Business Versus Ethics? Thoughts on the Future of Business Ethics.

To commemorate 40 years since the founding of the Journal of Business Ethics, the editors in chief of the journal have invited the editors to provide commentaries on the future of business ethics. This essay comprises a selection of commentaries aimed at creating dialogue around the theme Business versus Ethics? (inspired by the title of the commentary by Jeffrey Harrison). The authors of these commentaries seek to transcend the age-old separation fallacy (Freeman in Bus Ethics Q 4(4):409-421, 1994) that juxtaposes business and ethics/society, posing a forced choice or trade off. Providing a contemporary take on the classical question "if it's legal is it ethical?", David Hess explores the role of the law in promoting or hindering stakeholder-oriented purpose and governance structure. Jeffrey Harrison encourages scholars to move beyond the presupposition that businesses are either strategic or ethical and explore important questions at the intersection of strategy and ethics. The proposition that business models might be inherently ethical or inherently unethical in their design is developed by Sheila Killian, who examines business systems, their morality, and who they serve. However, the conundrum that entrepreneurs are either lauded for their self-belief and risk-taking, or loathed for their self-belief and risk-taking, is discussed by M. Tina Dacin and Julia Roloff using the metaphor of taboos and totems. These commentaries seek to explore positions that advocate multiplicity and tensions in which business ethics is not either/or but both.

Noncontact Imaging of Ion Dynamics in Polymer Electrolytes with Time-Resolved Electrostatic Force Microscopy.

Ionic-transport processes govern performance in many classic and emerging devices, ranging from battery storage to modern mixed-conduction organic electrochemical transistors (OECT). Here, we study local ion-transport dynamics in polymer films using time-resolved electrostatic force microscopy (trEFM). We establish a correspondence between local and macroscopic measurements using local trEFM and macroscopic electrical impedance spectroscopy (EIS). We use polymer films doped with lithium bis(trifluoromethane)sulfonimide (LiTFSI) as a model system where the polymer backbone has oxanorbornenedicarboximide repeat units with an oligomeric ethylene oxide side chain of length n. Our results show that the local polymer response measured in the time domain with trEFM follows stretched-exponential relaxation kinetics, consistent with the Havriliak-Negami relaxation we measure in the frequency-domain EIS data for macroscopic samples of the same polymers. Furthermore, we show that the trEFM results capture the same trends as the EIS results-changes in ion dynamics with increasing temperature, increasing salt concentration, and increasing volume fraction of ethylene oxide side chains in the polymer matrix evolve with the same trends in both measurement techniques. We conclude from this correlation that trEFM data reflect, at the nanoscale, the same ionic processes probed in conventional EIS at the device level. Finally, as an example application for emerging materials syntheses, we use trEFM and infrared photoinduced force microscopy (PiFM) to image a diblock copolymer electrolyte for next-generation solid-state energy storage applications.

Identifying Nanoscale Structure-Function Relationships Using Multimodal Atomic Force Microscopy, Dimensionality Reduction, and Regression Techniques.

Correlating nanoscale chemical specificity with operational physics is a long-standing goal of functional scanning probe microscopy (SPM). We employ a data analytic approach combining multiple microscopy modes using compositional information in infrared vibrational excitation maps acquired via photoinduced force microscopy (PiFM) with electrical information from conductive atomic force microscopy. We study a model polymer blend comprising insulating poly(methyl methacrylate) (PMMA) and semiconducting poly(3-hexylthiophene) (P3HT). We show that PiFM spectra are different from FTIR spectra but can still be used to identify local composition. We use principal component analysis to extract statistically significant principal components and principal component regression to predict local current and identify local polymer composition. In doing so, we observe evidence of semiconducting P3HT within PMMA aggregates. These methods are generalizable to correlated SPM data and provide a meaningful technique for extracting complex compositional information that is impossible to measure from any one technique.

Fast time-resolved electrostatic force microscopy: Achieving sub-cycle time resolution.

The ability to measure microsecond- and nanosecond-scale local dynamics below the diffraction limit with widely available atomic force microscopy hardware would enable new scientific studies in fields ranging from biology to semiconductor physics. However, commercially available scanning-probe instruments typically offer the ability to measure dynamics only on time scales of milliseconds to seconds. Here, we describe in detail the implementation of fast time-resolved electrostatic force microscopy using an oscillating cantilever as a means to measure fast local dynamics following a perturbation to a sample. We show how the phase of the oscillating cantilever relative to the perturbation event is critical to achieving reliable sub-cycle time resolution. We explore how noise affects the achievable time resolution and present empirical guidelines for reducing noise and optimizing experimental parameters. Specifically, we show that reducing the noise on the cantilever by using photothermal excitation instead of piezoacoustic excitation further improves time resolution. We demonstrate the discrimination of signal rise times with time constants as fast as 10 ns, and simultaneous data acquisition and analysis for dramatically improved image acquisition times.

Classifying Force Spectroscopy of DNA Pulling Measurements Using Supervised and Unsupervised Machine Learning Methods.

Dynamic force spectroscopy (DFS) measurements on biomolecules typically require classifying thousands of repeated force spectra prior to data analysis. Here, we study classification of atomic force microscope-based DFS measurements using machine-learning algorithms in order to automate selection of successful force curves. Notably, we collect a data set that has a testable positive signal using photoswitch-modified DNA before and after illumination with UV (365 nm) light. We generate a feature set consisting of six properties of force-distance curves to train supervised models and use principal component analysis (PCA) for an unsupervised model. For supervised classification, we train random forest models for binary and multiclass classification of force-distance curves. Random forest models predict successful pulls with an accuracy of 94% and classify them into five classes with an accuracy of 90%. The unsupervised method using Gaussian mixture models (GMM) reaches an accuracy of approximately 80% for binary classification.

Imaging Charge Transfer State Excitations in Polymer/Fullerene Solar Cells with Time-Resolved Electrostatic Force Microscopy.

We demonstrate nanoscale imaging of charge transfer state photoexcitations in polymer/fullerene bulk heterojunction solar cells using time-resolved electrostatic force microscopy (trEFM). We compare local trEFM charging rates and external quantum efficiencies (EQE) for both above-gap and below-gap excitation of the model system poly[2-methoxy-5-(3',7'-dimethyloctyloxy)-1,4-phenylenevinylene] (MDMO-PPV) and [6,6]-phenyl C61 butyric acid methyl ester (PCBM). We show that the local trEFM charging rate correlates with device EQE for both above-gap and below-gap photoexcitation, demonstrating that EFM methods have sufficient sensitivity to detect the low EQEs associated with CT state formation, a result that could be useful for probing weak subgap excitations in nanostructured materials such as quantum dot and organometal halide perovskite solar cells. Further, we use trEFM to map spatial variations in EQE arising from subgap CT excitation in organic photovoltaics (OPVs) and find that the local distribution of photocurrent arising from these states is nearly identical to the spatial variation in EQE from above-gap singlet excitation. These results are consistent with recent work showing that both above-gap and below-gap excitation have similar internal quantum efficiency.