468 research outputs found
Reversible water uptake and release of pseudo-cubic type La0.7Sr0.3Mn1- xNixO3 at intermediate temperatures
Solid oxide fuel cells (SOFCs) based on oxide-ion conducting electrolytes possess several attractive advantages such as high energy conversion, low pollutant emission and fuel flexibility. However, SOFCs suffer from the high operating temperatures 800-1000 °C; such high temperature operations result in the increase of costs and lessened lifetimes of materials. Hence, there exists a strong demand to decrease the working temperature into intermediate temperature (IT) region below 600 °C. Proton conducting ceramic fuel cells (PCFCs) is a kind of promising IT-fuel cells operating at around 400-600 °C because of lower activation energies of proton conductivity than oxide-ion conductivity. Recently Choi et al [1] reported that PCFC with BaZr0.4Ce0.4Y0.1Yb0.1O3 electrolyte exceeds 500 mW cm-2 at 500 °C, however, the performance still lags far behind the predicted values that is over 1.0 W cm-2 at 500°C. There are two major challenges, one is big ohm resistance of Zr-rich Ba(Zr, Ce, Y)O3 (BZCY) electrolyte, and the other one is lack of highly efficient cathode specially designed for PCFCs [2]. Since most of the cobaltite base cathodes are oxide-ion conductors, the mismatch of main ionic carriers between cathode and electrolytes limits the efficient cathodic reaction area into cathode-electrolyte-gas triple boundaries. Hence, it is motivated to develop cathode catalysts which exhibit sufficient proton conductivity in order to extend the efficient reaction zone and thus reduce cathode overpotentials and finally increase reaction efficiency. The protonic defects are incorporated into oxides via hydration reaction, whereas, many oxides do not have enough large hydration enthalpy [3-5] and thus, the reaction is less-pronounced at elevated temperatures.
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When Mining Electric Locomotives Meet Reinforcement Learning
As the most important auxiliary transportation equipment in coal mines,
mining electric locomotives are mostly operated manually at present. However,
due to the complex and ever-changing coal mine environment, electric locomotive
safety accidents occur frequently these years. A mining electric locomotive
control method that can adapt to different complex mining environments is
needed. Reinforcement Learning (RL) is concerned with how artificial agents
ought to take actions in an environment so as to maximize reward, which can
help achieve automatic control of mining electric locomotive. In this paper, we
present how to apply RL to the autonomous control of mining electric
locomotives. To achieve more precise control, we further propose an improved
epsilon-greedy (IEG) algorithm which can better balance the exploration and
exploitation. To verify the effectiveness of this method, a co-simulation
platform for autonomous control of mining electric locomotives is built which
can complete closed-loop simulation of the vehicles. The simulation results
show that this method ensures the locomotives following the front vehicle
safely and responding promptly in the event of sudden obstacles on the road
when the vehicle in complex and uncertain coal mine environments
Manganese oxide base electrocatalysts for proton-conducting ceramic cells
There has been a strong interest in clean and renewable energy sources due to finite fossil fuel sources, increasing oil prices and environmental concerns. Hydrogen is regarded as the leading candidate fuel, because it releases only H2O during combustion and it is compatible to use in high efficiency fuel system. Steam reforming of hydrocarbon gas is currently the main way to produce hydrogen but still relies on fossil fuel consumption. On the contrary, water electrolysis using electric power generated by renewable energy is attracted as sustainable hydrogen production method. Especially, steam electrolysis using solid electrolyte cells is promising for efficient hydrogen production because high-temperature heat partly offers the energy for water electrolysis, leading favorable kinetics and thermodynamics. Hence, it is motivated to investigate on solid oxide electrolysis cell (SOEC) using proton-conducting ceramics to achieve highly efficient conversion from electrical power into chemical fuel gas directly. However, sufficient performance has not be achieved yet in the current system because large overpotential is needed for oxygen evolution reaction at anode owing to the relatively slow kinetics and the limited active zone in the anode/electrolyte interfaces due to the mismatch of ionic carries, Accordingly, it is a great challenge to develop high performance oxygen electrode with efficient electrocatalytic ability for 4 electron transfer oxygen evolution reaction.
