University of Macau

Conditions mapped for the first time of polaron characteristics in 2D materials. TACC's Frontera supercomputer generated quantum mechanical calculations on hexagonal boron nitride system of 30,000 atoms. A new leaf has turned in scientists' hunt for developing cutting-edge materials used in organic light-emitting diode (OLED) TV's, touchscreens, and more. The advance involves the polaron, a quasiparticle consisting of an electron and its surrounding distortions of atoms in a crystal lattice. Simulations on the Texas Advanced Computing Center's (TACC) Frontera supercomputer have helped scientists map for the first time the conditions that characterize polarons in 2D materials, the thinnest materials that have ever been made. "We charted a map to indicate in which materials polarons should be found, under what conditions, and the characteristics of their properties," said Feliciano Giustino, professor of Physics and the W. A. 'Tex' Moncrief, Jr. Chair of Quantum Materials Engineering at the Oden Institute for Computational Engineering and Sciences (Oden Institute) and the Department of Physics, College of Natural Sciences, The University of Texas at Austin. Understanding polarons can help improve the performance and efficiency of devices such as touchscreens for phones and tablets, and the organic light-emitting diodes of OLED TVs, which rely on electric charge transport through polarons. What's more, generating hydrogen fuel from the splitting of water by sunlight is considered the 'holy grail' of energy science, a process which can be achieved through charge transport from polarons in key materials such as titanium dioxide. Giustino is the lead author on work published February 2023 in Nature Physics. In it, he and study co-author Weng Hong Sio of the Oden Institute and the University of Macau determined the fundamental properties of polarons in 2D materials using quantum mechanical theory and computation. Little has been known about polarons in 2D materials, until now. Polarons have been well-studied theoretically over the past 100 years, and characterized experimentally for three-dimensional bulk solids. Giustino and Sio focused on atomically-thin crystal monolayers of hexagonal boron nitride (h-BN) on graphene as a case study, where polarons were computed and compared in the bulk crystal and in the monolayer. Next, they created a generalized model of polarons in 2D materials. "Our aim was to understand where one can find polarons in two dimensions, and what are their properties. To do this, we used a new computational method that we developed," Giustino said. Giustino at the Oden Institute invented EPW, an open-source Fortran and message passing interface (MPI) code that calculates properties related to electron-phonon interaction using Density-Functional Perturbation Theory and Maximally Localized Wannier Functions. This code is currently developed by an international collaboration led by the Oden Institute. "We used supercomputers to perform the calculations, primarily those of DOE (Argonne Leadership Computing Facility and National Energy Research Scientific Computing) as well as Frontera at TACC. EPW is something that we optimized very heavily on Frontera," Giustino said. During TACC's Texascale Days, Giustino was awarded access to the full machine, allowing his group to perform full system runs on all 448,000 CPU cores of Frontera. "Thanks to DOE support, we've been refactoring the EPW for exascale computing over the past 4 years," Giustino said. "TACC's Frontera supercomputer has helped us with this effort. We managed to refactor the EPW code to achieve 92% of ideal scaling. The ability to access the entire machine within Texascale Days has been absolutely critical to bring us to where we are now with the code." TACC's Frontera supercomputer, funded by the National Science Foundation (NSF), is the most powerful academic system in the U.S. Frontera's Characteristic Science Applications (CSA) program is part of the planning and early science program for the NSF's Leadership-Class Computing Facility (LCCF), which will be 10 times as powerful as Frontera. "TACC provided us with the opportunity to develop the codes on full scale systems that has not been possible anywhere else," Giustino said. His EPW code is one of 21 CSA projects selected by TACC to be benchmarked and optimized for the LCCF -- these latest polaron simulations are linked with Giustino's CSA project. What's more, Giustino continues his strong collaboration with TACC through a recent grant to develop software to design new materials, awarded from the NSF Office for Advanced Cyberinfrastructure through the Cyberinfrastructure for Sustained Scientific Innovation (CSSI) program. The grant will fund the development of software to design new materials. The Department of Energy (DOE) funded Giustino's latest work with polarons under the DOE Office of Science, Basic Energy Sciences, Computational Materials Sciences award no. DE-SC0020129. "The National Energy Research Scientific Computing Center (NERSC) has provided the main resources that we use for this DOE project. We ran a significant fraction of our calculations on the Cori and Perlmuttersupercomputers at NERSC," Giustino said. The calculations pertain to the formation energies, wave functions, and