Data description This dataset presents the raw and augmented data that were used to train the machine learning (ML) models for classification of printing outcome in projection two-photon lithography (P-TPL). P-TPL is an additive manufacturing technique for the fabrication of cm-scale complex 3D structures with features smaller than 200 nm. The P-TPL process is further described in this article: “Saha, S. K., Wang, D., Nguyen, V. H., Chang, Y., Oakdale, J. S., and Chen, S.-C., 2019, "Scalable submicrometer additive manufacturing," Science, 366(6461), pp. 105-109.” This specific dataset refers to the case wherein a set of five line features were projected and the printing outcome was classified into three classes: ‘no printing’, ‘printing’, ‘overprinting’. Each datapoint comprises a set of ten inputs (i.e., attributes) and one output (i.e., target) corresponding to these inputs. The inputs are: optical power (P), polymerization rate constant at the beginning of polymer conversion (kp-0), radical quenching rate constant (kq), termination rate constant at the beginning of polymer conversion (kt-0), number of optical pulses, (N), kp exponential function shape parameter (A), kt exponential function shape parameter (B), quantum yield of photoinitiator (QY), initial photoinitiator concentration (PIo), and the threshold degree of conversion (DOCth). The output variable is ‘Class’ which can take these three values: -1 for the class ‘no printing’, 0 for the class ‘printing’, and 1 for the class ‘overprinting’. The raw data (i.e., the non-augmented data) refers to the data generated from finite element simulations of P-TPL. The augmented data was obtained from the raw data by (1) changing the DOCth and re-processing a solved finite element model or (2) by applying physics-based prior process knowledge. For example, it is known that if a given set of parameters failed to print, then decreasing the parameters that are positively correlated with printing (e.g. kp-0, power), while keeping the other parameters constant would also lead to no printing. Here, positive correlation means that individually increasing the input parameter will lead to an increase in the amount of printing. Similarly, increasing the parameters that are negatively correlated with printing (e.g. kq, kt-0), while keeping the other parameters constant would also lead to no printing. The converse is true for those datapoints that resulted in overprinting. The 'Raw.csv' file contains the datapoints generated from finite element simulations, the 'Augmented.csv' file contains the datapoints generated via augmentation, and the 'Combined.csv' file contains the datapoints from both files. The ML models were trained on the combined dataset that included both raw and augmented data.
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Corporate Responsibility: A Green Initiative to Reduce Chlorobenzene Based Chemistries in Semiconductor Processing
ABSTRACT Climate change and an increase in endangered species, are examples of technological advances negatively impacting the environment. As technology demands increase, an earnest effort to reduce the environmental impact of processing and manufacturing related activities is critical. From a business perspective, minimizing or removing toxic process chemicals is a high impact area that can increase work environment safety and decrease waste management costs. This work presents processing considerations when transitioning to greener alternative polymer resist solvents, for applications in nanomanufacturing with sustainability considerations. Within government contracting, process modifications that change product form, fit, or function require qualification and at minimum justification. This work presents the conversion from a chlorobenzene to anisole based solvent using a 495 kMW polymetheyl methacrylate polymer resin, without impacting form fit or function of the intended device. Resist conversion is of interest as the difference in the substituents of the two solvents, impact the effective toxicity of the polymer resists. Specifically, the oral median lethal dose (LD 50 ) in rats for chlorobenzene is 1110 mg/kg, while anisole is 3700 mg/kg. Therefore, developing a process utilizing anisole and replacing chlorobenzene addresses safety concerns and contributes to green initiatives worldwide. Within this work electron beam lithography fabricated transistor components consisting of a double layered source, and gate were converted from a chlorobenzene to anisole based process; while maintaining process of record specifications. The purpose of this work is to provide a starting platform for individuals seeking to convert from a chlorobenzene solvent to an anisole based resist for sub-micron lithography steps.
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- Award ID(s):
- 1846628
- NSF-PAR ID:
- 10094660
- Date Published:
- Journal Name:
- MRS Advances
- Volume:
- 4
- Issue:
- 07
- ISSN:
- 2059-8521
- Page Range / eLocation ID:
- 393 to 398
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Despite having favorable optoelectronic and thermomechanical properties, the wide application of semiconducting polymers still suffers from limitations, particularly with regards to their processing in solution which necessitates toxic chlorinated solvents due to their intrinsic low solubility in common organic solvents. This work presents a novel greener approach to the fabrication of organic electronics without the use of toxic chlorinated solvents. Low‐molecular‐weight non‐toxic branched polyethylene (BPE) is used as a solvent to process diketopyrrolopyrrole‐based semiconducting polymers, then the solvent‐induced phase separation (SIPS) technique is adopted to produce films of semiconducting polymers from solution for the fabrication of organic field‐effect transistors (OFETs). The films of semiconducting polymers prepared from BPE using SIPS show a more porous granular morphology with preferential edge‐on crystalline orientation compared to the semiconducting polymer film processed from chloroform. OFETs based on the semiconducting films processed from BPE show similar device characteristics to those prepared from chloroform without thermal annealing, confirming the efficiency and suitability of BPE to replace traditional chlorinated solvents for green organic electronics. This new greener processing approach for semiconducting polymers is potentially compatible with different printing techniques and is particularly promising for the preparation of porous semiconducting layers and the fabrication of OFET‐based electronics.
