arXiv subjects

Haiwei Li

Publications and source records attributed to Haiwei Li.

10 recordsLinked to original sources

arXiv2023

Aligning Three-Decade Surge in Urban Cooling with Global Warming

Rising demand for space cooling has been placing enormous strain on various technological, environmental, and societal dimensions, resulting in issues related to energy consumption, environmental sustainability, health and well-being, affordability, and equity. Holistic approaches that combine energy efficiency optimization, policy-making, and societal adaptation must be rapidly promoted as viable, timely solutions. We interpret the 30-year upward trend and spikes in urban cooling demand from the perspective of climate change, urbanization, and background climates, focusing on five representative cities: Hong Kong, Sydney, Montreal, Zurich, and London. An unequivocal, worrying upward trend in cooling demand is observed in meteorological data from 1990 to 2021, using cooling degree hours (CDH) as a city-scale metric. The surge in cooling energy demand can be largely attributed to global warming, urban heat islands, and extreme heat events. Further, our quantification of the impact of the base temperature, in relation to the historical CDH, reveals that a 20% energy saving could be achieved instantly within a rather broad range of temperature and humidity by increasing the setpoint temperature by one degree, while characteristic sensational and physiological levels can be maintained at 'acceptable' and 'physiological thermal neutrality' respectively. However, the potential of reducing cooling demand can be nonlinearly and significantly lowered due to the presence of compound high relative humidity and high air temperature. To reduce cooling energy demand rapidly in a warming climate, we highlight the necessity of promoting hard and soft behavioral adaptation along with regulatory intervention for the operation of space cooling systems.

physics.soc-ph↗

arXiv2023

Time-evolving Impact of Trees on Street Canyon Microclimate

Nowadays, cities are frequently exposed to heatwaves, worsening the outdoor thermal comfort and increasing cooling energy demand in summer. Urban forestry is seen as one of the viable and preferable solutions to combating extreme heat events and urban heat island (UHI) in times of climate change. While many cities have initiated tree-planting programmes in recent years, the evolving impact of trees on street microclimate, in a time span of up to several decades, remains unclear. We investigate the cooling effects of linden trees in five groups, i.e., 10-20, 20-30, 30-40, 40-60, and 60-100 years old. The leaf area index (LAI) and leaf area density (LAD) vary nonlinearly as the trees grow, peaking at different ages. Computational fluid dynamics (CFD) simulations solving microclimate are performed for an idealized street canyon with trees of varied age groups. Turbulent airflow, heat and moisture transport, shortwave and longwave radiation, shading and transpiration are fully coupled and solved in OpenFOAM. The meteorological data, including air temperature, wind speed, moisture, and shortwave radiation of the heatwave in Zurich (June 2019), are applied as boundary conditions. The results show that young trees in the age group of 10-20 years old provide little heat mitigation at the pedestrian level in an extreme heat event. Optimal heat mitigation by trees is observed for the group of 30-60 years old trees. Finally, the potential impact of growing trees as a heat mitigation measure on air ventilation is evaluated.

physics.flu-dyn↗

arXiv2023

The time-evolving impact of tree size on nighttime street canyon microclimate: Wind tunnel modeling of aerodynamic effects and heat removal

Urban trees play a crucial role in urban climate in many aspects. However, existing research has not adequately explored the impact from a time-evolving perspective, that is, tree growth over time. To bridge this research gap, this study investigates in a wind tunnel the effects of tree-to-canyon foliage cover and relative height (0.32-1.1 times canyon height), mimicking growth of trees, on conditions in street canyons during moderate and extreme heat. The results reveal that trees may affect canyon-wide ventilation and heat removal in two different scenarios. First, when canyons are in isothermal conditions, medium and large trees, that fill half the canyon height or reach slightly above the canyon, decelerate the shear layer and weaken the vortical flow, as a result reducing the canyon-wide ventilation. Second, in extreme heat conditions, medium and large trees trap heat at the pedestrian level due to the blockage of air entrainment and the suppression of upward buoyancy-driven flow from the ground surface. An air temperature rise that corresponds to 1.5 degree Celsius in a full-scale urban setting is observed in measurements. These observations suggest that urban trees' foliage cover must be managed for a canyon's optimal ventilation and heat removal during nighttime.

physics.flu-dyn↗

arXiv2021

Imaging the atomic-scale electronic states induced by a pair of hole dopants in Ca2CuO2Cl2 Mott insulator

We use scanning tunneling microscopy to visualize the atomic-scale electronic states induced by a pair of hole dopants in Ca2CuO2Cl2 parent Mott insulator of cuprates. We find that when the two dopants approach each other, the transfer of spectral weight from high energy Hubbard band to low energy in-gap state creates a broad peak and nearly V-shaped gap around the Fermi level. The peak position shows a sudden drop at distance around 4 a0 and then remains almost constant. The in-gap states exhibit peculiar spatial distributions depending on the configuration of the two dopants relative to the underlying Cu lattice. These results shed important new lights on the evolution of low energy electronic states when a few holes are doped into parent cuprates.