Recently, it is reported that high valence state metal oxide reveal superior electrocatalytic activity for water oxidation s because the energy levels between the occupied metal orbital and the O 2p orbital are very close, causing a strong hybridization and facilitating o-o bond formation. Herein, we examined electrocatalytic performance of high valence state Mn(V) oxide Ba3(MnO4)2 as an anode for SOEC This oxide has been reported to be very stable at elevated temperatures in oxidative conditions. Proton-conducting BaZr0.4Ce0.4Y0.2O3-δ (BZCY) was used as proton conducting electrolyte. Bulk electrolyte cell were constructed with a BZCY disc which were prepared by solid state reactive sintering (SSRS) method. The electrolyte precursor powder was prepared by mixing proper amount of BaCO3, CeO2, ZrO2, and Y2O3 according to the desired stoichiometry with the addition of 1.0wt.% NiO as a sintering aid. This mixture was ball-milled for 48 h and uniaxially pressed under 20 MPa for 1 min and then cold-isostatic-pressed under 100 MPa for 1 min. Finally, green pellets were calcined at 1500°C for 10 h so as to obtain dense electrolyte disc (2 mmd, 9 mmf)Pt paste was applied at one side of the surface as a cathode. LSCF or LSCF/Ba3(MnO4)2 mixed ink were screen-printed at the other side of the surface as anode materials. Samples are evaluated by XRD and XAS. The electrochemical impedance spectroscopy and I-V measurements were carried out to evaluate the SOEC properties.
Two kinds of anode materials were examined in this research, namely, the cell-1: Pt | BZCY | LSCF and cell-2: Ba3(MnO4)2/LSCF mixed anode cell. The cell-2 showed superior steam electrolytic performance compared to cell-1. The current density of steam electrolysis of cell-2 was 145 mA cm-2 meanwhile cell-1 was 145 mA cm-2 in bias voltage of 1.5 V at 600°C. Impedance spectroscopy was conducted to evaluate the anodic polarization resistance. LSCF anode gives 6 Ω cm2, however, the Ba3(MnO4)2/LSCF composite anode gives 3 Ω cm2. Furthermore, the spectral features were completely different between both. The spectrum of LSCF anode had three semi-circles: high frequency arc (10x-10y Hz), middle frequency arc (10zz-10zy Hz) and low frequency arc (10zz-10zy Hz). On the other hand, Ba3(MnO4)2/LSCF involves only two semi-circles: high frequency arc (10x-10y Hz) and low frequency arc (10zz-10zy Hz). These results indicate Ba3(MnO4)2 changes the reaction pathway of water oxidation electrode/solid electrolyte interface. .The oxygen evolution rate was measured by gas chromatography when electrolysis was performed at a constant current density of 100 mA, 200 mA, and 300 mA. The flax of oxygen from anode side is corresponded to that of calculated from the current density, indicating that the faradaic efficiency was almost 100%. XRD pattern of the sample after electrolysis showed that there were no secondary phases, indicating stability of Ba3(MnO4)2 is enough to use in SOEC anodic condition. The above results suggest the Ba3(MnO4)2 is promising for OER electrocatalysts for SOEC
Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection
While the voxel-based methods have achieved promising results for
multi-person 3D pose estimation from multi-cameras, they suffer from heavy
computation burdens, especially for large scenes. We present Faster VoxelPose
to address the challenge by re-projecting the feature volume to the three
two-dimensional coordinate planes and estimating X, Y, Z coordinates from them
separately. To that end, we first localize each person by a 3D bounding box by
estimating a 2D box and its height based on the volume features projected to
the xy-plane and z-axis, respectively. Then for each person, we estimate
partial joint coordinates from the three coordinate planes separately which are
then fused to obtain the final 3D pose. The method is free from costly 3D-CNNs
and improves the speed of VoxelPose by ten times and meanwhile achieves
competitive accuracy as the state-of-the-art methods, proving its potential in
real-time applications.Comment: 22 pages, 7 figures, submitted to ECCV 202
Multiple View Geometry Transformers for 3D Human Pose Estimation
In this work, we aim to improve the 3D reasoning ability of Transformers in
multi-view 3D human pose estimation. Recent works have focused on end-to-end
learning-based transformer designs, which struggle to resolve geometric
information accurately, particularly during occlusion. Instead, we propose a
novel hybrid model, MVGFormer, which has a series of geometric and appearance
modules organized in an iterative manner. The geometry modules are
learning-free and handle all viewpoint-dependent 3D tasks geometrically which
notably improves the model's generalization ability. The appearance modules are
