Engineering topics

Zhang, Li

Publications and source records attributed to Zhang, Li.

9 records

DOE OSTI2026

Engineering Thermally Resilient and Kinetically Active Reversible Protonic Ceramic Cells via Interfacial Design

Achieving concurrent fast electrode kinetics and long-term thermo-mechanical durability remains a critical challenge for reversible protonic ceramic electrochemical cells (R-PCECs). Herein, we report an interfacial engineering strategy that integrates a perovs.kite-type PrBaRu0.1Co1.9O5+δ (PBRC) nanoparticle layer onto a PrBa0.5Sr0.5Co1.5Fe0.5O5+δ (PBSCF) substrate (PBRC-PBSCF), together with a modified pellet-assisted sintering approach to fabricate dense BaZr0.4Ce0.4Y0.1Yb0.1O3-δ (BZCYYb4411) electrolytes. The in situ reconstructed heterointerface enhances oxygen reduction/evolution reaction (ORR/OER) kinetics, promotes H2O adsorption/dissociation, and improves steam tolerance, as verified by electrochemical measurements and interfacial microstructural analyses. Density functional theory reveals that Ru-induced electronic modulation at the PBRC-PBSCF interface lowers the energy of oxygen vacancy formation and optimizes the position of the O 2p band center, thereby accelerating oxygen redox kinetics and stabilizing the interface. The resulting R-PCECs deliver an excellent peak power density of 1.112 W cm−2 and an electrolysis current density of −1.257 A cm−2 at 1.3 V in 3% H2O wet air at 600°C, with a reasonable faradaic efficiency. Furthermore, the cells demonstrate excellent stability, sustaining 100 h of thermal cycling (400–600°C, 200°C h−1) in both fuel cell and electrolysis modes, with 600 h of stability in electrolysis mode (600°C, −0.5 to −2 A cm−2).

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

He, Shuaitong↗

DOE OSTI2024

AtDGCR14L contributes to salt-stress tolerance via regulating pre-mRNA splicing in Arabidopsis

In plants, the pre-mRNA alternative splicing has been demonstrated to be a crucial tier that regulates gene expression in response to salt stress. However, the underlying mechanisms remain elusive. Here, in this study, we studied the roles of DIGEORGE-SYNDROME CRITICAL REGION 14-like (AtDGCR14L) in regulating pre-mRNA splicing and salt stress tolerance. We discovered that Arabidopsis AtDGCR14L is required for maintaining plant salt stress tolerance and the constitutively spliced and active isoforms of important stress- and/or abscisic acid (ABA)-responsive genes. We also identified the interaction between AtDGCR14L and splicing factor U1-70k, which needs a highly conserved three amino acid (TWG) motif in DGCR14. Different from wild-type AtDGCR14L, the overexpression of TWG-substituted AtDGCR14L mutant did not change salt stress tolerance or pre-mRNA splicing of stress/ABA-responsive genes. Additionally, SWITCH3A (SWI3A) is a core subunit of the SWI/SUCROSE NONFERMENTING (SWI/SNF) chromatin-remodeling complexes. We found that SWI3A, whose splicing depends on AtDGCR14L, actively enhances salt stress tolerance. These results revealed that AtDGCR14L may play an essential role in crosstalk between plant salt-stress response and pre-mRNA splicing mechanisms. We also unveiled the potential role of SWI3A in controlling salt stress tolerance. The TWG motif in the intrinsically disordered region of AtDGCR14L is highly conserved and crucial for DGCR14 functions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

ETROC1: the first full chain precision timing prototype ASIC for CMS MTD endcap timing layer upgrade

