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1. A Direct Solution to the Self-Sensing Inverse Problem Via the Primal-Dual Interior Point Method

   https://doi.org/10.1115/SSDM2025-151276  

   Tallman, Tyler N (May 2025, American Society of Mechanical Engineers)

   Abstract Materials that are self-sensing via the piezoresistive effect have been widely explored for embedded sensing in aerospace structural composites, pressure sensing in touch pads, diagnostics in biomedical implant technology, and many other applications. In this approach, changes in electrical transport of the material are used as an indicator of stress/strain, pressure, or damage. However, engineers and other users of self-sensing materials are typically not directly interested in the electrical state of the material. Rather, they want to know the underlying mechanical state of the material that gives rise to an observed electrical change. Recovering material condition from electrical observations is referred to as the self-sensing inverse problem (SSIP). Prior work by the author has shown that the SSIP can be solved using an electrical impedance tomography (EIT)-generated conductivity map as an input, but this is undesirable because it requires solving a second inverse problem (i.e., the SSIP) on top of the EIT inverse problem. To that end, a direct formulation for the SSIP is herein presented. In this approach, voltage-current data is directly inverted to find the displacement field without using EIT as an intermediate step. Additionally, the direct SSIP is solved within the primal-dual interior point (PDIPM) framework such that an ℓ1-norm can be used on the regularization term, which promotes sparsity in the solution space. This approach is applied to a representative piezoresistive nanocomposite using the Laplace matrix as regularization to promote a spatially smooth solution. From the displacement field, strains and stresses are calculated and compared to a commercial finite element solution with good accuracy. 

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2. A Computational Method for Full-Field Mechanics Imaging via the Self-Sensing Inverse Problem Enhanced with Sensor Data Fusion

   https://doi.org/10.31224/6666  

   Nguyen, Andrew; Tallman, Tyler (March 2026, engrXiv)

   Achieving material state awareness (MSA) of a mechanical system, structure, or component empowers engineers to be able to perform accurate failure prognosis and estimate remaining operational lifetime. Piezoresistive materials exhibit a change in electrical conductivity (or resistivity) when subjected to mechanical strain and therefore have the potential to enable functional, self-sensing structures that can provide real-time insight into their mechanical state. While piezoresistive materials have been demonstrated to be able to detect and localize damage by imaging conductivity changes, conductivity changes alone do not directly translate to stresses, strains, or displacements, values that are more meaningful for stress and failure analyses. To this end, the self-sensing inverse problem (SSIP) is a method which reconstructs the strain state that gives rise to an observed conductivity distribution. The SSIP has to date been computationally and experimentally demonstrated to reconstruct the deformed displacement field of simple geometries under load with reasonable accuracy, but mathematical limitations can make obtaining an accurate reconstruction difficult. In this work, we seek to improve the ability of the SSIP to obtain accurate displacement field reconstructions on more complex geometries by incorporating sensor data fusion (SDF) techniques. We herein develop a computational inverse problem for two SDF methods, one fusing electrical resistivity with displacement data and another fusing resistivity with strain data, and demonstrate these methods computationally on shapes representing aircraft components. These results show that incorporating data from relatively few displacement sensors allows the SSIP to reconstruct the displacement field with high accuracy. The results also demonstrate that incorporating strain sensor data improves the accuracy of the displacement reconstruction, though to a lesser degree than displacement data. 

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3. A two-component regulatory system mediates quorum sensing-dependent morphology and motility transitions in the archaeon Haloferax volcanii

   https://doi.org/10.1128/mbio.01036-26  

   Cote, Jacob A; Chatterjee, Priyanka; Garcia, Marco; Tao, Ran; Mathijssen, Arnold_J_T M; Pohlschroder, Mechthild (July 2026, mBio)

   Albers, Sonja-Verena (Ed.)