learnable and are dedicated to estimating 2D poses from image signals
end-to-end which enables them to achieve accurate estimates even when occlusion
occurs, leading to a model that is both accurate and generalizable to new
cameras and geometries. We evaluate our approach for both in-domain and
out-of-domain settings, where our model consistently outperforms
state-of-the-art methods, and especially does so by a significant margin in the
out-of-domain setting. We will release the code and models:
https://github.com/XunshanMan/MVGFormer.Comment: 14 pages, 8 figure
Topological Transformation and Free-Space Transport of Photonic Hopfions
Structured light fields embody strong spatial variations of polarisation,
phase and amplitude. Understanding, characterization and exploitation of such
fields can be achieved through their topological properties. Three-dimensional
(3D) topological solitons, such as hopfions, are 3D localized continuous field
configurations with nontrivial particle-like structures, that exhibit a host of
important topologically protected properties. Here, we propose and demonstrate
photonic counterparts of hopfions with exact characteristics of Hopf fibration,
Hopf index, and Hopf mapping from real-space vector beams to homotopic
hyperspheres representing polarisation states. We experimentally generate
photonic hopfions with on-demand high-order Hopf indices and independently
controlled topological textures, including N\'eel-, Bloch-, and anti-skyrmionic
types. We also demonstrate a robust free-space transport of photonic hopfions,
thus, showing potential of hopfions for developing optical topological
informatics and communications
Observation of topology transition in Floquet non-Hermitian skin effects in silicon photonics
Non-Hermitian physics has greatly enriched our understanding of
nonequilibrium phenomena and uncovered novel effects such as the non-Hermitian
skin effect (NHSE) that has profoundly revolutionized the field. NHSE is
typically predicted in systems with nonreciprocal couplings which, however, are
difficult to realize in experiments. Without nonreciprocal couplings, the NHSE
can also emerge in systems with coexisting gauge fields and loss or gain (e.g.,
in Floquet non-Hermitian systems). However, such Floquet NHSE remains largely
unexplored in experiments. Here, we realize the Floquet NHSEs in periodically
modulated optical waveguides integrated on a silicon photonics platform. By
engineering the artificial gauge fields induced by the periodical modulation,
we observe various Floquet NHSEs and unveil their rich topological transitions.
Remarkably, we discover the transitions between the normal unipolar NHSEs and
an unconventional bipolar NHSE which is accompanied by the directional reversal
of the NHSEs. The underlying physics is revealed by the band winding in complex
quasienergy space which undergoes a topology change from isolated loops with
the same winding to linked loops with opposite windings. Our work unfolds a new
route toward Floquet NHSEs originating from the interplay between gauge fields
and dissipation effects and offers fundamentally new ways for steering light
and other waves.Comment: 12 pages, 3 figure
GAIA: Zero-shot Talking Avatar Generation
Zero-shot talking avatar generation aims at synthesizing natural talking
videos from speech and a single portrait image. Previous methods have relied on
domain-specific heuristics such as warping-based motion representation and 3D
Morphable Models, which limit the naturalness and diversity of the generated
avatars. In this work, we introduce GAIA (Generative AI for Avatar), which
eliminates the domain priors in talking avatar generation. In light of the
observation that the speech only drives the motion of the avatar while the
appearance of the avatar and the background typically remain the same
throughout the entire video, we divide our approach into two stages: 1)
disentangling each frame into motion and appearance representations; 2)
generating motion sequences conditioned on the speech and reference portrait
image. We collect a large-scale high-quality talking avatar dataset and train
the model on it with different scales (up to 2B parameters). Experimental
results verify the superiority, scalability, and flexibility of GAIA as 1) the
resulting model beats previous baseline models in terms of naturalness,
diversity, lip-sync quality, and visual quality; 2) the framework is scalable
since larger models yield better results; 3) it is general and enables
different applications like controllable talking avatar generation and
text-instructed avatar generation.Comment: ICLR 2024. Project page: https://microsoft.github.io/GAIA
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