We present the design and characterization of the first fullchain precision timing prototype ASIC, named ETL Readout Chipversion 1 (ETROC1) for the CMS MTD endcap timing layer (ETL)upgrade. The ETL utilizes Low Gain Avalanche Diode (LGAD) sensors todetect charged particles, with the goal to achieve a time resolutionof 40–50 ps per hit, and 30–40 ps per track with hits from twodetector layers. The ETROC1 is composed of a 5 × 5 pixelarray and peripheral circuits. The pixel array includes a4 × 4 active pixel array with an H-tree shaped networkdelivering clock and charge injection signals. Each active pixel iscomposed of various components, including a bump pad, a chargeinjection circuit, a pre-amplifier, a discriminator, adigital-to-analog converter, and a time-to-digital converter. Thesecomponents play essential roles as the front-end link in processingLGAD signals and measuring timing-related information. Theperipheral circuits provide clock signals and readoutfunctionalities. The size of the ETROC1 chip is7 mm× 9 mm. ETROC1 has been fabricated in a 65 nmCMOS process, and extensively tested under stimuli of chargeinjection, infrared laser, and proton beam. The time resolution ofbump-bonded ETROC1 + LGAD chipsets reaches 42–46 ps per hit in thebeam test.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Comparative Uptake Patterns of Radioactive Iodine and [18F]-Fluorodeoxyglucose (FDG) in Metastatic Differentiated Thyroid Cancers

Background: Metastatic differentiated thyroid cancer (DTC) represents a molecularly heterogeneous group of cancers with varying radioactive iodine (RAI) and [ 18 F]-fluorodeoxyglucose (FDG) uptake patterns potentially correlated with the degree of de-differentiation through the so-called “flip-flop” phenomenon. However, it is unknown if RAI and FDG uptake patterns correlate with molecular status or metastatic site. Materials and Methods: A retrospective analysis of metastatic DTC patients (n = 46) with radioactive 131-iodine whole body scan (WBS) and FDG-PET imaging between 2008 and 2022 was performed. The inclusion criteria included accessible FDG-PET and WBS studies within 1 year of each other. Studies were interpreted by two blinded radiologists for iodine or FDG uptake in extrathyroidal sites including lungs, lymph nodes, and bone. Cases were stratified by BRAF V600E mutation status, histology, and a combination of tumor genotype and histology. The data were analyzed by McNemar’s Chi-square test. Results: Lung metastasis FDG uptake was significantly more common than iodine uptake (WBS: 52%, FDG: 84%, p = 0.04), but no significant differences were found for lymph or bone metastases. Lung metastasis FDG uptake was significantly more prevalent in the papillary pattern sub-cohort (WBS: 37%, FDG: 89%, p = 0.02) than the follicular pattern sub-cohort (WBS: 75%, FDG: 75%, p = 1.00). Similarly, BRAF V600E+ tumors with lung metastases also demonstrated a preponderance of FDG uptake (WBS: 29%, FDG: 93%, p = 0.02) than BRAF V600E- tumors (WBS: 83%, FDG: 83%, p = 1.00) with lung metastases. Papillary histology featured higher FDG uptake in lung metastasis (WBS: 39%, FDG: 89%, p = 0.03) compared with follicular histology (WBS: 69%, FDG: 77%, p = 1.00). Patients with papillary pattern disease, BRAF V600E+ mutation, or papillary histology had reduced agreement between both modalities in uptake at all metastatic sites compared with those with follicular pattern disease, BRAF V600E- mutation, or follicular histology. Low agreement in lymph node uptake was observed in all patients irrespective of molecular status or histology. Conclusions: The pattern of FDG-PET and radioiodine uptake is dependent on molecular status and metastatic site, with those with papillary histology or BRAF V600E+ mutation featuring increased FDG uptake in distant metastasis. Further study with an expanded cohort may identify which patients may benefit from specific imaging modalities to recognize and surveil metastases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Vapor Phase Infiltration of Titanium Oxide into P3HT to Create Organic–Inorganic Hybrid Photocatalysts

