer, remote control of chemical reactions, and a new quantum mechanical regime of chemical reactivity due to wavefunction overlaps amongst a large number of molecular polaritons (Bose condensation). This research explores a frontier of Chemistry and Physics where electrons, vibrations, and photons interact strongly with each other to generate emergent behavior that can be creatively exploited to address contemporary challenges in Basic Energy Sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Superconducting Quantum Metamaterials from Convergence of Soft and Hard Condensed Matter Science

Superconducting quantum metamaterials are expected to exhibit a variety of novel properties, but have been a major challenge to prepare as a result of the lack of appropriate synthetic routes to high-quality materials. Here, the discovery of synthesis routes to block copolymer (BCP) self-assembly-directed niobium nitrides and carbonitrides is described. The resulting materials exhibit unusual structure retention even at temperatures as high as 1000 °C and resulting critical temperature, T c , values comparable to their bulk analogues. Applying the concepts of soft matter self-assembly, it is demonstrated that a series of four different BCP-directed mesostructured superconductors are accessible from a single triblock terpolymer. Resulting materials display a mesostructure-dependent T c without substantial variation of the XRDmeasured lattice parameters. Lastly, field-dependent magnetization measurements of a sample with double-gyroid morphology show abrupt jumps comparable in overall behavior to flux avalanches. Results suggest a fruitful convergence of soft and hard condensed matter science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tonal Emergence: An agent-based model of tonal coordination

Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these empirical findings have yet to be cached out in a working computational model. The present work fills this gap by presenting TonalEmergence, an idealized agent-based model of improvised musical coordination. TonalEmergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner’s previous notes. Here, the model replicates an interesting empirical result from a previous study of professional jazz pianists: feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by (i) a tendency to strive toward consonance, (ii) stochasticity, and (iii) a limited memory for previously played notes. TonalEmergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The phylogenetic roots of addiction: compulsive drug seeking, natural and drug-sensitive reward, and the acquisition of learned habits

Our rational faculties permit us humans to maximize the utility of our actions. We perform a fundamental type of cost-benefit analysis in which we frame a problem, assign values to the different paths, and then choose from among a set of available options, the course that promises the most favorable outcome. So why then does addiction appear to be so impervious to the associated costs, so unaffected by undesired consequences, and ultimately so resistant to cognitive oversight? The answer may likely be found in the fact that the drivers for compulsive drug seeking and drug taking are located in affective brain circuits, circuits that are structured and patterned by learning with repeated activation. These deep processes exhibit significant resistance to control by our cognitive faculties. The general consensus is that addiction arises from mechanisms that overvalue the magnitude of reward, discount the associated risks, and thereby bias individuals towards compulsive pursuit of addictive drugs. Behavioral disruption and dependence appear to arise at the intersection of a number of connected but separate phenomena: expectations for the occurrence of specific events, behaviors that seek encounters with them, the ability to notice and learn nonrandom, co-occurring conditions, the prediction and valuation of consequences, the forming of enduring memories, and the drivers of focused behavior through compulsion, habits, and acquired routines. It is important to recognize that each one of these individual faculties are present and well developed across the entire phylogenetic tree of bilateral metazoans. The goal of this special volume is dedicated to exploring the degree to which inherent elements can account for addiction and addiction-associated phenomena. In much of the literature on addiction, the underlying processes are often viewed as distinctly mammalian, arising, in part, from the strong cognitive capacities of this taxon. Some phenomena may even be regarded to exist only in primates, or even solely in humans. This supposition arises from the fact that studies are conducted almost exclusively in mammals and primates, while evolutionary antecedents of the behavior are rarely considered. A more comprehensive perspective that examines drug reward and reinforcement in a wider range of organisms demonstrates that many of the component traits are actually well developed across the greater metazoan lineage, and they may well predate the emergence of a mammalian clade by a wide margin. The collection of papers assembled here supports the notion that the capacity to associate cues and quences has not arisen in mammals de novo. Rather, the neural mechanisms for detecting contingencies and for predicting future outcomes are very deeply rooted across broad phylogenetic divisions. Our understanding of an ability to associate paired events has been enriched by work in invertebrate preparations in both classical and operant conditioning scenarios [Cook and Carew, 1986, 1989a, 1989b]. The ability to learn allows us to connect cues and behavioral actions to their associated consequences. Pavlovian conditioning enriches surrounding cues with predictive value. Outcomes with positive valence generate appetitive responses and approach to the associated cues, while those perceived as aversive bring cue avoidance and withdrawal. Humans are not the only life forms capable of such short- and long-term modulations of behavior

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Applying molecular dynamics simulations to the study of micro cold spray of yttria

Micro cold spray (MCS) is a novel manufacturing process with proven success depositing dense, thick films of technical ceramics without the need for elevated processing temperatures or chemical precursors. The process transforms a loose sub-micrometer powder into an adherent film with mechanical properties approaching that of the bulk material through a phenomenon known as room temperature impact consolidation. While this phenomenon has been demonstrated for a wide variety of ceramic materials and film substrates, yttria stands out as a material that is both well-characterized in experiments and of significant interest for industrial applications due to its excellent refractory properties. This dissertation seeks to investigate the fundamental mechanisms that enable room temperature impact consolidation by using molecular dynamics (MD) simulations of yttria particle impacts and characterizing the deformation behavior of the system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructure, compression properties, and oxidation behavior of Hf-25Ta-5Me alloys (Me is Mo, Nb, W, 0.5Mo + 0.5 W, Cr, or Zr)

