Boron carbide is characterized by a unique combination of properties that make it a material of choice for a wide range of engineering applications. Boron carbide is used in refractory applications due to its high melting point and thermal stability; it is used as abrasive powders and coatings due to its extreme abrasion resistance; it excels in ballistic performance due to its high hardness and low density; and it is commonly used in nuclear applications as neutron radiation absorbent. In addition, boron carbide is a high temperature semiconductor that can potentially be used for novel electronic applications. This paper provides a comprehensive review of the recent advances in understanding of structural and chemical variations in boron carbide and their influence on electronic, optical, vibrational, mechanical, and ballistic properties. Structural instability of boron carbide under high stresses associated with external loading and the nature of the resulting disordered phase are also discussed.

Carbon, which is often used as an additive to silicon carbide powder, is thought to facilitate densification during sintering by aiding the removal of the native SiO2 layer, which is present on the starting SiC powder. The mechanism is the reduction of SiO2 to SiC with the formation of primarily CO gas, which diffuses out from the porous compact at a temperature below the normal sintering temperature. It has been found beneficial to hold the compact at an intermediate temperature to allow time for the CO and other gases to diffuse out before the pores close. We investigate this process using a computational model based on codiffusion of multiple gas species, which enables prediction of the gas and condensed phase compositions as a function of time and position in the specimen. The results are used to determine the optimum holding time for complete SiO2 removal as a function of key parameters, such as specimen thickness, particle size, temperature, etc., as well as the necessary amount of C additive. The results of the modeling are consistent with the experimentally observed spatial variation of density and composition in SiC compacts.

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Densification of B4C during sintering can be aided by removing the native B2O3(condensed) (B2O3(c)) layer present on the starting B4C powder. B2O3 can be removed by adding excess C and holding the powder compact at an intermediate temperature below the normal sintering temperature. This allows time for CO and minor boron gases to diffuse out from the porous compact before the pores close. This process was examined using a computational model based on codiffusion of multiple gas species, which enables prediction of the gas‐ and condensed‐phase composition as a function of time and position in the specimen. The model, described previously elsewhere, was originally applied to the SiC/SiO2 system but has been adapted for the B4C/B2O3 system. The results are used to determine the optimum holding time for complete B2O3(c) removal as a function of key parameters, such as specimen thickness, particle size, temperature, etc. The role of gas‐phase transport in residual C and B4C profiles is also examined.

Nondestructive ultrasound testing has been evaluated as a technique for analyzing isolated bulk defects and microstructural inhomogeneities in silicon carbide (SiC). Three SiC samples of varying thickness, two of which were fabricated by hot pressing and a third that was fabricated by chemical vapor deposition (CVD), were characterized using pulse–echo ultrasound characterization at a frequency of 75 MHz. Point analysis techniques were utilized to measure variations in time‐of‐flight (TOF), or ultrasound travel time through each sample, for calculation of regional differences in material velocity and elastic properties. C‐scan imaging was used to evaluate differences in both TOF and reflected signal amplitude over the area of each sample. Area‐under‐the‐curve (AUTC) and full‐width at half‐maximum (FWHM) data were obtained from normalized histograms to establish trends for direct sample comparison. It was determined that lower AUTC and FWHM values correlated to higher density samples with fewer inhomogeneities. However, the histogram tail area and distribution were also important features, providing information about specific inhomogeneities and their distributions.