Health Risk Assessment of Photoresists Used in an Optoelectronic Semiconductor Factory

Sustainable Lithography Paradigm Enabled by Mechanically Peelable Resists

Lithography is critical in micro- and nanofabrication processes, enabling the development of integrated circuits, semiconductor devices, and various advanced electronic and photonic systems. However, there are challenges related to sustainability, efficiency, and yield, as well as compatibility with transient electronics. This work introduces a sustainable lithography paradigm employing mechanically peelable resists compatible with existing cleanroom processes. The resists exhibit near-zero adhesion to various substrates, facilitating efficient, cost-effective, environmentally friendly, and chemical-free mechanical stripping without observable particulate residues. The mechanical lift-off process enables scalable and 100%-yield pattern transfer using commercially available tape within seconds. Furthermore, the new paradigm supports distributed and in situ conformal manufacturing using the peelable resist as a "transferable stencil mask" to fabricate various functional devices on flexible and nonplanar surfaces, as well as ultra-thin biodegradable substrates. Overall, this work expands the potential for using lift-off as a standard process in the pan-semiconductor industry and opens new avenues for lithographic procedures aimed at the reliable mass production of transient electronics and integrated biodegradable devices, addressing growing sustainability issues caused by electronic waste.

Wavelength-Dependent Shaping of Azopolymer Micropillars for Three-Dimensional Structure Control

Surfaces endowed with three-dimensional (3D) mesostructures, showing features in the nanometer to micrometer range, are critical for applications in several fields of science and technology. Finding a fabrication method that is simultaneously inexpensive, simple, fast, versatile, highly scalable, and capable of producing complex 3D shapes is still a challenge. Herein, we characterize the photoreconfiguration of a micropillar array of an azobenzene-containing polymer at different light wavelengths and demonstrate the tailoring of the surface geometry and its related functionality only using light. By changing the irradiated light wavelength and its polarization, we demonstrate the fabrication of various complex isotropic and anisotropic 3D mesostructures from a single original pristine geometry. Quantitative morphological analyses revealed an interplay between the decay rate of absorbed light intensity, micropillar volume preservation, and the cohesive forces between the azopolymer chains as the origin of distinctive wavelength-dependent 3D structural remorphing. Finally, we show the potentialities of this method in surface engineering by photoreshaping a single original micropillar surface into two sets of different mesostructured surfaces exhibiting tunable hydrophobicity in a wide water contact angle range. Our study opens up a new paradigm for fabricating functional 3D mesostructures in a simple, low-cost, fast, and scalable manner.

Inkjet Printing: A Viable Technology for Biosensor Fabrication

Printing technology promises a viable solution for the low-cost, rapid, flexible, and mass fabrication of biosensors. Among the vast number of printing techniques, screen printing and inkjet printing have been widely adopted for the fabrication of biosensors. Screen printing provides ease of operation and rapid processing; however, it is bound by the effects of viscous inks, high material waste, and the requirement for masks, to name a few. Inkjet printing, on the other hand, is well suited for mass fabrication that takes advantage of computer-aided design software for pattern modifications. Furthermore, being drop-on-demand, it prevents precious material waste and offers high-resolution patterning. To exploit the features of inkjet printing technology, scientists have been keen to use it for the development of biosensors since 1988. A vast number of fully and partially inkjet-printed biosensors have been developed ever since. This study presents a short introduction on the printing technology used for biosensor fabrication in general, and a brief review of the recent reports related to virus, enzymatic, and non-enzymatic biosensor fabrication, via inkjet printing technology in particular.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool

STOFFENMANAGER^® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER^® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER^® and ART are based on a modified multiplicative model where an exposure base level (mg m⁻³) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m⁻³) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER^® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER^® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER^® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER^® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER^® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER^® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER^® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective

The turn of the 21st century heralded in the semiconductor age alongside the Anthropocene epoch, characterised by the ever-increasing human impact on the environment. The ecological consequences of semiconductor chip manufacturing are the most predominant within the electronics industry. This is due to current reliance upon large amounts of solvents, acids and gases that have numerous toxicological impacts. Management and assessment of hazardous chemicals is complicated by trade secrets and continual rapid change in the electronic manufacturing process. Of the many subprocesses involved in chip manufacturing, lithographic processes are of particular concern. Current developments in bottom-up lithography, such as directed self-assembly (DSA) of block copolymers (BCPs), are being considered as a next-generation technology for semiconductor chip production. These nanofabrication techniques present a novel opportunity for improving the sustainability of lithography by reducing the number of processing steps, energy and chemical waste products involved. At present, to the extent of our knowledge, there is no published life cycle assessment (LCA) evaluating the environmental impact of new bottom-up lithography versus conventional lithographic techniques. Quantification of this impact is central to verifying whether these new nanofabrication routes can replace conventional deposition techniques in industry as a more environmentally friendly option.

Incorporating Exposure Measurement Data from Similar Exposure Scenarios to Inform Exposure Modeling Estimates: A Demonstration Using Cluster Analysis and Bayesian Modeling

Addressing occupational health and safety concerns early in the design stage anticipates hazards and enables health professionals to recommend control measures that can best protect workers' health. This method is a well-established tool in public health. Importantly, its success depends on a comprehensive exposure assessment that incorporates previous exposure data and outcomes. Traditional methods for characterizing similar occupational exposure scenarios rely on expert judgment or qualitative descriptions of relevant exposure data, which often include undisclosed underlying assumptions about specific exposure conditions. Thus, improved methods for predicting exposure modeling estimates based on available data are needed. This study proposes that cluster analysis can be used to quantify the relevance of existing exposure scenarios that are similar to a new scenario. We demonstrate how this method improves exposure predictions. Exposure data and contextual information of the scenarios were collected from past exposure assessment reports. Prior distributions for the exposure distribution parameters were specified using Stoffenmanager® 8 predictions. Gower distance and k-Medoids clustering algorithm analyses grouped existing scenarios into clusters based on similarity. The information was used in a Bayesian model to specify the degree of correlation between similar scenarios and the scenarios to be assessed. Using the distance metric to characterize the degree of similarity, the performance of the Bayesian model was improved in terms of the average bias of model estimates and measured data, reducing from 0.77 (SD: 2.0) to 0.49 (SD: 1.8). Nevertheless, underestimation of exposures still occurred for some rare scenarios, which tended to be those with highly variable exposure data. In conclusion, the cluster analysis approach may enable transparent selection of similar exposure scenarios for factoring into design-phase assessments and thereby improve exposure modeling estimates.

Polymers for Regenerative Medicine Structures Made via Multiphoton 3D Lithography

Multiphoton 3D lithography is becoming a tool of choice in a wide variety of fields. Regenerative medicine is one of them. Its true 3D structuring capabilities beyond diffraction can be exploited to produce structures with diverse functionality. Furthermore, these objects can be produced from unique materials allowing expanded performance. Here, we review current trends in this research area. We pay particular attention to the interplay between the technology and materials used. Thus, we extensively discuss undergoing light-matter interactions and peculiarities of setups needed to induce it. Then, we continue with the most popular resins, photoinitiators, and general material functionalization, with emphasis on their potential usage in regenerative medicine. Furthermore, we provide extensive discussion of current advances in the field as well as prospects showing how the correct choice of the polymer can play a vital role in the structure’s functionality. Overall, this review highlights the interplay between the structure’s architecture and material choice when trying to achieve the maximum result in the field of regenerative medicine.