Every summer, the Molecular Foundry supports several summer undergraduate students from the College of Chemistry at UC Berkeley for a paid full-time summer internship.
The internship program period spans 10 weeks from early June through early August. As an intern, participants will not only conduct research, but will participate in virtual tours of Berkeley Lab facilities, lunchtime talks with researchers from across the lab, and more. The program culminates with a poster session where the interns present their research.
Continuing research opportunities after this time period may be available.
Summer 2022 Deadline: April 1, 2022
Eligibility:
- Applicants must have an undergraduate cumulative minimum grade point average (GPA) of at least 3.0 on a 4.0 scale for all completed courses taken as a matriculated student at the applicant’s current (or recently graduated) institution and at any undergraduate institutions attended as a matriculated post-secondary student during the five years preceding the start of the current year.
- The FUSE internship is for rising juniors and seniors
- FUSE interns cannot take classes while participating in the program.
Application Information
To apply for the 2022 FUSE internship program, applicants need to submit the online application no later than April 1, 2022. If you have questions about the program or application, please contact us.
The application asks for a 1-page statement of interest, college transcripts, and project preferences, as well as demographic data for administrative purposes.
Opportunities for the 2022 Summer Program
Project listings, as available, will be posted below. Interested students will be welcome and encouraged to reach out to the PIs to discuss their interest in a particular project, or to learn more about a project. (Note that there may be a few late additions to this project list.)
Automating assembly of atomically thin 2D materials
Principal Investigator: Archana Raja
The Raja group uses photons and electrons to study transport of energy, charge, and information on ultrasmall length scales and ultrafast timescales. We are part of the Imaging and Manipulation of Nanostructures facility within the Molecular Foundry where we fabricate atomically thin two-dimensional crystals that serve as the perfect canvas to paint arbitrary potential landscapes for charge carriers and spins.
Project Description:
Atomically thin two-dimensional materials like graphene were discovered over a decade ago and have garnered immense interest both from fundamental science and technological application points of view. These materials are less than 1 nanometer thick and exhibit extraordinary electronic and optical properties due to the unique physics at these nanoscale dimensions. In particular, the enhanced optical absorption and fast transport of excitations in the 2D plane make them promising materials for next generation energy and electronics applications.
A crucial aspect of enabling these applications is layer by layer assembly of 2D materials to tailor their properties. Our research team prepares these structures by deterministically placing materials under a microscope using hardware controlled in a Python environment. The focus of this internship will be automating this stacking process for high reproducibility of material properties. The student can extend the scope of the hardware automation to include aspects of computer vision and machine learning to find and manipulate samples under microscope. The student will work closely with a team of graduate students, postdoctoral scholars, staff scientists and staff engineers at the Imaging and Manipulation of Nanostructures Facility within the Molecular Foundry.
Intern’s role:
- Fabrication of two-dimensional materials
- Write code to control hardware to automate aspects of fabrication
- Collaborate and interact with scientists in the Raja group for feedback on automation
- Deliver oral, written and poster presentation
- Write a paper for peer review or report
What can the intern expect to learn?
- How to plan and execute experimental research in a safe manner
- How to simulate experimental outcomes when possible, with coding and analysis
- How to interpret results and critically assess applied methods
- How to conduct research and ask questions in a collaborative and multidisciplinary environment
- Scientific communication and presentation
Materials Simulation Translator
Principal Investigator: David Prendergast
The Prendergast Group at the Molecular Foundry provides nanoscale understanding and interpretation of a wide range of energy-relevant processes using theory and simulation of molecules, materials, and interfaces. We work on the fundamental principles behind batteries (Li-ion and beyond), hydrogen storage, various chemical conversions (catalysis, solar to fuel). We are particularly interested in the interpretation of X-ray spectroscopy performed at Berkeley Lab’s Advanced Light Source which can provide chemically specific insight on working interfaces. We make great use of the National Energy Research Scientific Computing Center, a national supercomputing facility to run our simulations
Project Description:
Arriving at a deep understanding of nanomaterials and their properties requires the convergence of multiple factors: supercomputing, simulation software, numerical analysis, visualization and interpretation. Recently, we have been exploring efficient means of bringing these various factors together using python notebooks with direct access to simulations and the data that they generate. This project aims to provide “pre-analysis” by developing standard conclusions based on computed data that can help accelerate the more complex conclusions that we should draw. An example output might look like, “Based on these computational results, your material/molecule has these properties…” As experts, we already draw these conclusions, but the translation is a slow and human-limited process that could, in principle, be automatically generated to accelerate the learning of new users.
