The novel coronavirus (COVID-19) pandemic spread globally from its outbreak in China in early 2020, negatively affecting economies and industries on a global scale. In line with historic crises and shock events including the 2002-04 SARS outbreak, the 2011 Christchurch earthquake and 2017 Hurricane Irma, COVID-19 has significantly impacted global economic conditions, causing significant economic downturns, company and industry failures, and increased unemployment. To understand how conditions created by the pandemic to date compare to the aforementioned shock events, we conducted a thorough literature review focusing on the presentation of panic buying and herd mentality behaviours, changes to discretionary consumer spending as defined by Maslow’s Hierarchy of Needs, and the impact of global media on these behaviours. The methodology utilised to analyse panic buying, herd mentality and altered patterns of consumer discretionary spending (according to Maslow’s theory) involved an analysis of consumer spending data, largely focused on Australian and American markets. Here, we analysed the volume and timing of consumer spending patterns; the volumes of spending on specific, highly-demanded consumer goods during the investigative period; and the distribution of spending on luxury and non-durable goods to identify the occurrence of these consumer behaviours. Moreover, to identify the presence of the media in influencing consumer behaviour we focused on web traffic to media sites, alongside keyword and phrase data mining. We conclude that, to date, consumer behaviour during the COVID-19 crisis appears to align with behaviours exhibited during historic shock events. We hope to contribute to the body of research on the early months of this pandemic before longer-term studies are available.

Control over the copy number and nanoscale positioning of quantum dots (QDs) is critical to their application to functional nanomaterials design. However, the multiple non-specific binding sites intrinsic to the surface of QDs have prevented their fabrication into multi-QD assemblies with programmed spatial positions. To overcome this challenge, we developed a general synthetic framework to selectively attach spatially addressable QDs on 3D wireframe DNA origami scaffolds using interfacial control of the QD surface. Using optical spectroscopy and molecular dynamics simulation, we investigated the fabrication of monovalent QDs of different sizes using chimeric single-stranded DNA to control QD surface chemistry. By understanding the relationship between chimeric single-stranded DNA length and QD size, we integrated single QDs into wireframe DNA origami objects and visualized the resulting QD-DNA assemblies using electron microscopy. Using these advances, we demonstrated the ability to program arbitrary 3D spatial relationships between QDs and dyes on DNA origami objects by fabricating energy-transfer circuits and colloidal molecules. Our design and fabrication approach enables the geometric control and spatial addressing of QDs together with the integration of other materials including dyes to fabricate hybrid materials for functional nanoscale photonic devices.

Autonomous computing materials for data storage and computing offer an opportunity for next generation of computing devices. Patchy nanoparticle networks, for example, have been suggested as potential candidates for emulating neuronal networks and performing brain-like computing. Here, we use molecular dynamics (MD) simulations to show that stable dimers, trimers, and tetramers can be built from citrate capped gold nanoparticles (cit-AuNPs) linked by poly(allylamine hydrochloride) (PAH) chains. We use different lengths of PAHs to build polymer-networked nanoparticle assemblies that can emulate a complex neuronal network linked by axons of varying lengths. We find that the tetramer structure can accommodate up to 11 different states when the AuNP pairs are connected by either of two polymer linkers, PAH200 and PAH300. We find that the heavy AuNPs contribute to the assembly’s structure stability. To further illustrate the stability, the AuNP–AuNP distances in dimer, trimer, and tetramer structures are reduced by steering the cit-AuNPs closer to each other. At different distances, these steered structures are all locally stable in a 10 ns MD simulation time scale because of their connection to the AuNPs. We also find that the global potential energy minimum is at short AuNP–AuNP distances where AuNPs collapse because the -NH3+ and –COO− attraction reduces the potential energy. The stability and application of these fundamental structures remain to be further improved through the use of alternative polymer linkers and nanoparticles.

Polymer–nanoparticle networks have potential applications in molecular electronics and nanophononics. In this work, we use all-atom molecular dynamics to reveal the fundamental mechanisms of thermal transport in polymer-linked gold nanoparticle (AuNP) dimers at the molecular level. Attachment of the polymers to AuNPs of varying sizes allows the determination of effects from the flexibility of the chains when their ends are not held fixed. We report heat conductance (G) values for six polymersviz. polyethylene, poly(p-phenylene), polyacene, polyacetylene, polythiophene, and poly(3,4-ethylenedioxythiophene)that represent a broad range of stiffness. We address the multimode effects of polymer type, AuNP size, polymer chain length, polymer conformation, system temperature, and number of linking polymers on G. The combination of the mechanisms for phonon boundary scattering and intrinsic phonon scattering has a strong effect on G. We find that the values of G are larger for conjugated polymers because of the stiffness in their backbones. They are also larger in the low-temperature region for all polymers owing to the quenching of segmental rotations at low temperature. Our simulations also suggest that the total G is additive as the number of linking polymers in the AuNP dimer increases from 1 to 2 to 3.

Materials that exhibit synaptic properties are a key target for our effort to develop computing devices that mimic the brain intrinsically. If successful, they could lead to high performance, low energy consumption, and huge data storage. A 2D square array of engineered nanoparticles (ENPs) interconnected by an emergent polymer network is a possible candidate. Its behavior has been observed and characterized using coarse-grained molecular dynamics (CGMD) simulations and analytical lattice network models. Both models are consistent in predicting network links at varying temperatures, free volumes, and E-field (E⃗) strengths. Hysteretic behavior, synaptic short-term plasticity and long-term plasticity—necessary for brain-like data storage and computing—have been observed in CGMD simulations of the ENP networks in response to E-fields. Non-volatility properties of the ENP networks were also confirmed to be robust to perturbations in the dielectric constant, temperature, and affine geometry.