13 research outputs found
Computational Smocking through Fabric-Thread Interaction
We formalize Italian smocking, an intricate embroidery technique that gathers
flat fabric into pleats along meandering lines of stitches, resulting in pleats
that fold and gather where the stitching veers. In contrast to English
smocking, characterized by colorful stitches decorating uniformly shaped
pleats, and Canadian smocking, which uses localized knots to form voluminous
pleats, Italian smocking permits the fabric to move freely along the stitched
threads following curved paths, resulting in complex and unpredictable pleats
with highly diverse, irregular structures, achieved simply by pulling on the
threads. We introduce a novel method for digital previewing of Italian smocking
results, given the thread stitching path as input. Our method uses a
coarse-grained mass-spring system to simulate the interaction between the
threads and the fabric. This configuration guides the fine-level fabric
deformation through an adaptation of the state-of-the-art simulator, C-IPC. Our
method models the general problem of fabric-thread interaction and can be
readily adapted to preview Canadian smocking as well. We compare our results to
baseline approaches and physical fabrications to demonstrate the accuracy of
our method
Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model
Chemical reactions are the fundamental building blocks of drug design and
organic chemistry research. In recent years, there has been a growing need for
a large-scale deep-learning framework that can efficiently capture the basic
rules of chemical reactions. In this paper, we have proposed a unified
framework that addresses both the reaction representation learning and molecule
generation tasks, which allows for a more holistic approach. Inspired by the
organic chemistry mechanism, we develop a novel pretraining framework that
enables us to incorporate inductive biases into the model. Our framework
achieves state-of-the-art results on challenging downstream tasks. By
possessing chemical knowledge, our generative framework overcome the
limitations of current molecule generation models that rely on a small number
of reaction templates. In the extensive experiments, our model generates
synthesizable drug-like structures of high quality. Overall, our work presents
a significant step toward a large-scale deep-learning framework for a variety
of reaction-based applications
Data_Sheet_1_Association between oral microbiome and five types of respiratory infections: a two-sample Mendelian randomization study in east Asian population.zip
ObjectiveTo explore the causal relationship between the oral microbiome and specific respiratory infections including tonsillitis, chronic sinusitis, bronchiectasis, bronchitis, and pneumonia, assessing the impact of genetic variations associated with the oral microbiome.MethodsMendelian randomization was used to analyze genetic variations, leveraging data from genome-wide association studies in an East Asian cohort to identify connections between specific oral microbiota and respiratory infections.ResultsOur analysis revealed that Prevotella, Streptococcus, Fusobacterium, Pauljensenia, and Capnocytophaga play crucial roles in influencing respiratory infections. Prevotella is associated with both promoting bronchitis and inhibiting pneumonia and tonsillitis, with a mixed effect on chronic sinusitis. Streptococcus and Fusobacterium show varied impacts on respiratory diseases, with Fusobacterium promoting chronic sinusitis, bronchiectasis, and bronchitis. Conversely, Pauljensenia and Capnocytophaga are linked to reduced bronchitis and tonsillitis, and inhibited pneumonia and bronchitis, respectively.DiscussionThese findings underscore the significant impact of the oral microbiome on respiratory health, suggesting potential strategies for disease prevention and management through microbiome targeting. The study highlights the complexity of microbial influences on respiratory infections and the importance of further research to elucidate these relationships.</p
Table_1_Association between oral microbiome and five types of respiratory infections: a two-sample Mendelian randomization study in east Asian population.XLSX
ObjectiveTo explore the causal relationship between the oral microbiome and specific respiratory infections including tonsillitis, chronic sinusitis, bronchiectasis, bronchitis, and pneumonia, assessing the impact of genetic variations associated with the oral microbiome.MethodsMendelian randomization was used to analyze genetic variations, leveraging data from genome-wide association studies in an East Asian cohort to identify connections between specific oral microbiota and respiratory infections.ResultsOur analysis revealed that Prevotella, Streptococcus, Fusobacterium, Pauljensenia, and Capnocytophaga play crucial roles in influencing respiratory infections. Prevotella is associated with both promoting bronchitis and inhibiting pneumonia and tonsillitis, with a mixed effect on chronic sinusitis. Streptococcus and Fusobacterium show varied impacts on respiratory diseases, with Fusobacterium promoting chronic sinusitis, bronchiectasis, and bronchitis. Conversely, Pauljensenia and Capnocytophaga are linked to reduced bronchitis and tonsillitis, and inhibited pneumonia and bronchitis, respectively.DiscussionThese findings underscore the significant impact of the oral microbiome on respiratory health, suggesting potential strategies for disease prevention and management through microbiome targeting. The study highlights the complexity of microbial influences on respiratory infections and the importance of further research to elucidate these relationships.</p
Tandem Solar Cells Using GaAs Nanowires on Si: Design, Fabrication, and Observation of Voltage Addition
Multijunction solar cells provide
us a viable approach
to achieve efficiencies higher than the Shockley–Queisser limit.