The goal of this work is to develop an efficient human interpretable translation of materials simulation outputs that can better inform understanding of computational results and guide next steps in computational experiments.
Intern’s role:
- You will make use of python to develop a set of tools that access the output of particular simulations and provide standardized interpretations that can be developed in partnership with scientists at Berkeley Lab
- You will provide text and visual aids within this tool to translate new concepts to new users (using yourself as the primary example);
- You will discuss your work with local experts and refine the process based on their feedback
What can the intern expect to learn?
- Python programming within Jupyter notebooks
- Accessing supercomputing resources, interfacing with data, performing numerical analysis
- Exposure to quantum chemistry, density functional theory for materials/molecular modeling
- Electronic properties of energy-relevant materials, fundamentals of energy conversion
- Data visualization and user interface design
- Scientific collaboration, communication, and presentation skills
Developing flexible dielectric films for capacitive energy storagery approach to materials self-assembly
Principal Investigator: Yi Liu
The Liu group at the Foundry focuses on the development of nanostructured functional energy materials through the design, synthesis and manipulation of tailor-made molecular and polymeric constituents. Some specific interests are directed towards 2D and 3D frameworks, organic electronics, dielectric materials, and organic-inorganic hybrids.
Project Description:
The use of electric vehicles carries substantial environmental benefits. For example, in the single year of 2020, the use of an electric vehicle instead of a conventional gasoline-powered vehicle saves around 1.5 million grams of CO2. However, a major challenge in electric vehicles is gaining high energy densities from capacitors to meet the miniaturization and lightweight demands since capacitors can contribute > 25% of the volume and weight to the power systems.
Since the energy density of a capacitor is in direct proportion to the dielectric constant (k), this project aims to develop flexible hybrid dielectric materials based on high-k (≥10) ferroelectric polymers and covalent organic frameworks (COFs). We will explore novel in-situ synthesis approaches to fabricating hybrid dielectric thin films with desirable compatibility at polymer/COF interfaces. By building rigid skeletons and generating deep traps, the incorporation of COFs is anticipated to break through inherent limitations of ferroelectric polymers (i.e., low mechanical and electrical insulation strengths) to achieve enhanced energy density with simultaneously improved Young’s modulus, breakdown strength and energy efficiency.
The main goal of the project is to overcome the inherent limitations of ferroelectric polymers for better capacitive energy storage
Intern’s role:
- Screen synthetic conditions for COF-based film growth
- Perform basic COF characterizations using PXRD, N2 sorption analysis, FTIR, UV-Vis
- Optimize composite film formation and fabricate capacitors
- Leakage current and capacitance measurements
What can the intern expect to learn?
- Basic principles of dielectrics and capacitors
- Hands-on experience on synthesis and characterization of COF films
- Hands-on experience on capacitors, from fabrication to characterization
- Learn how to conduct an interdisciplinary study involving chemical synthesis, materials optimization and electronic device fabrication and testing
Lithographically Defined Synthesis of Transition Metal Dichalcogenides
Principal Investigator: Tevye Kuykendall
In the Inorganic Facility of the Molecular Foundry, we develop methods for synthesis of compound semiconductors resulting in well controlled morphology and electronic structure. This can be achieved through band gap engineering in nanowire heterostructures, or energy level alignment in stacked assemblies of 2D materials. Using gas-phase methods allows us to realize arrays of 1D semiconducting heterostructures as well as approach synthesis of 2D materials with single layer precision. By harvesting the power of chemical vapor deposition and metalorganic chemistry our approach leads to realization of materials with optimized properties or exhibiting exotic behaviors. For example, bandgap engineered systems are a promising platform for the development of unconventional light emitting and energy harvesting devices through control of exciton generation and annihilation.
Project Description:
Transition metal dichalcogenides (TMDs) are an interesting class of semiconductor materials due to their emergent properties when reduced to thin two-dimensional (2D) layers. While exfoliation and vapor phase growth produce extremely high-quality 2D materials, direct fabrication at wafer scale remains a significant challenge. In previously published results, we demonstrated a method that we call “lateral conversion,” which employs chemical conversion of a metal-oxide film to TMD layers by diffusion of precursor propagating laterally between lithographically defined silica layers, resulting in patterned TMD structures with control over the thickness down to a few layers. The intern will work on further development of this synthetic method.
