Interface Trap Density Metrology of state-of-the-art undoped Si n-FinFETs

The presence of interface states at the MOS interface is a well-known cause of device degradation. This is particularly true for ultra-scaled FinFET geometries where the presence of a few traps can strongly influence device behavior. Typical methods for interface trap density (Dit) measurements are not performed on ultimate devices, but on custom designed structures. We present the first set of methods that allow direct estimation of Dit in state-of-the-art FinFETs, addressing a critical industry need.Comment: 9 pages, 4 figures, *G.C.T. and A.P. contributed equally to this wor

Probing the quantum states of a single atom transistor at microwave frequencies

The ability to apply gigahertz frequencies to control the quantum state of a single P atom is an essential requirement for the fast gate pulsing needed for qubit control in donor-based silicon quantum computation. Here, we demonstrate this with nanosecond accuracy in an all epitaxial single atom transistor by applying excitation signals at frequencies up to ≈13 GHz to heavily phosphorus-doped silicon leads. These measurements allow the differentiation between the excited states of the single atom and the density of states in the one-dimensional leads. Our pulse spectroscopy experiments confirm the presence of an excited state at an energy ≈9 meV, consistent with the first excited state of a single P donor in silicon. The relaxation rate of this first excited state to the ground state is estimated to be larger than 2.5 GHz, consistent with theoretical predictions. These results represent a systematic investigation of how an atomically precise single atom transistor device behaves under radio frequency excitations

MEDTEC Students against Coronavirus: Investigating the Role of Hemostatic Genes in the Predisposition to COVID-19 Severity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. Besides virus intrinsic characteristics, the host genetic makeup is predicted to account for the extreme clinical heterogeneity of the disease, which is characterized, among other manifestations, by a derangement of hemostasis associated with thromboembolic events. To date, large-scale studies confirmed that genetic predisposition plays a role in COVID-19 severity, pinpointing several susceptibility genes, often characterized by immunologic functions. With these premises, we performed an association study of common variants in 32 hemostatic genes with COVID-19 severity. We investigated 49,845 single-nucleotide polymorphism in a cohort of 332 Italian severe COVID-19 patients and 1668 controls from the general population. The study was conducted engaging a class of students attending the second year of the MEDTEC school (a six-year program, held in collaboration between Humanitas University and the Politecnico of Milan, allowing students to gain an MD in Medicine and a Bachelor’s Degree in Biomedical Engineering). Thanks to their willingness to participate in the fight against the pandemic, we evidenced several suggestive hits (p < 0.001), involving the PROC, MTHFR, MTR, ADAMTS13, and THBS2 genes (top signal in PROC: chr2:127192625:G:A, OR = 2.23, 95%CI = 1.50–3.34, p = 8.77 × 10−5). The top signals in PROC, MTHFR, MTR, ADAMTS13 were instrumental for the construction of a polygenic risk score, whose distribution was significantly different between cases and controls (p = 1.62 × 10−8 for difference in median levels). Finally, a meta-analysis performed using data from the Regeneron database confirmed the contribution of the MTHFR variant chr1:11753033:G:A to the predisposition to severe COVID-19 (pooled OR = 1.21, 95%CI = 1.09–1.33, p = 4.34 × 10−14 in the weighted analysis)