Due to their unique optical, electrical, and crystallographic features,
semiconductor nanowires are good candidates to achieve monolithic
integration of solar cell materials that are not lattice-matched.
Here, we report the first realization of nanowire-on-Si tandem cells
with the observation of voltage addition of the GaAs nanowire top
cell and the Si bottom cell with an open circuit voltage of 0.956
V and an efficiency of 11.4%. Our simulation showed that the current-matching
condition plays an important role in the overall efficiency. Furthermore,
we characterized GaAs nanowire arrays grown on lattice-mismatched
Si substrates and estimated the carrier density using photoluminescence.
A low-resistance connecting junction was obtained using n<sup>+</sup>-GaAs/p<sup>+</sup>-Si heterojunction. Finally, we demonstrated tandem
solar cells based on top GaAs nanowire array solar cells grown on
bottom planar Si solar cells. The reported nanowire-on-Si tandem cell
opens up great opportunities for high-efficiency, low-cost multijunction
solar cells
Toward Optimized Light Utilization in Nanowire Arrays Using Scalable Nanosphere Lithography and Selected Area Growth
Vertically aligned, catalyst-free semiconducting nanowires
hold
great potential for photovoltaic applications, in which achieving
scalable synthesis and optimized optical absorption simultaneously
is critical. Here, we report combining nanosphere lithography (NSL)
and selected area metal–organic chemical vapor deposition (SA-MOCVD)
for the first time for scalable synthesis of vertically aligned gallium
arsenide nanowire arrays, and surprisingly, we show that such nanowire
arrays with patterning defects due to NSL can be as good as highly
ordered nanowire arrays in terms of optical absorption and reflection.
Wafer-scale patterning for nanowire synthesis was done using a polystyrene
nanosphere template as a mask. Nanowires grown from substrates patterned
by NSL show similar structural features to those patterned using electron
beam lithography (EBL). Reflection of photons from the NSL-patterned
nanowire array was used as a measure of the effect of defects present
in the structure. Experimentally, we show that GaAs nanowires as short
as 130 nm show reflection of <10% over the visible range of the
solar spectrum. Our results indicate that a highly ordered nanowire
structure is not necessary: despite the “defects” present
in NSL-patterned nanowire arrays, their optical performance is similar
to “defect-free” structures patterned by more costly,
time-consuming EBL methods. Our scalable approach for synthesis of
vertical semiconducting nanowires can have application in high-throughput
and low-cost optoelectronic devices, including solar cells
GaAs Nanowire Array Solar Cells with Axial p–i–n Junctions
Because of unique structural, optical,
and electrical properties,
solar cells based on semiconductor nanowires are a rapidly evolving
scientific enterprise. Various approaches employing III–V nanowires
have emerged, among which GaAs, especially, is under intense research
and development. Most reported GaAs nanowire solar cells form p–n
junctions in the radial direction; however, nanowires using axial
junction may enable the attainment of high open circuit voltage (<i>V</i><sub>oc</sub>) and integration into multijunction solar
cells. Here, we report GaAs nanowire solar cells with axial p–i–n
junctions that achieve 7.58% efficiency. Simulations show that axial
junctions are more tolerant to doping variation than radial junctions
and lead to higher <i>V</i><sub>oc</sub> under certain conditions.
We further study the effect of wire diameter and junction depth using
electrical characterization and cathodoluminescence. The results show
that large diameter and shallow junctions are essential for a high
extraction efficiency. Our approach opens up great opportunity for
future low-cost, high-efficiency photovoltaics
Electrical and Optical Characterization of Surface Passivation in GaAs Nanowires
We report a systematic study of carrier dynamics in Al<sub><i>x</i></sub>Ga<sub>1–<i>x</i></sub>As-passivated
GaAs nanowires. With passivation, the minority carrier diffusion length
(<i>L</i><sub>diff</sub>) increases from 30 to 180 nm, as
measured by electron beam induced current (EBIC) mapping, and the
photoluminescence (PL) lifetime increases from sub-60 ps to 1.3 ns.
A 48-fold enhancement in the continuous-wave PL intensity is observed
on the same individual nanowire with and without the Al<sub><i>x</i></sub>Ga<sub>1–<i>x</i></sub>As passivation
layer, indicating a significant reduction in surface recombination.
These results indicate that, in passivated nanowires, the minority
carrier lifetime is not limited by twin stacking faults. From the
PL lifetime and minority carrier diffusion length, we estimate the
surface recombination velocity (SRV) to range from 1.7 × 10<sup>3</sup> to 1.1 × 10<sup>4</sup> cm·s<sup>–1</sup>, and the minority carrier mobility μ is estimated to lie in
the range from 10.3 to 67.5 cm<sup>2</sup> V<sup>–1</sup> s<sup>–1</sup> for the passivated nanowires