The synthesis has two distinct components: 1) Micro lithography and substrate preparation, and 2) sample annealing and conversion to the resulting TMD. The intern will focus on processing lithographically patterned substrates using chemical vapor deposition (CVD) under a variety of conditions to optimize the growth strategy and control their morphology and crystalline quality. The main goal of the internship is to explore and optimize different synthetic conditions for growing 2D TMD semiconductor films. They will study the effect of precursor conditioning, pressure, temperature, and reactive gasses on the TMD growth. Using a variety of characterization techniques, they will narrow down the process, through successive experiments and characterization, to control size, thickness, and size distribution, producing high-quality TMD materials.
Intern’s role:
- The intern will learn how to conduct independent research on solid state materials synthesis.
- They will be responsible for synthesizing 2D TMD films using a two-step “lateral conversion” synthesis method.
- They will learn how to characterize their samples using a variety of synthetic and analytic techniques.
- They will learn how to interpret results, and make improvements to the synthetic process using feedback for successive experiments.
They will receive careful oversight and training during the first month, until they are qualified to work independently. Additional training will be given as needed. Regular discussions will be had to interpret results and gauge their progress.
What can the intern expect to learn?
They will learn a variety of synthetic and analytic techniques, such as:
- Chemical vapor deposition (CVD) synthesis
- Raman spectroscopy
- Optical microscopy
- They will learn about the lithographic process and microfabrication techniques
- They will be mentored in the creation of a final poster project and will learn how to present their data using written text, plots, photographic images, and illustrations.
Fabrication of niobium-nitride nanotips as superconducting electron beam sources for
quantum information science
Principal Investigator: Alexander Stibor
The quantum information science (QIS) project QUINTESSENCE at the Molecular Foundry’s Quantum Lab at the Imaging Facility in a collaboration with NCEM is funded by the DOE and aims to realize a combined QIS electron microscope. An important part is the development of a novel superconducting, entangled two-electron nanotip beam source consisting of niobium (Nb) or niobium-nitride (NbN). This emitter is relevant for decoherence studies, correlated spectroscopy, or QIS and is planned to be implemented as a key component in several new projects such as QUINTESSENCE, 1K EM LDRD, and quantum-SPLEEM (spin-polarized low energy electron microscope).
Project Description:
The project aims to develop nanotip fabrication methods with NbN, which is well suited due to the high superconducting transition temperature of 16.5 K. We recently developed methods to etch and ion mill a monocrystalline Nb nanotip and built a cryogenic field emitter test and characterization setup. It was demonstrated that a superconducting niobium tip emits an electron beam with a ten times smaller energy width than conventional emitters (e.g. tungsten tips) and theory predicts an Nb tip to be a possible source of entangled free electrons with opposed spin and initial momentum through field emission of correlated Cooper pairs (Yuasa et al., PRB 79, 180503R (2009)). Due to the higher transition temperature, we believe that NbN is superior to Nb. Such an entangled electron source would have a strong impact in QIS with several applications in decoherence measurements, electron microscopy, and fundamental EPR-experiments.
The project for the intern is to transform an existing Nb tip to an NbN tip by atomic layer deposition (ALD) and test its field emission properties. ALD produces high-quality materials conformally, with sub-angstrom level control over thickness, allowing us to coat ultra-sharp metal tips. Superconducting order can be different in thin films relative to bulk materials, so ALD thickness control will provide an additional materials parameter to optimize performance. The field emission properties of the tips produced by the student will be tested in an ultra-high vacuum (UHV) setup with a closed-cycle liquid helium cryostat where the electron beam characteristics can be measured with an energy analyzer, a Faraday cup, and a multichannel plate detector.
Intern’s role:
The intern will test the applicability of ALD instrumentation and protocols for the fabrication of NbN nanotips by surface coating of an Nb tip. He or she will optimize existing techniques and characterize the tip shape and size in a scanning electron microscope. Then these tips are implemented into an existing vacuum setup for electron field emission characterization. The goal is to explore and optimize NbN nanotip fabrication protocols, using existing instrumentation at the Foundry. Performance measures will be beam stability, intensity, correlation, and beam energy distribution. The ultimate goal is the generation of correlated two-electron beams from an NbN nanotip field emitter.
What can the intern expect to learn?
The intern will learn nanotip fabrication methods and coating by ALD. He or she will be trained on a scanning electron microscope and how to work with an UHV setup including the energy analyzer and the multichannel plate detector. The student will also gain experience in electron optics, electron beam sources, cryo-techniques and get insight into the fundamental role of coherent electrons in QIS.
Self-Registered Polymer Brush Nanopatterning
Principal Investigator: Ricardo Ruiz
The Soft-Nano Research Group, led by Dr. Ricardo Ruiz in the Nanofabrication Facility, uses Soft-Matter physics to overcome specific challenges in assembling and manipulating matter at the nanometer-length scale. This covers a variety of nanofabrication techniques such as block copolymer lithography, nanoparticle and colloidal self-assembly and bio-molecular lithography for applications in nanoelectronics, memory and semiconductor synthetic biology.
