Applied Materials (United States)

Clinical evidence is needed for performance of novel coronavirus disease (COVID-19) molecular tests in asymptomatic populations to support regulatory decisions. To support claim expansion of a direct molecular test, clinical use and performance of the Cobas® SARS-CoV-2 qualitative test for use on Cobas 5800/6800/8800 Systems ("candidate test") for detecting SARS-CoV-2 in individuals who are asymptomatic were investigated. This study leveraged real-world data from the 2020 National Football League (NFL) COVID-19 Surveillance Program during August 1, 2020-January 3, 2021. NFL players and staff from 32 clubs had nasal samples prospectively collected on a near-daily basis. Samples underwent reverse transcription polymerase chain reaction (RT-PCR) testing by a single provider across five laboratories. The study population included individuals whose samples were tested on the candidate test. A comparator algorithm was constructed based on comparator test results and clinical adjudication within the NFL program. Results from the candidate test were compared against the comparator algorithm to calculate positive and negative percent agreements (PPA and NPA). Two-sided 95% confidence intervals (CIs) for PPA and NPA were determined (Wilson score method). A total of 1776 samples were included in the final analysis. All 11 samples with positive comparator status were positive on the candidate test (PPA 100% [95%CI 74.1, 100]). Of 1765 samples with negative comparator status, 1762 were negative on the candidate test (NPA 99.8% [95%CI 99.5, 99.9]). Results were consistent when stratified by age and sex. Based on data collected during this occupational testing protocol, our study provides strong evidence supporting real-world performance of this test in an asymptomatic population. These findings, complemented by data from an existing clinical study, provided the totality-of-evidence that supported the US Food and Drug Administration clearance for the expanded claim of the candidate test for the qualitative detection of SARS-CoV-2 in the asymptomatic population.

This paper presents a variety of broadband, low-loss interconnects designed on an experimental process that includes 6 organic resin-filled dielectric layers laminated on both sides of a silicon interposer. The process allows metallization of each dielectric layer, making 6 metallic layers available for design. This paper highlights 3 interconnects using 3 metal layers, as well as a coaxial through-silicon via (TSV) interconnect using all 6 layers. Interconnects on both high-resistivity and low-resistivity interposer wafers are characterized from 2 to 50 GHz, showing a return loss better than 10 dB and insertion loss below 0.5 dB across the frequency range for organic-layer interconnects. The TSV transitions demonstrate 0.11 dB/mm and 0.16 dB/mm insertion loss at 10 GHz when fabricated on high and low resistivity interposers, respectively. Broadside couplers are designed and characterized to evaluate cross-coupling between lines on different metal layers. A second generation wafer including multilayer passive circuits is fabricated and measured. Results for a 6-dB grounded coplanar waveguide coupler and a substrate-integrated waveguide multi-layer filter are presented.

We present a fully integrated AI-driven framework for rapid endurance prediction in NVDRAM ferroelectric capacitors. Endurance testing is one of the most time- and resource-intensive steps in memory characterization, often requiring up to 10¹<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> cycles per device. To overcome the scarcity of endurance training data, we propose an experimentally calibrated synthetic data generation pipeline using kinetic Monte Carlo (kMC) simulations in Ginestra™, seeded with experimentally extracted defect parameters. We train a transformer-based AI surrogate using this high-fidelity dataset, achieving an R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.992 and enabling ~10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup>x speedup in defect evolution prediction. The surrogate generates large-scale synthetic datasets by sampling initial defect profiles, which are then used to train a hybrid multi-layer perceptron (MLP)-attention model that maps early-life defect characteristics to Weibull endurance distributions. This final endurance prediction model achieves strong agreement with ground truth Weibull parameters, with R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values of >0.98 for η and ~0.9 for β, demonstrating its reliability in capturing endurance distribution characteristics. Wafer-scale prediction of breakdown distributions is demonstrated in one-shot, reducing characterization time by over 10 orders of magnitude. This framework enables scalable, high-throughput reliability screening for ferroelectric memory technologies.

Background/Objectives: Ochratoxin A (OTA) is a widespread foodborne mycotoxin linked to chronic kidney disease of unknown etiology. Despite evidence from animal models showing OTA accumulation in the kidney, the molecular mechanisms underlying its renal disposition in humans remain only partially understood. Here, we identify human renal transporters responsible for OTA kidney accumulation, elimination, and establish Michaelis–Menten kinetics under matched conditions to directly compare transport mechanisms. We also aim to identify inhibition potential of these transport mechanisms with common dietary polyphenols. Methods: Mammalian cells and membrane vesicles overexpressing human renal transporters were used to screen and profile the uptake and efflux of OTA. Miquelianin, (-)-Epicatechin-3-O-gallate, myricetin, luteolin, and caffeic acid were tested as potential concentration-dependent transporter inhibitors. Results: We demonstrate that OTA is a substrate for human organic anion transporter (hOAT) 1 (Km: 2.10 ± 0.50 μM, Vmax: 396.9 ± 27.0 pmol/mg/min), hOAT3 (Km: 2.58 ± 0.83 μM, Vmax: 141.4 ± 30.3 pmol/mg/min), hOAT4 (Km: 6.38 ± 1.45 μM, Vmax: 96.9 ± 18.8 pmol/mg/min), and human organic anion transporting polypeptide (hOATP) 1A2 (Km: 37.3 ± 6.2 μM, Vmax: 801.0 ± 133.9 pmol/mg/min). Among efflux transporters, OTA was transported only by human breast cancer resistance protein (hBCRP), which has minimal renal expression. While none of the uptake transporters were potently inhibited (>90%) by polyphenols at 10 μM, luteolin inhibited hBCRP-mediated transport of OTA with an IC50 of 22 μM and caffeic acid stimulated hBCRP-mediated efflux with an EC50 of 713.8 μM, both of which are physiologically relevant intestinal lumen concentrations. Conclusions: Our results confirm that exposure to OTA will lead to renal accumulation and increased health risks in affected populations, necessitating increased scrutiny of our food sources.

