Electronic systems with physical properties matched to the human epidermis can be used in clinical monitoring.

Gallium Oxide has undergone rapid technological maturation over the last decade, pushing it to the forefront of ultra-wide band gap semiconductor technologies. Maximizing the potential for a new semiconductor system requires a concerted effort by the community to address technical barriers which limit performance. Due to the favorable intrinsic material properties of gallium oxide, namely, critical field strength, widely tunable conductivity, mobility, and melt-based bulk growth, the major targeted application space is power electronics where high performance is expected at low cost. This Roadmap presents the current state-of-the-art and future challenges in 15 different topics identified by a large number of people active within the gallium oxide research community. Addressing these challenges will enhance the state-of-the-art device performance and allow us to design efficient, high-power, commercially scalable microelectronic systems using the newest semiconductor platform.

Different physics-based negative bias temperature instability (NBTI) models as proposed in the literature are reviewed, and the predictive capability of these models is benchmarked against experimental data. Models that focus exclusively on hole trapping in gate-insulator-process-related preexisting traps are found to be inconsistent with direct experimental evidence of interface trap generation. Models that focus exclusively on interface trap generation are incapable of predicting ultrafast measurement data. Models that assume strong correlation between interface trap generation and hole trapping in switching hole traps cannot simultaneously predict long-time dc stress, recovery, and ac stress and cannot estimate gate insulator process impact. Uncorrelated contributions from generation and recovery of interface traps, together with hole trapping and detrapping in preexisting and newly generated bulk insulator traps, are invoked to comprehensively predict dc stress and recovery, ac duty cycle and frequency, and gate insulator process impact of NBTI. The reaction-diffusion model can accurately predict generation and recovery of interface traps for different devices and experimental conditions. Hole trapping/detrapping is modeled using a two-level energy well model.

Recent advances in experimental techniques (on-the- fly and ultrafast techniques) allow measurement of threshold voltage degradation due to negative-bias temperature instability (NBTI) over many decades in timescale. Such measurements over wider temperature range (-25degC to 145degC), film thicknesses (1.2-2.2 nm of effective oxide thickness), and processing conditions (variation of nitrogen within gate dielectric) provide an excellent framework for a theoretical analysis of NBTI degradation. In this paper, we analyze these experiments to refine the existing theory of NBTI to 1) explore the mechanics of time transients of NBTI over many orders of magnitude in time; 2) establish field dependence of interface trap generation to resolve questions regarding the appropriateness of power law versus exponential projection of lifetimes; 3) ascertain the relative contributions to NBTI from interface traps versus hole trapping as a function of processing conditions; and 4) briefly discuss relaxation dynamics for fast-transient NBTI recovery that involves interface traps and trapped holes.

Human health and performance monitoring (HHPM) is imperative to provide information necessary for protecting, sustaining, evaluating, and improving personnel in various occupational sectors, such as industry, academy, sports, recreation, and military. While various commercially wearable sensors are on the market with their capability of “quantitative assessments” on human health, physical, and psychological states, their sensing is mostly based on physical traits, and thus lacks precision in HHPM. Minimally or noninvasive biomarkers detectable from the human body, such as body fluid (e.g., sweat, tear, urine, and interstitial fluid), exhaled breath, and skin surface, can provide abundant additional information to the HHPM. Detecting these biomarkers with novel or existing sensor technologies is emerging as critical human monitoring research. This review provides a broad perspective on the state of the art biosensor technologies for HHPM, including the list of biomarkers and their physiochemical/physical characteristics, fundamental sensing principles, and high‐performance sensing transducers. Further, this paper expands to the additional scope on the key technical challenges in applying the current HHPM system to the real field.