Project Description:
The directed self-assembly (DSA) of block copolymers is a lithographic process that leverages block copolymer microphase separation to generate well-ordered structures with precise features and minimal defects. Our group has developed a DSA workflow that expands the processing window by incorporating polymer brushes that self-register on to the substrate and encode affinity for specific polymer species. While we have achieved great success using this workflow, the molecular origins of the self-registration process are still unknown. This project will explore the kinetic and thermodynamic limitations of the self-registration process in a model block copolymer system, polystyrene-block-poly(methyl methacrylate). These experiments will determine the optimal processing conditions, including polymer concentration, molecular weight, and temperature, for self-registration and uncover the mechanism for polymer brush insertion. Future directions of this project will include translating the insights gained on the model polymer system to other polymer brushes, including a novel biomimetic peptoid brush system to interface between semiconductor processing and synthetic biology.
The main research question of this project is to uncover the molecular origins of self-registered polymer brush nanopatterning.
Intern’s role:
- Hands-on laboratory work including sample preparation and characterization
- Analyze results and develop scientific conclusions and compare with existing literature
- Conduct an independent research project while working closely with a postdoc and the mentor, interact with team members in the Nanofabrication Facility through group meetings and other scientists at the Molecular Foundry
- Observe and contribute to the safety working culture of the Molecular Foundry
What can the intern expect to learn?
- Learn about polymer thin films and the fundamentals behind block copolymer self-assembly
- Advanced characterization techniques such scanning electron microscopy (SEM), atomic force microscopy (AFM)
- Exposure to the Molecular Foundry’s nanofabrication facility and cleanroom work
- Learn how to work on a research project from developing an overall research plan to planning daily tasks, practice asking good scientific questions
- Practice scientific communication and presentation skills through daily interaction with scientists, group meetings, and the end-of-program poster session
Learning to grow: autonomous synthesis of materials by simulated evolution
Principal Investigator: Steve Whitelam
An outstanding problem of materials science is to develop predictive, microscopic rules for self-assembly: given a nanoscale building block, such as a protein or small molecule, how will it self-assemble? As time evolves, what phases and structures will it form, and what will be the yield of the `target’ structure when (and if) it assembles? My group uses the tools and techniques of statistical mechanics to address these questions.
Project Description:
In this project we will explore approaches based on evolutionary learning that design particles and protocols in order to self-assemble materials to order. We will express the interparticle potential and time-dependent assembly protocol as arbitrary functions, encoded by neural networks. This encoding is the instruction code or “genome” for self-assembling a material. Molecular simulations carried out using the particle and protocols specified by the genome results in the “phenome”, a material whose properties can be measured and compared to a design goal. We will use evolutionary learning to produce phenomes whose properties satisfy user-defined goals, both directed or exploratory in nature.
Intern’s role:
- Through discussion with mentor, and review of scientific literature, formulate a 9-week project plan.
- Carry out simulation work, and present the results through discussions and formal presentations.
- Prepare review materials for the FUSE program.
What can the intern expect to learn?
- Basic research skills including experience defining and planning a project.
- Experience with molecular simulation and basic machine-learning tools, including neural networks and evolutionary methods.
Inline fluorescence and X-ray analysis of protein samples
Principal Investigator: Corie Ralston
The Ralston group designs and builds advanced new instruments to study protein structures using X-rays and fluorescence spectroscopies. These instruments are used by other scientists around the world to help solve a range of problems in biomedicine, such as how proteins misfold in certain diseases, and how drugs bind to proteins.
Project Description:
The intern will help complete a spectroscopy system for measuring fluorescence from protein samples inline with an X-ray beam. In this system, samples flow past an X-ray beam, and fluorescence is collected from the sample while it is flowing into a collection tube. The protein samples are oligomeric forms of amyloid beta, and the data acquired using this method will help determine how amyloid plaques form in Alzheimer’s Disease.
Intern’s role:
- Assist in building an inline fluorescence spectrometer
- Collect spectroscopy and X-ray data from protein samples using the spectrometer
- Help scientists analyze and interpret data on amyloid beta proteins
- Help prepare data for publication
What can the intern expect to learn?
- The basics of fluorescence and how it is used to examine protein structure
- How to prepare proteins for fluorescence and X-ray experiments
- How to collaborate and work on a multidisciplinary biophysics team
- How to interpret and present scientific results