The synthesis of biobased covalent adaptable networks (CANs) is becoming increasingly popular as a sustainable alternative to thermosetting polymers since they are both recyclable and less dependent on petroleum chemicals. However, biobased CANs centered on the Diels–Alder (DA) reaction typically comprise the aromatic N,N′-(4,4′-methylene diphenyl) bismaleimide (BMI), which is toxic. Here, we synthesize less harmful aliphatic bismaleimides with varying molar mass and biobased multifunctional furan cross-linkers via facile procedures that achieve high conversion. These materials were subsequently copolymerized to prepare a range of thermally reversible cross-linked aliphatic polyester CANs with high gel fractions (88–98%). Structure–property relationships were established, showing that the compositions of the furan cross-linker and bismaleimide controlled the thermal and mechanical properties of the networks, leading to dissociation temperatures up to 136 °C and tensile strengths up to 9.3 MPa. Moreover, network recyclability was demonstrated via compression molding under mild conditions with very good recovery of mechanical properties (>75%), and the materials also displayed rapid healing. This research provides a facile approach to the smart design of recyclable biobased aliphatic polyester Diels–Alder CANs without the use of BMI, while achieving network properties that are tunable via the structures of the aliphatic bismaleimides and biobased furan cross-linkers.

Abstract A quadruply lensed source, J125856.3–031944, has been discovered using the DELVE survey and Wide-field Infrared Survey Explorer W1–W2 colors. Follow-up direct imaging carried out with the Magellan Baade 6.5 m telescope is analyzed, as is spectroscopy from the 2.5 m Nordic Optical Telescope. The lensed image configuration is kite-like, with the major axis of the lensing galaxy along the symmetry axis of the kite, and with the faintest image at its tail. Redward of 6000 Å, the tail image is strongly blended with the lensing galaxy. The Sloan g direct imaging carried out with Magellan permits deblending. As the lensed image configuration is nearly circular, simple models give high predicted magnifications for all four images. The source’s narrow emission lines at redshift z = 2.225 and low intrinsic luminosity qualify it as a type 2 active galactic nucleus. The Magellan image shows a substantial residual that suggests a second lensing galaxy.

Analog compute in memory (CIM) with multilevel cell (MLC) resistive random access memory (ReRAM) promises highly dense and efficient compute support for machine learning and scientific computing. This article introduces analog to digital converter (ADC)-assisted bit-serial processing for efficient, high-throughput compute. Bit-serial digital to analog converters (DACs) and 8-bit binary-weighted multicycle sampling (BWMCS) ADCs perform analog vector-matrix multiplication (VMM) on MLC-based crossbar arrays. A direct drive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${g}_{m}$ </tex-math></inline-formula>-boosted transimpedance amplifier (TIA) enables high-speed crossbar readout. We present a system on chip (SoC) prototype consisting of four self-contained ReRAM-based CIM macros and a reduced instruction set computer-five (RISC-V) host. The test chip is fabricated in 65 nm CMOS with foundry-integrated MLC ReRAM. We trained LeNet1 for handwritten digit classification and mapped the CNN weights differentially to 3-bit MLC ReRAM across multiple CIM macros. The classification accuracy loss is 1.6% when compared to the quantization-aware trained model. The measured raw and normalized peak efficiencies are 20.7 and 662 TOPS/W, respectively. The compute density is 8.4 TOPS/mm2.

AMOLED displays at low gray levels require high SS to control the data potential easily. In this study, we present a high‐mobility, coplanar dual‐gate (DG) dual‐channel TFT, where the SS can be tailored. This approach enables the device to function effectively as a driving TFT, achieving SS of 0.618 V/dec. The proposed DG, dual‐sweep (DS) a‐IZO/a‐IGZTO TFT exhibits µFE of 65 cm 2 /V.s, V TH of 0.46 V, and on/off current ratio of 108.

As performance gains from 2D scaling and innovation slows, wafer-level hybrid bonding has become a key enabler for 3D scaling and heterogenous integration. Over the last decade, the industry has seen aggressive shrinking of wafer-to-wafer (W2W) bond pitches from 4 μm to 200 nm to meet the demands of next generation device connectivity requirements. Such aggressive pitch and Cu density scaling necessitates innovations in materials and process equipment (films, etch, treatments, CMP), bonding equipment and thoughtful Design Technology CoOptimization (DTCO) to ensure precise dimensional control and signal reliability. This approach enabled a first successful demonstration of W2W hybrid bonding at a bond pitch of 100 nm through careful design, materials and module co-optimization.