M-CELL
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M-CELL is a 2-algorithm 1-LLSLL method that can be added on to various methods as a final step it has one algorithm for solving L5C and one for L5E. Each are commutators meaning that neither affects the other so both can be recognised at the same time and executed one after each other without having to rerecognise.
Contents
Steps
- Solve a 1x2x3 in DL*
- Solve a 2x2x2 in DBR and FR Edge*
- Recognise L5C and L5E cases
- Execute in either order
(* These are part of SSF2L (Shadowslice F2L) which the method was originally proposed to be used in conjunction with)
Variants
- 2OP- (2-OP/2 (double) Orient and Permute)
- The beginner variant so to speak, it has a 2-Look lower alg system of the method which gets the user into the habit of recognising 2 algs at the same time which can often be a barrier to entry with the larger alg sets
- Steps:
- T-CELL- (twinned-CELL) the "normal"/ "speedsolvable" variant
- This is more or less the variant described above
- Steps
- Recognise L5C and L5E
- Execute L5C and L5E in either order
- B-CELL- (broken-CELL) typically for FMCesque solves
- This is essentially the same as T-CELL in terms of steps though for this one the corner and edge do not necessarily have to be in the adjacent meaning that a variety of F2L structures can be used- notably Heise though not using the centre-edge-centre one as this will block the edge position. While not recommended for speedsolving as the pieces Corner and edge in the D-layer could become hidden and impede lookahead and recognition, it can none the less produce very good FMC results as F2L can be created very efficiently and commutators for the other pieces can be inserted using commutators.
Pros
- 1LLSLL
- Relatively low algorithm count for a 1LLSLL especially compared to others such as CTLS or ZBLL.
- Fairly efficient and low movecount
- Requires no special setting up or conditions such as Edge Orientation (as in ZBLL), Corner Orientation (as in COALL) or Corner Permutation (as in 2GLL).
Cons
- Many pieces mean recognition is difficult.
- 2 algorithms will always be less efficient that 1.
- Ergonomics can sometimes leave something to be desired.