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Li, Bo

Publications and source records attributed to Li, Bo.

At least 37 records · Page 2

Dynamic Monkey Bar Mechanism of Superionic Li‐ion Transport in LiTaCl 6

Abstract The LiTaCl 6 solid electrolyte has the lowest activation energy of ionic conduction at ambient conditions (0.165 eV), with a record high ionic conductivity for a ternary compound (11 mS cm −1 ). However, the mechanism has been unclear. We train machine‐learning force fields (MLFF) on ab initio molecular dynamics (AIMD) data on‐the‐fly and perform MLFF MD simulations of AIMD quality up to the nanosecond scale at the experimental temperatures, which allows us to predict accurate activation energy for Li‐ion diffusion (at 0.164 eV). Detailed analyses of trajectories and vibrational density of states show that the large‐amplitude vibrations of Cl − ions in TaCl 6 − enable the fast Li‐ion transport by allowing dynamic breaking and reforming of Li−Cl bonds across the space in between the TaCl 6 − octahedra. We term this process the dynamic‐monkey‐bar mechanism of superionic Li + transport which could aid the development of new solid electrolytes for all‐solid‐state lithium batteries.

Lei, Ming↗

Dynamic Monkey Bar Mechanism of Superionic Li–ion Transport in LiTaCl 6

Here, the LiTaCl 6 solid electrolyte has the lowest activation energy of ionic conduction at ambient conditions (0.165 eV), with a record high ionic conductivity for a ternary compound (11 mS cm –1 ). However, the mechanism has been unclear. We train machine-learning force fields (MLFF) on ab initio molecular dynamics (AIMD) data on-the-fly and perform MLFF MD simulations of AIMD quality up to the nanosecond scale at the experimental temperatures, which allows us to predict accurate activation energy for Li-ion diffusion (at 0.164 eV). Detailed analyses of trajectories and vibrational density of states show that the large-amplitude vibrations of Cl – ions in TaCl 6 – enable the fast Li-ion transport by allowing dynamic breaking and reforming of Li–Cl bonds across the space in between the TaCl 6 – octahedra. We term this process the dynamic-monkey-bar mechanism of superionic Li + transport which could aid the development of new solid electrolytes for all-solid-state lithium batteries.

25 ENERGY STORAGE↗

Stabilized hole-selective layer for high-performance inverted p-i-n perovskite solar cells

P-i-n geometry perovskite solar cells (PSCs) offer simplified fabrication, greater amenability to charge extraction layers, and low-temperature processing over n-i-p counterparts. Self-assembled monolayers (SAMs) can enhance the performance of p-i-n PSCs but ultrathin SAMs can be thermally unstable. Here we report a thermally robust hole-selective layer comprised of nickel oxide (NiO x ) nanoparticle film with a surface-anchored (4-(3,11-dimethoxy-7H-dibenzo[c,g]carbazol-7-yl)butyl)phosphonic acid (MeO-4PADBC) SAM that can improve and stabilize the NiO x /perovskite interface. The energetic alignment and favorable contact and binding between NiO x /MeO-4PADBC and perovskite reduced the voltage deficit of PSCs with various perovskite compositions and led to strong interface toughening effects under thermal stress. The resulting 1.53–electron-volt devices achieved 25.6% certified power conversion efficiency and maintained >90% of their initial efficiency after continuously operating at 65 degrees Celsius for 1200 hours under 1-sun illumination.

14 SOLAR ENERGY↗

Lower-length-scale modeling of chemical additions, corrosion and fission products in select MSR base salts

Molten salts play a crucial role in advancing Generation IV nuclear energy technology, with chloride-based salts like NaCl-UCl 3 garnering significant attention due to their distinctive properties. However, the corrosive nature of molten salts causes the dissolution of chromium (Cr), leading to the formation of CrCl 2 and CrCl 3 species in molten chlorides. Moreover, the radioactive decay of nuclear fuel gives rise to fission products, including Cs, Sr, and I chlorides. The first part of this report presents a comprehensive study utilizing ab initio molecular dynamics (AIMD) simulations to investigate the properties of eutectic NaCl-UCl 3 molten salt in the presence of corrosion products (CrCl 2 and CrCl 3 ) and fission product (CsCl). The study focuses on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) of the salts with varying compositions of corrosion products and fission product, covering a range from 0% to 13.5%. The results offer valuable insights into the behavior of corrosion and fission products in uranium-based molten salts, providing essential data that can be used as input to the MTDB-TC and MSTDB-TP property databases being developed by the NEAMS program. Due to their favorable characteristics such as low melting points, high boiling points, and low costs, MgCl 2 +NaCl+KCl (MNK) eutectic salts have recently attracted attention as high-temperature heat transfer fluids. The incorporation of LiCl into MNK salts can further reduce their melting points and increase their specific heat capacities, which is de- sirable for high-temperature heat transfer applications. The second part of this report presents the development and validation of a new shell-model potential for the MgCl 2 +NaCl+KCl+LiCl system, which captures the polarization of Cl anions. The extensive comparison with experimental data and AIMD simulations demonstrates the accuracy and reliability of the potential. Furthermore, using this potential, we elucidate the intricate network structure in MNK eutectic salts that is formed through polyhedron sharing. This research contributes to a fundamental understanding of the atomic structures and thermophysical properties of multi-component molten salts, which is crucial for future development of heat transfer fluids for applications in molten salt reactors.