cond-mat.supr-con↗

arXiv2021

Evolution of Charge and Pair Density Modulations in Overdoped Bi2Sr2CuO6+delta

One of the central issues concerning the mechanism of high temperature superconductivity in cuprates is the nature of the ubiquitous charge order and its implications to superconductivity. Here we use scanning tunneling microscopy to investigate the evolution of charge order from the optimally doped to strongly overdoped Bi2Sr2CuO6+δ cuprates. We find that with increasing hole concentration, the long-range checkerboard order gradually evolves into short-range glassy patterns consisting of diluted charge puddles. Each charge puddle has a unidirectional nematic internal structure, and exhibits clear pair density modulations as revealed by the spatial variations of superconducting coherence peak and gap depth. Both the charge puddles and the nematicity vanish completely in the strongly overdoped non-superconducting regime, when another type of short-range order with root2 * root2 periodicity emerges. These results shed important new lights on the intricate interplay between the intertwined orders and the superconducting phase of cuprates.

cond-mat.supr-con↗

arXiv2020

Machine Learning Identification of Impurities in the STM Images

In this work we train a neural network to identify impurities in the experimental images obtained by the scanning tunneling microscope measurements. The neural network is first trained with large number of simulated data and then the trained neural network is applied to identify a set of experimental images taken at different voltages. We use the convolutional neural network to extract features from the images and also implement the attention mechanism to capture the correlations between images taken at different voltages. We note that the simulated data can capture the universal Friedel oscillation but cannot properly describe the non-universal physics short-range physics nearby an impurity, as well as noises in the experimental data. And we emphasize that the key of this approach is to properly deal these differences between simulated data and experimental data. Here we show that even by including uncorrelated white noises in the simulated data, the performance of neural network on experimental data can be significantly improved. To prevent the neural network from learning unphysical short-range physics, we also develop another method to evaluate the confidence of the neural network prediction on experimental data and to add this confidence measure into the loss function. We show that adding such an extra loss function can also improve the performance on experimental data. Our research can inspire future similar applications of machine learning on experimental data analysis.

cond-mat.str-el↗

arXiv2019

Atomic scale electronic structure of the ferromagnetic semiconductor Cr2Ge2Te6

Cr2Ge2Te6 is an intrinsic ferromagnetic semiconductor with van der Waals type layered structure, thus represents a promising material for novel electronic and spintronic devices. Here we combine scanning tunneling microscopy and first-principles calculations to investigate the electronic structure of Cr2Ge2Te6. Tunneling spectroscopy reveals a surprising large energy level shift and change of energy gap size across the ferromagnetic to paramagnetic phase transition, as well as a peculiar double-peak electronic state on the Cr-site defect. These features can be quantitatively explained by density functional theory calculations, which uncover a close relationship between the electronic structure and magnetic order. These findings shed important new lights on the microscopic electronic structure and origin of magnetic order in Cr2Ge2Te6.

cond-mat.mtrl-sci↗

arXiv2019

Visualizing the periodic modulation of Cooper pairing in a severely underdoped cuprate

A major obstacle in understanding the mechanism of Cooper pairing in the cuprates is the existence of various intertwined orders associated with spin, charge, and Cooper pairs. Of particular importance is the ubiquitous charge order features that have been observed in a variety of cuprates, especially in the underdoped regime of the phase diagram. To explain the origin of the charge order and its implication to the superconducting phase, many theoretical models have been proposed, such as charge stripes, electronic nematicity, and Fermi surface instability. A highly appealing physical picture is the so-called pair density wave (PDW), a periodic modulation of Cooper paring in space, which may also induce a charge order. To elucidate the existence and nature of the PDW order, here we use scanning tunneling microscopy (STM) to investigate a severely underdoped Bi2Sr2CaCu2O8+δ, in which superconductivity just emerges on top of a pronounced checkerboard charge order. By analyzing the spatial distribution of the spectral features characteristic of superconductivity, we observe a periodic modulation of both the superconducting coherence peak and gap depth, demonstrating the existence of a density wave order of Cooper pairing. The PDW order has the same spatial periodicity as the charge order, and the amplitudes of the two orders exhibit clear positive correlation. These results shed important new lights on the origin of and interplay between the charge order and Cooper pairing modulation in the cuprates.

cond-mat.supr-con↗

arXiv2019

Effect of structural supermodulation on superconductivity in tri-layer cuprate Bi2Sr2Ca2Cu3O10+x

We investigate the spatial and doping evolutions of the superconducting properties of tri-layer cuprate Bi2Sr2Ca2Cu3O10+x by using scanning tunneling microscopy and spectroscopy. Both the superconducting coherence peak and gap size exhibit periodic variations with the structural supermodulation, but the effect is much more pronounced in the underdoped regime than at optimal doping. Moreover, a new type of tunneling spectrum characterized by two superconducting gaps emerges with increasing doping, and the two-gap features also correlate with the supermodulation. We propose that the interaction between the inequivalent outer and inner CuO2 planes is responsible for these novel features that are unique to tri-layer cuprates.

cond-mat.supr-con↗

arXiv2018

Superconductivity in Few-Layer Stanene

A single atomic slice of α-tin-stanene-has been predicted to host quantum spin Hall effect at room temperature, offering an ideal platform to study low-dimensional and topological physics. While recent research has intensively focused on monolayer stanene, the quantum size effect in few-layer stanene could profoundly change material properties, but remains unexplored. By exploring the layer degree of freedom, we unexpectedly discover superconductivity in few-layer stanene down to a bilayer grown on PbTe, while bulk α-tin is not superconductive. Through substrate engineering, we further realize a transition from a single-band to a two-band superconductor with a doubling of the transition temperature. In-situ angle resolved photoemission spectroscopy (ARPES) together with first-principles calculations elucidate the corresponding band structure. Interestingly, the theory also indicates the existence of a topologically nontrivial band. Our experimental findings open up novel strategies for constructing two-dimensional topological superconductors.

cond-mat.mtrl-sci↗