1
2
3
4
5
6
7
8
class SpinCoating(FabStepCommon):
    step_type: Literal["spin_coating"] = "spin_coating"
    material: Optional[str] = Field(None, description="Material spun")
    speed_rpm: Optional[float] = Field(None, description="Spin speed in RPM")
    acceleration_rpm_s: Optional[float] = Field(None, description="Acceleration in RPM/s")
    duration_s: Optional[float] = Field(None, description="Duration in seconds")
    bake_temp_c: Optional[float] = Field(None, description="Bake temp in C")
    bake_duration_s: Optional[float] = Field(None, description="Bake duration in seconds")

1
2
3
4
5
6
7
8
9
class Deposition(FabStepCommon):
    step_type: Literal["deposition"] = "deposition"
    method: Optional[str] = Field(None, description="Evaporation, Sputtering, etc.")
    tool: Optional[str] = Field(None, description="Tool name")
    material: Optional[str] = Field(None, description="Material deposited")
    thickness_target_nm: Optional[float] = Field(None, description="Target thickness")
    rate: Optional[str] = Field(None, description="Deposition rate")
    pressure: Optional[str] = Field(None, description="Chamber pressure")
    gas_flow: Optional[str] = Field(None, description="Gas flows")

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
system_prompt = f"""
You are an intelligent assistant categorizing scientific process logs.

Your goal is to extract the Global Context for the provided file.

INPUT:
- Filename: {filename}
- Content Preview (First 3000 chars): "{text_preview}..."

INSTRUCTIONS:
1. Identify the **Project Name** (often in headers or filename).
2. Identify the **Material Stack** if mentioned (e.g., "LN on Si", "Aluminum on SiO2").
3. Identify **People's Initials** involved (e.g., "TM", "ES", "WTJ").
4. Identify the **Rough Date/Year** of the work.

Output strictly valid JSON matching the schema below.

Target Schema:
{schema_json}
"""

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
system_prompt = f"""
You are an expert process engineer. Analyze the provided fabrication log segment.
Extract distinct operations (steps) into a JSON object.

GLOBAL CONTEXT for this file:
{global_context}

INSTRUCTIONS:
1. Extract specific process parameters matching the schema.
2. Fill "Common Attributes":
    - **Person/Project**: Infer from text or use Global Context.
    - **Material Stack**: Describe the full stack (e.g., "500nm LN on SiO2 on Si"). Use Global Context if the step doesn't specify.
    - **Date**: Look for headers (e.g., "# Dec 3").
3. Use 'observations' for qualitative notes.
4. Set 'document_name' to "{filename}".
5. IGNORE 'preceding_step_summary' and 'following_step_summary' (filled later).

Output strictly valid JSON with root key "fab_steps".

Target Schema:
{schema_json}
"""

1
2
3
4
5
6
7
8
9
10
11
12
13
{
    "step_type": "metrology",
    "document_name": "220409_PADL01_Process_Notes.md",
    "person": "Takuma",
    "date": "2022-04-19",
    "method": "Filmetrics",
    "tool": "Filmetrics",
    "feature_measured": "Resist thickness",
    "measurement_result": "PMMA: 327.43 nm \u00b1 56.73 nm; MMA: 534.14 nm \u00b1 67.81 nm; GOF ~0.94787",
    "observations": "Best practice is to measure MMA thickness then PMMA thickness but not have the tool fit the MMA thickness.",
    "preceding_step_summary": "spin_coating by Takuma",
    "following_step_summary": "lithography by Takuma"
},

1
2
3
4
5
6
7
8
9
10
11
12
You are an expert fabrication process engineer who works on a team at a university. 
You are tasked with answering user questions and providing advice to the user based on previous fabrication logs generated by the team. 
The question will be provided to you as a natural language question.

In order to answer the user's question, you are given context from fabrication logs and associated references. 

Rules:
1. Base your answer ONLY on the provided context.
2. If the context doesn't contain the answer, say "I couldn't find that information in the logs."
3. Cite your sources using the [Ref X] tags provided in the context.
4. Be technical and be concise. 
5. If there is a specific project name or document associated with the context, explicitly state it.

The logs provide detailed parameters for dicing silicon using various tools and recipes. Here are the recommended parameters:

1. **Blade Type**:
   - Use a **hub blade** such as **eszakiel_220614** ([Fab Log Ref 1]) or **oliver_210620** ([Fab Log Ref 6]).
   - Alternatively, use a **resin blade** like **jfherrm 2204** for specific recipes ([Fab Log Ref 5]).

2. **Spindle Speed**:
   - Typical spindle speeds range from **20,000 RPM** ([Fab Log Ref 5]) to **30,000 RPM** ([Fab Log Ref 3, Ref 7]).

3. **Feed Speed**:
   - Common feed speeds include:
     - **0.5 mm/s** for controlled dicing ([Fab Log Ref 3, Ref 5, Ref 6]).
     - **2.0 mm/s** for faster dicing ([Fab Log Ref 7]).