36 MATERIALS SCIENCE↗

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography ( MSOT ) imaging

Abstract Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through‐plane resolution volumetric MSOT is time‐consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross‐sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG‐conjugated nanoworms particles (NWs‐ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

Juhong, Aniwat↗

Close Roof Mounted System Temperature Estimation for Compliance to IEC TS 63126

When photovoltaic modules are installed on rooftops the temperature is dependent on both the geographic location and the mounting configuration. If the mounting structure does not provide sufficient air flow in a hot environment, the 98th percential temperature will exceed 70 degrees C which according to IEC TS 63126 requires higher levels of thermal stability testing. However, a simple there is not a clear way to determe which temperature level is needed for a particular location and system design. In this work we identify a relationship between the gap between the rooftop and a module and propose methods to describe minimum gaps for a given location. Because system designs vary in more ways than just the gap, we show how to determine an effective gap which can be simply applied to generic calculations. Lastly, we show measurements and calculations from several systems to demonstrate how this method could work.

IEC 63126↗

Mainstream nitrogen removal from low temperature and low ammonium strength municipal wastewater using hydrogel-encapsulated comammox and anammox

Application of partial nitritation (PN)-anammox to mainstream wastewater treatment faces challenges in low water temperature and low ammonium strength. In this study, a continuous flow PN-anammox reactor with hydrogel-encapsulated comammox and anammox was designed and operated for nitrogen removal from mainstream wastewater with low temperature. Long-term operation with synthetic and real wastewater as the feed demonstrated nearly complete ammonium and total inorganic nitrogen (TIN) removal by the reactor at temperatures as low as 10 °C. A significantly decreased nitrogen removal performance and biomass activity was observed in the reactor at 4 °C before a selective heating strategy was employed. A novel heating technology using radiation to heat carbon black co-encapsulated in the hydrogel matrix with biomass was used to selectively heat biomass but not water in the treatment system. This selective heating technology enabled nearly complete ammonium removal and 89.4 ± 4.3 % TIN removal at influent temperature of 4 °C and reactor temperature 5 °C. Activity tests suggested selective heating brought the biomass activity at influent temperatures of 4 °C and reactor temperature 5 °C to a level comparable to that at 10 °C. Comammox and anammox were consistently present in the system and spatially organized in the hydrogel beads as revealed by qPCR and fluorescence in-situ hybridization (FISH). The abundance of comammox largely decreased by 3 orders of magnitude during the operation at 4 °C, and rapidly recovered after the application of selective heating. The anammox-comammox technology tested in this study essentially enabled mainstream shortcut nitrogen removal, and the selective heating ensured good performance of the technology at temperature as low as 5 °C.

54 ENVIRONMENTAL SCIENCES↗

Ab-Initio molecular dynamics simulations of binary NaCl-ThCl 4 and ternary NaCl-ThCl 4 -UCl 3 molten salts

Molten salt reactor (MSR) with Thorium (Th) fuel cycle has attracted growing attention due to its merits such as safety, low radioactive waste production, and non-proliferation. The design and safe operation of MSR rely on a thorough understanding of the thermophysical properties of molten salts over a wide range of composition and temperature. However, experimental data of Th-based molten salts are limited due to the inherent challenges of dealing with corrosive molten salts and the radioactive nature of actinides. Here, in this work, thermophysical properties including density, heat capacity, thermal expansion coefficient, and mixing energy of binary NaCl-ThCl 4 and ternary NaCl-ThCl 4 -UCl 3 molten salts are explored using ab-initio molecular dynamic simulations (AIMD) with the dDsC dispersion correction. The calculated mixing energy of binary NaCl-ThCl 4 exhibits a minimum close to the eutectic composition. The heat capacity of the mixtures is linearly dependent on the mole fraction of each component. 7-fold and 6-fold coordinated Th complexes are dominant in the mixtures. 8-fold coordinated Th complex increases with ThCl 4 fraction due to the formation of network structures. The average coordination number of Th exhibits a minimum near the eutectic composition. The minimum mixing energy for the ternary mixtures is observed in systems with a composition close to [NaCl] 0.5 [ThCl 4 ] 0.25 [UCl 3 ] 0.25 . The density positively deviates from the ideal solution in mixtures near this composition. These results are important to fill the data and knowledge gap of ThCl 4 molten salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ligand effect on switching the rate-determining step of water oxidation in atomically precise metal nanoclusters