Herein, we report for the first time the use of vapor phase infiltration (VPI) to infuse conducting polymers with inorganic metal oxide clusters that together form a photocatalytic material. While vapor infiltration has previously been used to electrically dope conjugated polymers, this is the first time, to our knowledge, that the resultant hybrid material has been demonstrated to have photocatalytic properties. The system studied is poly(3-hexylthiophene-2,5-diyl) (P3HT) vapor infiltrated with TiCl 4 and H 2 O to create P3HT-TiO x organic–inorganic hybrid photocatalytic materials. X-ray photoelectron spectroscopy analysis shows that P3HT-TiO x VPI films consist of a partially oxidized P3HT matrix, and the infiltrated titanium inorganic is in a 4+ oxidation state with mostly oxide coordination. Upon visible light illumination, these P3HT-TiO x hybrids degrade methylene blue dye molecules. The P3HT-TiO x hybrids are 4.6× more photocatalytically active than either the P3HT or TiO 2 individually or when sequentially deposited (e.g., P3HT on TiO 2 ). On a per surface area basis, these hybrid photocatalysts are comparable or better than other best in class polymer semiconductor photocatalysts. VPI of TiCl 4 + H 2 O into P3HT makes a unique hybrid structure and idealized photocatalyst architecture by creating nanoscale TiO x clusters concentrated toward the surface achieving extremely high catalytic rates. The mechanism for this enhanced photocatalytic rate is understood using photoluminescence spectroscopy, which shows significant quenching of excitons in P3HT-TiO x as compared to neat P3HT, indicating that P3HT acts as a photosensitizer for the TiO x catalyst sites in the hybrid material. This work introduces a new approach to designing and synthesizing organic–inorganic hybrid photocatalytic materials, with expansive opportunities for further exploration and optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting

Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.

17 WIND ENERGY↗

NASA NTRS2017

What Factors Control the Trend of Increasing AAOD Over the United States in the Last Decade?

We examine the spatial and temporal trends of absorbing aerosol optical depth (AAOD) in the last decade over the United States (U.S.) observed by the Ozone Monitoring Instrument (OMI). Monthly average OMI AAOD has increased over broad areas of the central U.S. from 2005 to 2015, by up to a factor of 4 in some grid cells (~60 km resolution). The AAOD increases in all seasons, although the percentage increases are larger in summer (June-July-August) than in winter (December-January-February) by a factor of 3. Despite enhancements in AAOD, OMI AOD exhibits insignificant trend over most of the U.S. except parts of the central and western U.S., the latter which may partly be due to decreases in precipitation. Trends in AAOD contrast with declining trends in surface concentrations of black carbon (BC) aerosol. Interannual variability of local biomass burning emissions of BC may contribute to the positive trend in AAOD over the western U.S. Changes in both dust aerosol measured at the surface (in terms of concentration and size) and dust AAOD indicate distinct enhancements, especially over the central U.S. by 50-100%, which appears to be one of the major factors that impacts positive trends in AAOD.

Satellite retrieval↗

NASA NTRS2015

Constraining Black Carbon Aerosol over Asia using OMI Aerosol Absorption Optical Depth and the Adjoint of GEOS-Chem

Accurate estimates of the emissions and distribution of black carbon (BC) in the region referred to here as Southeastern Asia (70degE-l50degE, 11degS-55degN) are critical to studies of the atmospheric environment and climate change. Analysis of modeled BC concentrations compared to in situ observations indicates levels are underestimated over most of Southeast Asia when using any of four different emission inventories. We thus attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem model and its adjoint for April and October of 2006. Overwhelming enhancements, up to 500%, in anthropogenic BC emissions are shown after optimization over broad areas of Southeast Asia in April. In October, the optimization of anthropogenic emissions yields a slight reduction (1-5%) over India and parts of southern China, while emissions increase by 10-50% over eastern China. Observational data from in situ measurements and AERONET observations are used to evaluate the BC inversions and assess the bias between OMI and AERONET AAOD. Low biases in BC concentrations are improved or corrected in most eastern and central sites over China after optimization, while the constrained model still underestimates concentrations in Indian sites in both April and October, possibly as a. consequence of low prior emissions. Model resolution errors may contribute up to a factor of 2.5 to the underestimate of surface BC concentrations over northern India. We also compare the optimized results using different anthropogenic emission inventories and discuss the sensitivity of top-down constraints on anthropogenic emissions with respect to biomass burning emissions. In addition, the impacts of brown carbon, the formulation of the observation operator, and different a priori constraints on the optimization are investigated. Overall, despite these limitations and uncertainties, using OMI AAOD to constrain BC sources improves model representation of BC distributions, particularly over China.

Aerosols↗