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Organic photovoltaics have achieved breakthroughs in power conversion efficiency due to the superior aggregation and packing nature of non‐fullerene acceptors (NFAs). Solution processing and various treatments would tend to form distinct packing motifs for state‐of‐the‐art NFAs. Herein, the solvent‐induced polymorphism for 3,9‐bis(2‐methylene‐(3‐(1,1‐dicyanomethylene)‐indanone))‐5,5,11,11‐tetrakis(4‐hexylphenyl)‐dithieno[2,3‐d:2′,3′‐d′]‐s‐indaceno[1,2‐b:5,6‐b′]dithiophne) (ITIC) prepared by chloroform (CF) and chlorobenzene (CB) is revealed. The packing motif of ITIC exhibits dense π–π stacking from CF induction, which presents red‐shifted absorption and reversible high‐temperature crystallization and melting. Meanwhile, strong lamellar stacking and π–π stacking can be formed in the CB solution with unstable low‐temperature crystallization and melting. Combining in situ absorption spectra and interaction calculation, the stronger preaggregation of ITIC in the CF solution was found to be the main reason for forming a different packing motif from in the CB solution. The packing and thermodynamic features are retained in the PBDB‐T:ITIC blends, though good miscibility weakens characteristic features. Benefiting from the polymorph structure, CB‐processed devices denote more favorable performance but less thermal stability. This research indicates the significant effect of solvent induction for manipulating and optimizing the morphology of organic solar cell devices.
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Abstract To elucidate the details of film morphology/order evolution during spin‐coating, solvent and additive effects are systematically investigated for three representative organic solar cell (OSC) active layer materials using combined in situ grazing incidence wide angle x‐ray scattering (GIWAXS) and optical reflectance. Two archetypical semiconducting donor (p‐type) polymers, P3HT and PTB7, and semiconducting donor small‐molecule,
p ‐DTS(FBTTh2)2are studied using three neat solvents (chloroform, chlorobenzene, 1,2‐dichlorobenzene) and four processing additives (1‐chloronaphthalene, diphenyl ether, 1,8‐diiodooctane, and 1,6‐diiodohexane). In situ GIWAXS identifies several trends: 1) for neat solvents, rapid crystallization occurs that risks kinetically locking the material into multiple crystal structures or crystalline orientations; and 2) for solvent + additive processed films, morphology evolution involves sequential transformations on timescales ranging from seconds to hours, with key divergences dependent on additive/semiconductor molecular interactions. When π‐planes dominate the additive/semiconductor interactions, both polymers and small molecule films follow similar evolutions, completing in 1–5 min. When side chains dominate the additive/semiconductor interactions, polymer film maturation times are up to 9 h, while initial crystallization times <10 s are observed for small‐molecule films. This study offers guiding information on OSC donor intermediate morphologies, evolution timescales, and divergent evolutions that can inform OSC manufacture. -
null (Ed.)(1) Different methods have been applied to fabricate polymeric membranes with non-solvent induced phase separation (NIPS) being one of the mostly widely used. In NIPS, a solvent or solvent blend is required to dissolve a polymer or polymer blend. N-methyl-2-pyrrolidone (NMP), dimethylacetamide (DMAc), dimethylformamide (DMF) and other petroleum-derived solvents are commonly used to dissolve some petroleum-based polymers. However, these components may have negative impacts on the environment and human health. Therefore, using greener and less toxic components is of great interest for increasing membrane fabrication sustainability. The chemical structure of membranes is not affected by the use of different solvents, polymers, or by the differences in fabrication scale. On the other hand, membrane pore structures and surface roughness can change due to differences in diffusion rates associated with different solvents/co-solvents diffusing into the non-solvent and with differences in evaporation time. (2) Therefore, in this review, solvents and polymers involved in the manufacturing process of membranes are proposed to be replaced by greener/less toxic alternatives. The methods and feasibility of scaling up green polymeric membrane manufacturing are also examined.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1557/adv.2019.20
