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Here we provide percent contribution of mineral associated (i.e., heavy fraction - HF) and relatively more labile (i.e., light fraction - LF) organic matter through soil profiles and along hillslope catena within sites in the Critical Zone Network (CZNet) Geomicrobiology cluster. Each sample is separated into a HF an a LF utilizing a 1.85 g cm-3 sodium polytungstate (3Na2WO4·9WO3·H2O or Na6 [H2W12O40]) solution. The resultant fractions are run for percent carbon (C) and nitrogen (N) and their associated stable isotopes (δ13C and δ15N) to offer novel insights in soil organic matter processes. Samples that were either too small for analytical analysis or below instrument detection limit are labeled with BDL. 

Abstract Intracellular electrophysiology is essential in neuroscience, cardiology, and pharmacology for studying cells’ electrical properties. Traditional methods like patch-clamp are precise but low-throughput and invasive. Nanoelectrode Arrays (NEAs) offer a promising alternative by enabling simultaneous intracellular and extracellular action potential (iAP and eAP) recordings with high throughput. However, accessing intracellular potentials with NEAs remains challenging. This study presents an AI-supported technique that leverages thousands of synchronous eAP and iAP pairs from stem-cell-derived cardiomyocytes on NEAs. Our analysis revealed strong correlations between specific eAP and iAP features, such as amplitude and spiking velocity, indicating that extracellular signals could be reliable indicators of intracellular activity. We developed a physics-informed deep learning model to reconstruct iAP waveforms from extracellular recordings recorded from NEAs and Microelectrode arrays (MEAs), demonstrating its potential for non-invasive, long-term, high-throughput drug cardiotoxicity assessments. This AI-based model paves the way for future electrophysiology research across various cell types and drug interactions. 

In this paper, we construct a novel Eulerian–Lagrangian finite volume (ELFV) method for nonlinear scalar hyperbolic equations in one space dimension. It is well known that the exact solutions to such problems may contain shocks though the initial conditions are smooth, and direct numerical methods may suffer from restricted time step sizes. To relieve the restriction, we propose an ELFV method, where the space-time domain was separated by the partition lines originated from the cell interfaces whose slopes are obtained following the Rakine–Hugoniot junmp condition. Unfortunately, to avoid the intersection of the partition lines, the time step sizes are still limited. To fix this gap, we detect effective troubled cells (ETCs) and carefully design the influence region of each ETC, within which the partitioned space-time regions are merged together to form a new one. Then with the new partition of the space-time domain, we theoretically prove that the proposed first-order scheme with Euler forward time discretization is total-variation-diminishing and maximum-principle-preserving with at least twice larger time step constraints than the classical first order Eulerian method for Burgers’ equation. Numerical experiments verify the optimality of the designed time step sizes. 

Abstract This study explores a novel multi-material 3D printing technique for fabricating bioinspired hydrogel-Rochelle salt composites, focusing on optimizing concentration, cooling, and coating parameters to enhance material performance. The hydrogel-Rochelle salt composite is a promising material due to its lightweight, mechanical robustness, and piezoelectric properties, making it suitable for applications in sensors, medical devices, and structural materials. A series of concentration tests was conducted to determine the optimal Rochelle salt concentration for achieving efficient curing depth and exposure time. The results identified 50wt% hydrogel/50wt% Rochelle salt as the optimal concentration, providing a balanced curing profile essential for ensuring reliable layer adhesion and structural consistency. To enable controlled crystallization, a cooling process was introduced, with a cooling time of 15 minutes found to be sufficient for complete crystallization to a depth of 500 microns. Thermal imaging and microscopy confirmed the stability of the crystalline structure within the hydrogel matrix, ensuring the material’s functional integrity. Additionally, applying a coating to the printed structure significantly improved surface uniformity and durability, embedding the crystalline elements more effectively within the hydrogel matrix and enhancing the composite’s overall structural integrity. This coating process allowed the composite to withstand repeated printing cycles, facilitating the construction of layered, multi-material structures with improved mechanical and functional properties. The results highlight the importance of fine-tuning concentration, cooling time, and coating techniques to achieve optimal performance in multi-material 3D printing. By addressing these factors, the study demonstrates a reliable approach to producing hydrogel-Rochelle salt composites with high structural quality and piezoelectric functionality. This method not only enhances the material’s durability and adhesion between layers but also opens new possibilities for creating customized, multifunctional materials. The developed process holds significant promise for applications that require precise control over material properties, such as wearable electronics, medical implants, and lightweight structural components. In conclusion, this research provides valuable insights into the fabrication of hydrogel-Rochelle salt composites through advanced 3D printing techniques. The findings offer a foundation for future exploration in multi-material printing and composite fabrication, paving the way for the development of versatile materials with tailored properties for diverse applications.