atomic displacements of polarons, a quantum wave packet consisting of an electron "dressed" by a cloud of atomic vibrations. Electrons alone behave like delocalized waves, and polarons behave differently in that the wave packet jumps from one lattice site to another. "This 'hopping transport' regime confers the material with novel properties and has implications on the design of materials for electronics," Giustino said. The packet extends over 10 nanometers, encompassing about 30,000 atoms of boron and nitrogen, considering all the interactions between atoms. This kind of calculation isn't possible currently using standard density functional theory methods. "We recast this problem into the solution of a very large nonlinear eigenvalue problem. Then we used supercomputers to solve this gigantic linear algebra problem," Giustino said. "We believe that with these new methods that we developed through the EPW code, we are now capitalizing on and supporting experimental data and see new directions in materials design," he added. Said Giustino: "The materials that we know today are just a tiny fraction of what is possible. Supercomputers are key to exploring this valuable and gigantic space without having to first invest billions into experimental synthesis and material characterization. Computation gives scientists a first pass to more easily see what is possible, something which I strongly advocate for and want the U.S. to maintain leadership in materials research through sustained support for high performance computing."

A new online Hong Kong COVID-19 Hotspot Map has gone live which provides a visualisation of the real-time and dynamic geographic distribution of COVID-19 cases in the city. The interactive map was developed by a research team led by Hong Kong Baptist University (HKBU), along with the University of Macau and The University of Hong Kong. WHAT IT'S ABOUT The map presents territory-wide data on COVID-19 infection cases. Its real-time data comes from the Interactive Map Dashboard run by the Hong Kong government. It shows infection risks in different locations in a colour scheme ranging from purple for the lowest risk level to red for the highest. Evolving risk levels in each location are presented through a dynamic movement of colour patterns on the map. Moreover, users can zoom in or zoom out to browse COVID-19 risk levels at broader or more specific geographical sites. The colour visualisation of COVID-19 risk levels is based on the automatic, real-time updating and computation of infection case data using a computational tool for spatial-temporal data analysis called Kernel Density Visualisation (KDV). Using the new computation methods, the hotspot map's resolution can be increased to a high-definition resolution (1376 x 960 pixels). It can also process one million data points in less than 0.5 second of response time. WHY IT MATTERS Having timely and accurate information on the geographic distribution of COVID-19 cases is key to the implementation of effective infection control measures, as well as the allocation of medical resources to fight the pandemic. This information is also useful to the public in understanding health risks. Thus, developing a system that can update and process high-resolution images timely is also important in this endeavour. However, many existing visualisation software tools cannot support high-resolution KDV with million-scale datasets. Moreover, current computation methods of conventional KDV cannot support the real-time creation of dynamic images. To address this need, the research team developed new computation methods to enhance the KDV's visual creation. Experiments with these novel methods have shown response time to be 100 times faster than most advanced methods currently available. THE LARGER TREND The launch of the interactive COVID-19 map comes as Hong Kong is seeing an increase in daily cases over the past two weeks, going above the 8,000 mark from 5,000 earlier. The city has recently relaxed social distancing protocols in a bid to further reopen its economy. In August, the Hong Kong University of Science and Technology unveiled its CovidInArea mobile app which also visualises COVID-19 risks. It uses open data from the Department of Health to generate a real-time heatmap of places where COVID-19 cases are reported. Available on both Android and iOS devices, the app runs an automatic check of COVID-19 hotspots by providing real-time GPS support. No user registration is required to access the mobile map and no personal information is also collected. ON THE RECORD "The newly developed algorithms and solutions can support more KDV-based geospatial analysis tasks. With their application, the functionalities of the Hong Kong COVID-19 Hotspot Map were greatly enhanced, making it a useful tool to monitor the risks of COVID-19 in the community. It can assist health authorities as well as individual citizens in introducing informed, effective measures against the pandemic," said Xu Jianliang, research lead and professor and head of the Department of Computer Science at HKBU. The research team is also looking to apply its new computation methods for KDV in traffic hotspot detection, crowd control in tourist attractions, property prices visual analysis and real-time weather resources management.