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This paper introduces our system submission for the Cadenza ICASSP 2024 Grand Challenge, which presents the problem of remixing and enhancing music for hearing aid users. Our system placed first in the challenge, achieving the best average Hearing-Aid Audio Quality Index (HAAQI) score on the evaluation data set. We describe the system, which uses an ensemble of deep learning music source separators that are fine tuned on the challenge data. We demonstrate the effectiveness of our system through the challenge results and analyze the importance of different system aspects through ablation studies., Comment: 2 pages, ICASSP 2024, Cadenza Grand Challenge

The complex atomic scale structure of high entropy alloys presents new opportunities to expand the deformation theories of mechanical metallurgy. In this regard, solute-defect interactions have emerged as critical piece in elucidating the operation of deformation mechanisms. While notable progress has been made in understanding solute-defect interactions for random solute arrangements, recent interest in high entropy alloys with short-range order adds a new layer of structural complexity for which a cohesive picture has yet to emerge. To this end, this minireview synthesizes the current understanding of short-range order effects on defect behavior through an examination of the key recent literature. This analysis centers on the nanoscale metallurgy of deformation mechanisms, with the order-induced changes to the relevant defect energy landscapes serving as a touchstone for discussion. The topics reviewed include dislocation-mediated strengthening, twinning and phase transformation-based mechanisms, and vacancy-mediated processes. This minireview concludes with remarks on current challenges and opportunities for future efforts.

Many people with severely limited muscle control can only communicate through augmentative and alternative communication (AAC) systems with a small number of buttons. In this paper, we present the design for ColorCode, which is an AAC system with two buttons that uses Bayesian inference to determine what the user wishes to communicate. Our information-theoretic analysis of ColorCode simulations shows that it is efficient in extracting information from the user, even in the presence of errors, achieving nearly optimal error correction. ColorCode is provided as open source software (https://github.com/mrdaly/ColorCode)., Comment: 7 pages, 3 figures, SLPAT Workshop - ACL 2022

Recent studies of concentrated solid solutions have highlighted the role of varied solute interactions in the determination of a wide variety of mesoscale properties. These solute interactions emerge as spatial fluctuations in potential energy, which arise from local variations in the chemical environment. Although observations of potential energy fluctuations are well documented in the literature, there remains a paucity of methods to determine their statistics. Here, we present a set of analytical equations to quantify the statistics of potential energy landscapes in randomly arranged solid solutions. Our approach is based on a reparameterization of the relations of the embedded atom method in terms of the solute coordination environment. The final equations are general and can be applied to different crystal lattices and energy landscapes, provided the systems of interest can be described by sets of coordination relations. We leverage these statistical relations to study the cohesive energy and generalized planar fault energy landscapes of several different solid solutions. Analytical predictions are validated using molecular statics simulations, which find excellent agreement in most cases. The outcomes of this analysis provide new insights into phase stability and the interpretation of local planar fault energies in solid solutions, which are topics of ongoing discussion within the community.

Recent studies of FeMnCoCr-based high entropy alloys have demonstrated uncommon deformation behaviors such as transformation-induced plasticity, which were largely believed to be restricted to select families of steels. Coupled with the potential for entropy stabilization of high symmetry phases at high temperatures, this system represents a promising class of materials for structural applications in extreme environments. Yet, transformation-induced plasticity mechanisms are notably sensitive to microstructure parameters and the literature offers examples of deleterious decomposition of high entropy alloys under heat treatment, which raises concerns of resiliency in mechanical performance. Here, we evaluate the evolution of microstructure and mechanical properties of a FeMnCoCr high entropy alloy after prolonged heat treatment at high temperature. Microstructures are found to retain their characteristic austenite/martensite features, with parent face-centered cubic grains partitioned by hexagonal close-packed laths after heat treatment at 1200 C for up to 48 hours. Results of mechanical testing reveal an unusual insensitivity of this alloy to grain growth-induced weakening effects. Namely, the yield strengths of FeMnCoCr samples are observed to remain constant across all heat treatment conditions, despite a near four-fold increase in the grain size. Close examination of post-heat treatment microstructures reveals a dramatic decrease in the inter-lath spacing at longer durations, which segments parent austenite grains. This crystal partitioning counteracts conventional grain growth-induced weakening by introducing additional barriers for dislocation pile-up. These results offer new insights into the mechanical resiliency of this transformation-induced plasticity high entropy alloy under prolonged high temperature heat treatment.

The competition between deformation twinning and dislocation slip underpins the evolution of mesoscale plasticity in face-centered cubic materials. While competition between these mechanisms is known to be related to the critical features of the generalized planar fault energy landscape, a physical theory that tracks competition over extended plasticity has yet to emerge. Here, we report a methodology to predict the mesoscale evolution of this competition in deformed crystals. Our approach implements kinetic Monte Carlo simulations to examine fault structure evolution in face-centered cubic metals using intrinsic material parameters as inputs. These results are leveraged to derive an analytical model for the evolution of the fault fraction, fault densities, and partitioning of plastic strains among deformation mechanisms. In addition, we define a competition parameter that measures the tendencies for deformation twinning and dislocation slip. In contrast to previous twinnability parameters, our derivation considers deformation history when examining mechanism competition. This contribution therefore extends the reach of deformation twinning theory beyond incipient nucleation events. These products find direct applications in work hardening and crystal plasticity models, which have previously relied on phenomenological relations to predict the mesoscale evolution of deformation twin microstructures.