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Powdered iron is being investigated for its potential use as a carbon-free fuel due to its ability to burn heterogeneously and produce oxide particles, which can be collected, reduced back to iron and burned again. However, high temperature oxidation of iron particles can induce partial vaporization/decomposition and evolution of nanometric iron oxide particles. To investigate the formation process of nanoparticles in iron combustion, iron powders (consisting of spheroidal 45–53 μm particles) were injected in an electrically-heated drop tube furnace, operated at a maximum gas temperature of 1375 K, where they experienced high heating rates (104 K/s). The particles reacted with oxygen at concentrations of 15, 21, 35, 50 and 100 % by volume in nitrogen diluent gas. Particles ignited and burned brightly, with peak temperatures reaching 2344–2884 K, depending on the oxygen concentration. The observed distribution of the combustion products of iron was bimodal in size and composition, containing (a) dark gray spherical micrometric particles bigger than their iron particle precursors composed of both magnetite and hematite, and (b) highly agglomerated orange-reddish nanometric particles composed of hematite. The mass fraction of nanometric particles accounted for up to 1.7–7.4 % of the collected products, increasing with the oxygen partial pressure. The nanometric particles were spherules, 30–100 nm in diameter. However, they were highly agglomerated with aggregate aerodynamic diameters peaking at 180–560 nm. The yield of nanoparticles increased with increasing oxygen concentration in the furnace. A heuristic model was used to investigate the impact and sensitivity of various strategies for modeling evaporation, aiming to identify key mechanisms that limit the evaporation rate. This study highlights that understanding the type of liquid at the particle surface is crucial, as evaporation can increase significantly with a homogeneous liquid Fe-O particle compared to a core–shell morphology. Additionally, the analysis suggests that evaporation likely occurs in an intermediate regime where gaseous Fe-containing species oxidize in the boundary layer. Understanding these boundary layer processes is essential for accurately modeling the evaporation rate while maintaining computational efficiency. 1. 

Human-human communication is like a delicate dance where listeners and speakers concurrently interact to maintain conversational dynamics. Hence, an effective model for generating listener nonverbal behaviors requires understanding the dyadic context and interaction. In this paper, we present an effective framework for creating 3D facial motions in dyadic interactions. Existing work consider a listener as a reactive agent with reflexive behaviors to the speaker’s voice and facial motions. The heart of our framework is Dyadic Interaction Modeling (DIM), a pre-training approach that jointly models speakers’ and listeners’ motions through masking and contrastive learning to learn representations that capture the dyadic context. To enable the generation of non-deterministic behaviors, we encode both listener and speaker motions into discrete latent representations, through VQ-VAE. The pre-trained model is further fine-tuned for motion generation. Extensive experiments demonstrate the superiority of our framework in generating listener motions, establishing a new state-of-the-art according to the quantitative measures capturing the diversity and realism of generated motions. Qualitative results demonstrate the superior capabilities of the proposed approach in generating diverse and realistic expressions, eye blinks and head gestures. 

This manuscript reports on the combustion of powdered iron, for the purpose of utilizing it as an environmentally friendly circular energy carrier. The conducted research investigated the spectral emissivity and temperature of iron particles, burned either individually or in groups. Combustion experiments were conducted under high heating rates in an externally-heated drop tube furnace. The pressure was atmospheric and the axial temperature was nearly-constant at ~1350 K. The oxidizer gas contained 15-100% oxygen in nitrogen diluent. Iron particles were sieve-classified in the 44-53 µm range. Results showed that, depending on the oxygen concentration, and consequently the particle temperature, the average spectral emissivities of single burning particles varied between 0.18 and 0.46, in the 600-1000 nm wavelength range. Corresponding temperatures of single particles varied between 2300 K and 2800 K, increasing with increasing oxygen concentration in the gas. In the case of groups of iron particles burning in air at different particle number densities, average spectral emissivities were found to be in the range of 0.42-0.45, with the upper value associated with denser particle clouds. Corresponding peak temperatures of particle burning in groups were found to be in the range of 2160 K to 2100 K, with the lower value attributed to denser particle clouds.