Hf–Ta based alloys have recently been investigated as potential candidates for high-temperature structural applications. While most attentions have been given to the properties above ~1200 °C where the alloys are mainly single-phase BCC structures and have excellent oxidation performance due to formation of super-oxides, structural properties at lower temperatures are equally important for applications in which an alloy may experience a range of temperatures. In the present work, microstructure, phase composition, mechanical properties and oxidation behavior of six Hf-25Ta-5Me alloys (Me is Mo (HTM alloy), W (HTW), 0.5Mo + 0.5 W (HTMW), Cr (HTC) or Zr (HTZ), the compositions are in at.%) are reported at temperatures below the eutectoid transformation. The alloys were prepared by arc melting followed by hot isostatic pressing for 3 h at 1400 °C and 207 MPa. All the alloys display coarse grains of partially or fully transformed (by a eutectoid reaction) high-temperature BCC phase. The eutectoid regions consist of fine lamellae of Hf-rich HCP and Ta-rich BCC phases. The ternary alloys containing W or Cr also contained small amounts of a cubic Laves phase. At 25 °C, the HTW alloy was the strongest (yield stress σ y = 1966 MPa) but brittle and HTZ was the weakest (σ y = 1120 MPa) but ductile among the studied alloys. Other alloys showed intermediate behaviors. In general, the room temperature ductility of the alloys increased with decreasing σy. All alloys maintained high strength up to 800 °C, but displayed a noticeable strength decrease at 1000 °C. At 1000 °C, HTMW was the strongest alloy (σ y = 468 MPa) and HTC was the weakest alloy (σ y = 368 MPa). All alloys had excellent deformability at 1000 °C. Oxidation behavior of the alloys was studied at 800 °C and 1000 °C and compared with that of Hf–27Ta binary alloy. Although the ternary additions improved oxidation resistance, overall oxidation performance of the studied alloys at 800 °C and 1000 °C was poor.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermomechanical conversion in metals: dislocation plasticity model evaluation of the Taylor-Quinney coefficient

Using a partitioned-energy thermodynamic framework which assigns energy to that of atomic configurational stored energy of cold work and kinetic-vibrational, in this study we derive an important constraint on the Taylor-Quinney coefficient, which quantifies the fraction of plastic work that is converted into heat during plastic deformation. Associated with the two energy contributions are two separate temperatures – the ordinary temperature for the thermal energy and the effective temperature for the configurational energy. We show that the Taylor-Quinney coefficient is a function of the thermodynamically defined effective temperature that measures the atomic configurational disorder in the material. Finite-element analysis of recently published experiments on the aluminum alloy 6016-T4 [1], using the thermodynamic dislocation theory (TDT), shows good agreement between theory and experiment for both stress-strain behavior and temporal evolution of the temperature. The simulations include both conductive and convective thermal energy loss during the experiments, and significant thermal gradients exist within the simulation results. Computed values of the differential Taylor-Quinney coefficient are also presented and suggest a value which differs between materials and increases with increasing strain.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tunable mechanical behavior of graphene nanoribbon-metal composites fabricated through an electrocharge-assisted process

This work investigates the role of a carbon nanophase on the local mechanical behavior of nanocarbon metal matrix composites (NCMCs) produced through an electrocharge-assisted process. Nanoindentation experiments on single crystal Al, Al 1350 parent alloys, and Al 1350 NCMCs revealed variable mechanical properties, caused by an interplay between microstructure and graphitic reinforcements. TEM and AFM studies also reveal nanoscale structural changes based on the incorporation of a carbon nanophase. In order to decouple the effects of the aforementioned mechanical behaviors, molecular dynamics nanoindentation simulations were performed on the (111) surface of Al and Al NCMC samples containing semi-infinite graphene nanoribbons to examine the evolution of plasticity over time. Findings indicate that the arrangement of a finite graphene nanophase within a host matrix can alter plasticity mechanisms and therefore yield strength in near-surface mechanical behavior with little effect on elastic properties. Here, this understanding enables further study into tunable bulk properties of Al-based NCMCs while isolating microstructural effects and reinforcement effects of the carbon phase. Such an understanding will lead to application-specific material geometries ranging from highperforming vehicle structures to next-generation electrical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Protecting building occupants against the inhalation of outdoor-origin aerosols

During normal operations, buildings can protect their occupants from outdoor airborne particle hazards of all types, including airborne pollutants. A long-term international research effort has advanced our knowledge of building protection physics. Recently we have developed an operationally efficient, regional-scale methodology - Regional Shelter Analysis - to account for both building protection effects and the typical distribution of people in and among buildings. To provide input to this capability, we estimate here the degree of protection afforded by the currently existing US building stock. Here, we first assemble and summarize the published literature relevant to indoor particle losses including (a) deposition to indoor surfaces, (b) losses that occur when particles penetrate through the building envelope, and (c) heating, ventilation and air conditioning (HVAC) system filtration efficiencies as well as general building operating conditions. Building protection against inhaling particulate hazards varies strongly, by orders of magnitude, according to particle size, airborne particle loss rate, and to a lesser extent building use (occupancy). Protection increases modestly as particle size increases from 0.1 to 1 μm and significantly as particle size increases from 1 to 10 μm. Model results are placed in context with previously reported measurements. Suggestions for future work, including enhanced validation datasets are provided.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