The ligand effects of atomically precise metal nanoclusters on electrocatalysis kinetics have been rarely revealed. Herein, we employ atomically precise Au 25 nanoclusters with different ligands (i.e., para-mercaptobenzoic acid, 6-mercaptohexanoic acid, and homocysteine) as paradigm electrocatalysts to demonstrate oxygen evolution reaction rate-determining step switching through ligand engineering. Au 25 nanoclusters capped by para-mercaptobenzoic acid exhibit a better performance with nearly 4 times higher than that of Au 25 NCs capped by other two ligands. We deduce that para-mercaptobenzoic acid with a stronger electron-withdrawing ability establishes more partial positive charges on Au(I) (i.e., active sites) for facilitating feasible adsorption of OH – in alkaline media. X-ray photo-electron spectroscopy and theoretical study indicate a profound electron transfer from Au(I) to para-mercaptobenzoic acid. The Tafel slope and in situ Raman spectroscopy suggest different ligands trigger different rate-determining step for these Au 25 nanoclusters. The mechanistic insights reported here can add to the acceptance of atomically precise metal nanoclusters as effective electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoinhibition of comammox reaction in Nitrospira inopinata in a dose- and wavelength-dependent manner

Apparent contribution of complete ammonia-oxidizing organisms (comammox) to the global nitrogen cycle highlights the necessity for understanding niche differentiation of comammox bacteria among other ammonia oxidizers. While the high affinity for ammonia of the comammox species Nitrospira inopinata suggests their niche partitioning is expected to be centered in oligotrophic environments, their absence in nutrient-depleted environments (such as the oceans) suggests that other (abiotic) factors might control their distribution and spatial localization within microbial communities. Many ammonia- and nitrite-oxidizing organisms are sensitive to light; however, the photosensitivity of comammox has not been explored. Since comammox bacteria encode enzymatic machinery homologous to canonical ammonia-and nitrite-oxidizers, we hypothesized that comammox N. inopinata, the only available pure culture of this group of microorganisms, may be inhibited by illumination in a similar manner. We evaluated the impact of light intensity, wavelength, and duration on the degree of photoinhibition for cultures of the comammox species N. inopinata and the soil ammonia-oxidizing archaea Nitrososphaera viennensis. Both species were highly sensitive to light. Interestingly, mimicking diurnal light exposure caused an uncoupling of ammonia and nitrite oxidation in N. inopinata, indicating nitrite oxidation might be more sensitive to light exposure than ammonia oxidation. It is likely that light influences comammox spatial distribution in natural environments such as surface fresh waters according to diurnal cycles, light attenuation coefficients, and the light penetration depths. Our findings therefore provide ecophysiological insights for further studies on comammox both in field and laboratory settings.

59 BASIC BIOLOGICAL SCIENCES↗

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗

High‐Pressure and High‐Temperature Single‐Crystal Elasticity of Cr‐Pyrope: Implications for the Density and Seismic Velocity of Subcontinental Lithospheric Mantle

Abstract Single‐crystal X‐ray diffraction and Brillouin spectroscopy experiments were performed on a natural Cr‐pyrope (Prp 71.0 Alm 12.6 Sps 0.7 Grs 3.5 Uvr 12.2 ) at high pressure and high temperature up to 11.0 GPa and 800 K. Fitting the collected data to the third‐order finite strain equation yields bulk modulus ( K S 0 ), shear modulus ( G 0 ), their pressure ((∂ K S /∂ P ) T and (∂ G /∂ P ) T ) and temperature (( ∂K S /∂T ) P and ( ∂G/∂T ) P ) derivatives, K S 0 = 167.7(8) GPa, G 0 = 91.5(5) GPa, (∂ K S /∂ P ) T = 4.3(1), (∂ G /∂ P ) T = 1.4(1), ( ∂K S /∂T ) P = − 0.0175(1) GPa/K and ( ∂G/∂T ) P = − 0.0073(1) GPa/K. Using the obtained results, we examined whether the elastic properties of the Cr‐pyrope can be accurately calculated from those of endmembers including pyrope, almandine, grossular, and uvarovite assuming a linear relationship between elastic properties and composition (end‐member model). The results indicate that the end‐member model provides a sufficient approximation for the elastic properties of Cr‐pyrope in calculating the density and velocity of the subcontinental lithospheric mantle (SCLM). We modeled the densities and velocities of three typical types of SCLM (Archon, Proton, and Tecton) in order to investigate how the variation of chemical composition influences the SCLM. We obtained that the compositional change from the Archon to the Tecton increases the density of the SCLM significantly, which can be an important prerequisite for SCLM delamination. However, the compositional variation only slightly changes the velocity of the SCLM and the change is within the uncertainty of the calculation. Moreover, in comparison to the velocity, ρ / V P and ρ / V S are much more sensitive to the compositional change of the SCLM.

Xu, Jingui↗