4. **Blade Height**:
   - Blade height is typically set to **0.05 mm** ([Fab Log Ref 3, Ref 7]).

5. **Water Flow**:
   - Water flow is set to **0.5 L/min** for both channels ([Fab Log Ref 1, Ref 3]).

6. **Alignment**:
   - Align theta to the flat edge of the silicon wafer for precision ([Fab Log Ref 2]).
   - Use position readout for accurate alignment ([Fab Log Ref 5]).

7. **Kerf Width**:
   - Kerf widths vary depending on the blade and recipe, e.g., **260 µm** ([Fab Log Ref 5]) or **107.1 µm** ([Fab Log Ref 7]).

8. **Recipe**:
   - Use recipes such as **esz_LN-Si** ([Fab Log Ref 1, Ref 4]) or **kmultani_5x5** ([Fab Log Ref 5]) for silicon dicing.

To prevent chips from flying off during dicing, the logs suggest several strategies:

1. **Tape Adhesion**:
   - Use **stickier tape** to improve adhesion during dicing. For example, in the **250305_lowfats05_fab_doc.md**, chip loss was attributed to insufficient tape adhesion, and the suggestion was made to use stickier tape ([Fab Log Ref 4]).
   - Ensure proper tape pressing using tools like a **dark gray roller** to minimize chip movement, as noted in the **FLXM02 _ lowfATS01 Process Notes.md** ([Fab Log Ref 6]).

2. **Dicing Parameters**:
   - Reduce **cut depth** to avoid excessive stress on the chips. In the **250305_lowfats05_fab_doc.md**, chip loss occurred at various cut depths, and decreasing the cut depth was recommended ([Fab Log Ref 4]).
   - Use a **low feed rate** (e.g., **0.5 mm/s**) and controlled **spindle speed** (e.g., **30,000 RPM**) to minimize vibrations and stress during dicing ([Fab Log Ref 6]).
   - Maintain **water flow** at **0.5 L/min** to cool the blade and reduce chip movement ([Fab Log Ref 6]).

3. **Sandwich Tape Method**:
   - Apply a second layer of tape (sandwich method) after the first set of cuts to secure the chips before performing the second set of cuts. This method was successfully used in the **FLXM02 _ lowfATS01 Process Notes.md** ([Fab Log Ref 6]).
   - Avoid pressing too hard on the tape sandwich near the chips to prevent shifts ([Fab Log Ref 6]).

4. **Alignment**:
   - Proper alignment of the chips and tape is critical. For example, in the **250305_lowfats05_fab_doc.md**, chip orientation was carefully adjusted to minimize loss ([Fab Log Ref 7]).

The logs provide detailed considerations for fracturing Josephson junctions in BEAMER:

1. **Manual Field Placement**:
   - Manual field placement in BEAMER is critical to avoid overlapping fields, which can cause unpredictable assignment of polygons. Overlapping fields lead to errors in the traversal path and can compromise the integrity of the junctions ([Fab Log Ref 1]).

2. **Traversal Path Verification**:
   - After fracturing, verify that the traversal path writes one entire SQUID array before moving to another. This ensures efficient traversal and minimizes errors during exposure ([Fab Log Ref 1]).

3. **Fracturing Settings**:
   - **Conventional fracturing**: Used to maintain predictable field boundaries.
   - **No compaction**: Ensures that the fractured geometry does not compress or distort the design.
   - **Shot pitch fracturing**: None, to avoid introducing additional artifacts.
   - **Dose to class**: Used to optimize exposure doses for different regions.
   - **Multipass**: None, to simplify the exposure process.
   - **Extent**: Auto, to allow BEAMER to automatically determine the field extent ([Fab Log Ref 1]).

4. **Critical Observations**:
   - Fracturing errors can result in alignment issues and incomplete resist removal, leading to scum in the junction critical region and SQUID loop. Longer develop times and ghost lining may help mitigate scum ([Fab Log Ref 4]).

To strip HSQ after a failed spin, the logs suggest using **25% TMAH (Tetramethylammonium Hydroxide)** as the primary method:
1. **Wet Strip with TMAH**:
   - In the **LNOSM2 Process Notes**, HSQ was stripped using **25% TMAH** after a failed spin. This method was used to clean the chip and prepare it for re-spinning ([Fab Log Ref 1, Ref 3]).
   - TMAH effectively removes HSQ without damaging the chip surface, as noted in multiple instances ([Fab Log Ref 1, Ref 3]).
   - This approach was specifically used when the HSQ spin did not spread properly or failed to adhere uniformly ([Fab Log Ref 3]).

2. **Observation**:
   - Stripping HSQ with TMAH was necessary to remove the failed spin and allow for re-spinning ([Fab Log Ref 1, Ref 3]).

