The development of planar high-K/III-V p-channel MOSFETs for post-silicon CMOS

Conventional Si complementary-metal-oxide-semiconductor (CMOS) scaling is fast approaching its limits. The extension of the logic device roadmap for future enhancements in transistor performance requires non-Si materials and new device architectures. III-V materials, due to their superior electron transport properties, are well poised to replace Si as the channel material beyond the 10nm technology node to mitigate the performance loss of Si transistors from further reductions in supply voltage to minimise power dissipation in logic circuits. However several key challenges, including a high quality dielectric/III-V gate stack, a low-resistance source/drain (S/D) technology, heterointegration onto a Si platform and a viable III-V p-metal-oxide-semiconductor field-effect-transistor (MOSFET), need to be addressed before III-Vs can be employed in CMOS. This Thesis specifically addressed the development and demonstration of planar III-V p-MOSFETs, to complement the n-MOSFET, thereby enabling an all III-V CMOS technology to be realised. This work explored the application of InGaAs and InGaSb material systems as the channel, in conjunction with Al2O3/metal gate stacks, for p-MOSFET development based on the buried-channel flatband device architecture. The body of work undertaken comprised material development, process module development and integration into a robust fabrication flow for the demonstration of p-channel devices. The parameter space in the design of the device layer structure, based around the III-V channel/barrier material options of In_x≥0.53Ga_1-xAs/In_0.52Al_0.48As and In_x≥0.1Ga_1-xSb/AlSb, was systematically examined to improve hole channel transport. A mobility of 433 cm²/Vs, the highest room temperature hole mobility of any InGaAs quantum-well channel reported to date, was obtained for the In_0.85Ga_0.15As (2.1% strain) structure. S/D ohmic contacts were developed based on thermally annealed Au/Zn/Au metallisation and validated using transmission line model test structures. The effects of metallisation thickness, diffusion barriers and de-oxidation conditions were examined. Contacts to InGaSb-channel structures were found to be sensitive to de-oxidation conditions. A fabrication process, based on a lithographically-aligned double ohmic patterning approach, was realised for deep submicron gate-to-source/drain gap (L_side) scaling to minimise the access resistance, thereby mitigating the effects of parasitic S/D series resistance on transistor performance. The developed process yielded gaps as small as 20nm. For high-k integration on GaSb, ex-situ ammonium sulphide ((NH₄)₂S) treatments, in the range 1%-22%, for 10min at 295K were systematically explored for improving the electrical properties of the Al₂O₃/GaSb interface. Electrical and physical characterisation indicated the 1% treatment to be most effective with interface trap densities in the range of 4 - 10×10¹²cm^-2eV^-1 in the lower half of the bandgap. An extended study, comprising additional immersion times at each sulphide concentration, was further undertaken to determine the surface roughness and the etching nature of the treatments on GaSb. A number of p-MOSFETs based on III-V-channels with the most promising hole transport and integration of the developed process modules were successfully demonstrated in this work. Although the non-inverted InGaAs-channel devices showed good current modulation and switch-off characteristics, several aspects of performance were non-ideal; depletion-mode operation, modest drive current (I_d,sat=1.14mA/mm), double peaked transconductance (g_m=1.06mS/mm), high subthreshold swing (SS=301mV/dec) and high on-resistance (R_on=845kΩ.μm). Despite demonstrating substantial improvement in the on-state metrics of I_d,sat (11×), g_m (5.5×) and R_on (5.6×), inverted devices did not switch-off. Scaling gate-to-source/drain gap (L_side) from 1μm down to 70nm improved I_d,sat (72.4mA/mm) by a factor of 3.6 and gm (25.8mS/mm) by a factor of 4.1 in inverted InGaAs-channel devices. Well-controlled current modulation and good saturation behaviour was observed for InGaSb-channel devices. In the on-state In_0.3Ga_0.7Sb-channel (I_d,sat=49.4mA/mm, g_m=12.3mS/mm, R_on=31.7kΩ.μm) and In_0.4Ga_0.6Sb-channel (I_d,sat=38mA/mm, g_m=11.9mS/mm, R_on=73.5kΩ.μm) devices outperformed the InGaAs-channel devices. However the devices could not be switched off. These findings indicate that III-V p-MOSFETs based on InGaSb as opposed to InGaAs channels are more suited as the p-channel option for post-Si CMOS.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.