Peer review of: Nano-topology optimization for materials design with atom-by-atom control (2020)

REVIEWER COMMENTS 
Reviewer #1 (Remarks to the Author): 


In this paper, the authors propose a design method on Topology Optimization that can search for 
the best possible atom distributions for desired properties of nanostructured materials. Through 
designing Al structures atom-by-atom without the need of a predetermined design, the elastic 
properties such as the bulk modulus can exceed the theoretical maximum. The resulting 
performance of the optimized design also surpasses that of other triply periodic minimal surface 
structures. These results are of interest to the readers in the related field of advanced design for 
nanomaterials and nanomachines with desired properties. I have several suggestions and I hope that 
the authors can address these points before the publication of this manuscript. 

 

1. In Figure 1 and supporting information, the concept of rejection and admission rate and how the 
value is selected in the optimization process have not been discussed. The definition for the filter 
radius in Eq. 10 should also be provided. How do these parameters affect the optimization? 

 
2. In this work, aluminum is selected as the base material. How about the application of the method 
in other material systems? 

 
3. In the supporting information, the nanoplate with a free surface {1 1 0} is selected for comparison. 
How about other faces? 

 
4. The authors present the case studies of using Nano-TO in maximizing the bulk modulus and elastic 
constant. If the desired performance of nanostructured materials requires two or more improved 
mechanical properties, how to make use of this method and make balance in the design? 


5. As the authors mentioned that “the generality of the approach that it can be used to design 
nanomaterials and nanomachines with optimal performance”, it would be helpful to compare this 
method with prior approaches such as mentioned ML models, and describe how their method bases 
on the TO can be transferred to other nanomachines. 

 

Reviewer #2 (Remarks to the Author): 

The work presents a method to optimize atomic structures. Though the algorithm is simple and 
straightforward, the concept is innovative. The following questions should be well answered before 
acception: 


1)The process of optimization is shown in the flow chart in Fig. 1 but has not well been explained. 


2)A robust optimization algorithm should not rely on the initial structures. But the authors claim that 
16 structures were produced in 16 attempts with random initialization. Then how the optimization 
guarantee the minimum of objective functional, no matter locally or globally. 

 
3)Is the surface effect considered in atomistic modeling? If yes, how to take it into consideration? 


4)How to impose periodic boundary condition? 


5)How to determine the embedding energy and potential energy in Eq. (4). 


6)The statement “an energy minimization using the conjugate gradient (CG) algorithm is performed 
to equilibrate the material system” is very unclear. Please give more details to show how to calculate 
the elastic properties? In homogenization theory when calculating the effective properties like C11, 
only one test strain is imposed. But the work needs a positive strain and a negative test strain, why? 
Will the magnitude of test strain affect the value of C11? 

 

 

Reviewer #3 (Remarks to the Author): 

The paper presents a so-called nano-topology optimization method for atom-by-atom controlled 
material design. While the paper is well written and well described the method, the reviewer didn't 
find it interesting. 

In particular, I couldn't find any novelty and broader impacts of the paper. 

It seems the authors are trying to re-invent the wheel that is already out there—by using the same 
old-fashioned optimization approach, just at a different scale. 

More importantly, people in the design and optimization community have already tackled these 
kinds of problems in many different ways and at different length scales. A small survey on the 
designing (and even manufacturing) of architected and cellular material with desired properties 
(linear/nonlinear) would reveal those well-established approaches. 

Therefore, I don't see any novelty and broader impact by re-trying a well-established old-fashioned 
topology optimization approach at another length scale. To me, this is just a matter of scaling, and 
you could get the same results (even better) at the continuum level. You could also develop any of 
these objectives (even complex cases) at the continuum level and obtain any desired properties, as 
people have done this before. 

In conclusion, the reviewer does not recommend the manuscript for publication in Nat. Comm.