To etch **500 µm of silicon**, the logs suggest using **Deep Silicon Etch (DSE)** methods, such as DRIE or PT-DSE. Here are the relevant parameters and observations:

1. **Etch Method**:
   - **Deep Silicon Etch (DSE)** is the preferred method for etching large depths of silicon. For example:
     - In the **20210915 BBMMW02 fabrication notes**, 250 µm of silicon was etched using **365 cycles** with an etch rate of **0.685 µm/cycle** ([Fab Log Ref 2]).
     - In the same fabrication notes, another DSE process achieved an etch rate of **0.83 µm/cycle**, requiring **362 cycles** for a 300 µm etch ([Fab Log Ref 5]).
     - To achieve 500 µm, you would need approximately **600–730 cycles**, depending on the etch rate.

2. **Tool and Recipe**:
   - Use tools like **PT-DSE** or **FAT EBTr** for silicon etching.
   - Recipes such as **rvanlaer** or **LINQS** are commonly used for DSE ([Fab Log Ref 4, Ref 5]).

3. **Etch Parameters**:
   - **Etch Rate**: Typical etch rates range from **0.685 µm/cycle** to **0.83 µm/cycle** ([Fab Log Ref 2, Ref 5]).
   - **Cycles**: For 500 µm, calculate the number of cycles based on the etch rate. For example:
     - At **0.685 µm/cycle**, you would need ~730 cycles.
     - At **0.83 µm/cycle**, you would need ~600 cycles.
   - **Power**: In the **230906_HIR01_Process_Notes**, power settings were **1200 W** for etching and **0 W** for cooling ([Fab Log Ref 3]).
   - **Cooling**: Include cooling steps (e.g., **1 min cooling after every 30 loops**) to prevent overheating and maintain uniform etching ([Fab Log Ref 3]).

4. **Observations**:
   - Ensure proper wafer adhesion to prevent the wafer from falling off during the etch. For example, in the **20210915 BBMMW02 fabrication notes**, kapton tape was used to secure the wafer ([Fab Log Ref 2]).
   - Monitor He pressure and chamber conditions to avoid process errors ([Fab Log Ref 7]).

You are an expert fabrication process engineer who works on a team. 
You are tasked with answering user questions and providing advice to the user based on: (1) previous fabrication logs generated by the team, and (2) previous discussions with team members. 

The question will be provided to you as a natural language question.

In order to answer the user's question, you are given context from: (1) previous fabrication logs and associated references, and (2) previous discussions with team members. 

Rules:
1. Base your answer ONLY on the provided context.
2. Your answer should explicitly differentiate between context from previous fabrication logs and context from previous discussions with team members. 
3. Your answer should be organized as follows: (1) summarize your answer from previous fabrication logs, (2) summarize your answer from previous discussions, (3) cite the previous fabrication logs, (4) cite the previous discussions. 
4. Cite your fabrication log sources using the [Ref X] tags provided in the context
5. Cite your discussion sources using the [Ref X] tags provided in the context
6. If the context doesn't contain the answer, say "I couldn't find that information in the logs or from previous discussions with other team members.” 
7. Be technical and be concise. 
8. If there is a specific project name or document associated with the fab context, explicitly state 
9. If there is a specific person or name associated with the discussion context, explicitly state it.

### Summary from Previous Fabrication Logs:
To strip crosslinked resist, the fabrication logs suggest the following methods:
1. **Nanostrip Soak**:
   - In the **240216_single_mask_circuit_development.md**, crosslinked resist was successfully removed by soaking the chip in **Nanostrip at 35°C for 1200 seconds (20 minutes)**. This method was observed to remove all crosslinked resist without affecting Nb layers ([Fab Log Ref 4]).
   - Note: Nanostrip may attack sensitive metals like aluminum, so caution is required ([Fab Log Ref 4]).

2. **Hot NMP**:
   - In the **LN_ Releasing Structures in PT-DSE.md**, NMP was heated to **80°C** for 60 minutes to strip resist. This method is less aggressive and can be used for crosslinked resist ([Fab Log Ref 3]).
   - Followed by IPA spray and soak to clean residual resist ([Fab Log Ref 3]).

3. **Solvent Cleaning**:
   - Acetone and IPA sprays were used in **240216_single_mask_circuit_development.md**, but these methods were insufficient for removing crosslinked resist ([Fab Log Ref 2, Ref 6]).

### Summary from Previous Discussions:
From discussions with Takuma Makihara:
1. **Nanostrip**:
   - Nanostrip at **35°C for 20 minutes** is effective for removing crosslinked resist but may attack sensitive metals like aluminum ([Discussion Ref 1, Ref 2]).

2. **Hot NMP**:
   - **Hot NMP (heated to 80°C)** should be attempted first for crosslinked resist. It is less aggressive and safer for sensitive materials like aluminum ([Discussion Ref 1, Ref 2]).

3. **Piranha Solution**:
   - For a more aggressive clean, **Piranha solution** can be used, but it has the same chemistry as Nanostrip and will also attack sensitive metals like aluminum. Use with caution ([Discussion Ref 1, Ref 2]).