   ABSTRACT Quorum sensing (QS) enables microorganisms—including bacteria, eukaryotes, and viruses—to coordinate collective behaviors in response to population density. Despite their ecological and evolutionary significance, QS mechanisms in Archaea remain poorly characterized. The halophilic archaeonHaloferax volcaniiprovides a model for archaeal QS, transitioning from motile rods to non-motile disks in a density-dependent response to a secreted disk-forming signal (DFS). To identify components of the DFS regulatory network, we screened for spontaneous mutants that retained motility in DFS-containing soft-agar medium. One candidate,HVO_1357, encodes a predicted response regulator located adjacent to a histidine kinase (HVO_1356) and a second response regulator (HVO_1358), consistent with an extended two-component regulatory system (TCS). Based on our results, these genes encodequorum-sensing-associatedregulators (Qar); therefore, we propose renaming them toqarA(HVO_1357),qarB(HVO_1356), andqarC(HVO_1358). Deletion ofqarAenabled cells to swim on DFS-containing soft-agar plates and conferred hypermotility on standard soft-agar media; however, these phenotypes were not due to changes in motility-related parameters, but a reduced sensitivity to DFS for induction of the non-motile, disk-shaped state. In contrast, ΔqarBand ΔqarCstrains were non-motile and exhibited premature disk formation during normal growth. Suppressor mutations restoring motility to ΔqarBand ΔqarCmapped exclusively toqarA, and epistasis analysis indicated QarA as the central regulator of this system. Phosphoablative variants of QarA, QarB, and QarC failed to complement their respective deletion strains, supporting QarABC as a TCS. Transcriptomic analyses revealed thatqarAdeletion leads to upregulation of genes involved in motility and rod-shape formation. Together, these findings revealqarABCas a DFS-responsive regulatory module and represent the first TCS in archaea shown to control QS-dependent behavior.IMPORTANCEArchaea are ubiquitous and play key roles across diverse ecosystems—including human microbiomes—yet little is known about how they communicate with one another and with other organisms, or how these interactions shape their ecological impact. Such intercellular communication, including quorum sensing (QS), allows microorganisms to coordinate behaviors critical for survival, adaptation, and community organization. In this study, we identify the first archaeal two-component regulatory system that is involved in QS-dependent regulation, providing a foundation for understanding how organisms in this domain sense and respond to population cues. By revealing a previously unknown aspect of archaeal biology, this work represents an important step toward understanding how archaeal communication shapes both their physiology and their interactions within complex microbial communities. 

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4. A Krylov subspace type method for Electrical Impedance Tomography

   https://doi.org/10.1051/m2an/2021057  

   Pasha, Mirjeta; Kupis, Shyla; Ahmad, Sanwar; Khan, Taufiquar (November 2021, ESAIM: Mathematical Modelling and Numerical Analysis)

   Electrical Impedance Tomography (EIT) is a well-known imaging technique for detecting the electrical properties of an object in order to detect anomalies, such as conductive or resistive targets. More specifically, EIT has many applications in medical imaging for the detection and location of bodily tumors since it is an affordable and non-invasive method, which aims to recover the internal conductivity of a body using voltage measurements resulting from applying low frequency current at electrodes placed at its surface. Mathematically, the reconstruction of the internal conductivity is a severely ill-posed inverse problem and yields a poor quality image reconstruction. To remedy this difficulty, at least in part, we regularize and solve the nonlinear minimization problem by the aid of a Krylov subspace-type method for the linear sub problem during each iteration. In EIT, a tumor or general anomaly can be modeled as a piecewise constant perturbation of a smooth background, hence, we solve the regularized problem on a subspace of relatively small dimension by the Flexible Golub-Kahan process that provides solutions that have sparse representation. For comparison, we use a well-known modified Gauss–Newton algorithm as a benchmark. Using simulations, we demonstrate the effectiveness of the proposed method. The obtained reconstructions indicate that the Krylov subspace method is better adapted to solve the ill-posed EIT problem and results in higher resolution images and faster convergence compared to reconstructions using the modified Gauss–Newton algorithm. 

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5. HfO ₂ -based platform for high-index-contrast visible and UV integrated photonics

   https://doi.org/10.1364/OL.553552  

   Jaramillo, Oscar; Natarajan, Vighnesh; Mahmud_Rivy, Hamim; Tensuan, Joshua; Massai, Leonardo; Mehta, Karan K (January 2025, Optics Letters)

   Ultraviolet and visible integrated photonics enable applications in quantum information, sensing, and spectroscopy, among others. Few materials support low-loss photonics into the UV, and the relatively low refractive index of known depositable materials limits the achievable functionality. Here, we present a high-index integrated photonics platform based on HfO₂and Al₂O₃composites deposited via atomic layer deposition (ALD) with low loss in the visible and near UV. We show that Al₂O₃incorporation dramatically decreases bulk loss compared to pure HfO₂, consistent with inhibited crystallization due to the admixture of Al₂O₃. Composites exhibit refractive indexnfollowing the average of that of HfO₂and Al₂O₃, weighted by the HfO₂fractional compositionx. Atλ = 375 nm, composites withx = 0.67 exhibitn = 2.01, preserving most of HfO₂’s significantly higher index, and 3.8(7) dB/cm material loss. We further present fully etched and cladded waveguides, grating couplers, and ring resonators, realizing a single-mode waveguide loss of 0.25(2) dB/cm inferred from resonators of 2.6 million intrinsic quality factor atλ = 729 nm, 2.6(2) dB/cm atλ = 405 nm, and 7.7(6) dB/cm atλ = 375 nm. We measure the composite’s thermo-optic coefficient (TOC) to be 2.44(3) × 10⁻⁵RIU/°C nearλ = 397 nm. This work establishes (HfO₂)_x(Al₂O₃)_1−xcomposites as a platform amenable to integration for low-loss, high-index photonics spanning the UV to NIR. 

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