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Abstract The rational design of the electronic band structures and the associated properties (e.g. optical) of advanced materials has remained challenging for crucial applications in optoelectronics, solar desalination, advanced manufacturing technologies, etc. In this work, using first-principles calculations, we studied the prospects of tuning the absorption spectra of graphene via defect engineering, i.e. chemical doping and oxidation. Our computational analysis shows that graphene functionalization with single hydroxyl and carboxylic acid fails to open a band gap in graphene. While single epoxide functionalization successfully opens a bandgap in graphene and increases absorptivity, however, other optical properties such as reflection, transmission, and dielectric constants are significantly altered. Boron and nitrogen dopants lead to p- and n-type doping, respectively, while fluorine dopants or a single-carbon atomic vacancy cannot create a significant bandgap in graphene. By rigorously considering the spin-polarization effect, we find that titanium, zirconium, and hafnium dopants can create a bandgap in graphene via an induced flat band around the Fermi level as well as the collapse of the Dirac cone. In addition, silicon, germanium, and tin dopants are also effective in improving the optical characteristics. Our work is important for future experimental work on graphene for laser and optical processing applications. 

Graphene with in-plane nanoholes, named holey graphene, shows great potential in electrochemical applications due to its fast mass transport and improved electrochemical activity. Scalable nanomanufacturing of holey graphene is generally based on chemical etching using hydrogen peroxide to form through-the-thickness nanoholes on the basal plane of graphene. In this study, we probe into the fundamental mechanisms of nanohole formation under peroxide etching via an integrated experimental and computational effort. The research results show that the growth of nanoholes during the etching of graphene oxide is achieved by a three-stage reduction–oxidation–reduction procedure. First, it is demonstrated that vacancy defects are formed via a partial reduction-based pretreatment. Second, hydrogen peroxide reacts preferentially with the edge-sites of defect areas on graphene oxide sheets, leading to the formation of various oxygen-containing functional groups. Third, the carbon atoms around the defects are removed along with the neighboring carbon atoms via reduction. By advancing the understanding of process mechanisms, we further demonstrate an improved nanomanufacturing strategy, in which graphene oxide with a high density of defects is introduced for peroxide etching, leading to enhanced nanohole formation. 

Nanodiamonds (NDs) have been widely explored for applications in drug delivery, optical bioimaging, sensors, quantum computing, and others. Room-temperature nanomanufacturing of NDs in open air using confined laser shock detonation (CLSD) emerges as a novel manufacturing strategy for ND fabrication. However, the fundamental process mechanism remains unclear. This work investigates the underlying mechanisms responsible for nanomanufacturing of NDs during CLSD with a focus on the laser-matter interaction, the role of the confining effect, and the graphite-to-diamond transition. Specifically, a first-principles model is integrated with a molecular dynamics simulation to describe the laser-induced thermo-hydrodynamic phenomena and the graphite-to-diamond phase transition during CLSD. The simulation results elucidate the confining effect in determining the material’s responses to laser irradiation in terms of the temporal and spatial evolutions of temperature, pressure, electron number density, and particle velocity. The integrated model demonstrates the capability of predicting the laser energy threshold for ND synthesis and the efficiency of ND nucleation under varying processing parameters. This research will provide significant insights into CLSD and advance this nanomanufacturing strategy for the fabrication of NDs and other high-temperature-high-pressure synthesized nanomaterials towards extensive applications.

 

Additively manufactured stainless steels have become increasingly popular due to their desirable properties, but their mechanical behavior in structural parts is not yet fully understood. Specifically, the impact of columnar microstructures on fatigue behavior is still unclear. A typical directed energy deposition (DED)‐fabricated 316L stainless steel microstructure consists of distinct zones with equiaxed and columnar grains. To answer the question of how these zones of a DED‐fabricated 316L stainless steel microstructure affect the local mechanical behavior individually, such as the fatigue strength, stress/strain distribution, and fatigue life, crystal plasticity simulations are conducted to investigate the influence of microstructure on local mechanical behavior such as fatigue strength, stress/strain distribution, and fatigue life. The simulations find that columnar microstructures exhibit better fatigue strength than equiaxed structures when the load is parallel to the major axis of the columnar grains, but the strength decreases when the load is perpendicular. This study also uses machine learning to predict fatigue life, which shows good agreement with crystal plasticity modeling. The study suggests that the combined crystal plasticity–machine learning approach is an effective way to predict the fatigue behavior of additively manufactured components.

 

In this paper, we examine the development of tailored 3D-structured (engineered) polymer-metal interfaces to create enhanced ionic polymer-metal composite (eIPMC) sensors towards soft, self-powered, high sensitivity strain sensor applications. First, a physics-based chemoelectromechanical model is developed to predict the sensor behavior of eIPMCs by incorporating structure microfeature effects in the mechanical response of the material. The model incorporates electrode surface properties, such as microscale feature thickness, size and spacing, to help define the mechanical response and transport characteristics of the polymer-electrode interface. Second, two novel approaches are described to create functional samples of eIPMC sensors using fused deposition manufacturing and inkjet printing technologies. Sample eIPMC sensors are fabricated for experimental characterization. Finally, experimental results are provided to show superior performance in the sensing capabilities compared to traditional sensors fabricated from sheet-form material. The results also validate important predictive aspects of the proposed minimal model.