We have investigated the relationship between particle removal efficiency and etched depth in SC-1 solution (the mixture composed of ammonium hydroxide, hydrogen peroxide and DI water) for Si wafers. The Si etching rate increases with increasing NH4OH (ammonium hydroxide) concentration. The particle removal efficiency depends on the etched Si depth, and is independent of NH4OH concentration. The minimum required Si etching depth to get over 95% particle removal efficiency is 4 nm. Particles on the Si wafers exponentially decrease with increasing the etched Si depth. However the particle removal efficiency is not affected by particle size ranging from 0.2 to 0.5 µm. The particle removal mechanism on the Si wafers in SC-1 solution is dominated by the lift-off of particles due to Si undercutting and redeposition of the removed particle.

In this paper, we study a variant of the MINIMUM DOMINATING SET problem. Given an unweighted undirected graph G=(V,E) of n=|V| vertices, the goal of the MINIMUM SINGLE DOMINATING CYCLE problem (MinSDC) is to find a single shortest cycle which dominates all vertices, i.e., a cycle C such that for the set V(C) of vertices in C and the set N(V(C)) of neighbor vertices of C, V(G)=V(C)∪N(V(C)) and |V(C)| is minimum over all dominating cycles in G [6], [17], [24]. In this paper we consider the (in)approximability of MinSDC if input graphs are restricted to some special classes of graphs. We first show that MinSDC is still NP-hard to approximate even when restricted to planar, bipartite, chordal, or r-regular (r≥3). Then, we show the (lnn+1)-approximability and the (1-ε)lnn-inapproximability of MinSDC on split graphs under P≠NP. Furthermore, we explicitly design a linear-time algorithm to solve MinSDC for graphs with bounded treewidth and estimate the hidden constant factor of its running time-bound.